Coupling of marine and continental oxygen isotope records during the Eocene-Oligocene transition

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148587/1/Sheldon_et_al_2016_GSA_Bulletin-EOT_marine-terrestrial_comparison.pd

Converting Boundary Representation Solid Models to Half-Space Representation Models for Monte Carlo Analysis

Solid modeling computer software systems provide for the design of three-dimensional solid models used in the design and analysis of physical components. The current state-of-the-art in solid modeling representation uses a boundary representation format in which geometry and topology are used to form three-dimensional boundaries of the solid. The geometry representation used in these systems is cubic B-spline curves and surfaces--a network of cubic B-spline functions in three-dimensional Cartesian coordinate space. Many Monte Carlo codes, however, use a geometry representation in which geometry units are specified by intersections and unions of half-spaces. This paper describes an algorithm for converting from a boundary representation to a half-space representation

Catastrophizing mediates the relationship between the personal belief in a just world and pain outcomes among chronic pain support group attendees

Health-related research suggests the belief in a just world can act as a personal resource that protects against the adverse effects of pain and illness. However, currently, little is known about how this belief, particularly in relation to one’s own life, might influence pain. Consistent with the suggestions of previous research, the present study undertook a secondary data analysis to investigate pain catastrophizing as a mediator of the relationship between the personal just world belief and chronic pain outcomes in a sample of chronic pain support group attendees. Partially supporting the hypotheses, catastrophizing was negatively correlated with the personal just world belief and mediated the relationship between this belief and pain and disability, but not distress. Suggestions for future research and intervention development are made

Selective exposure to deserved outcomes

Research has shown that people often reinterpret their experiences of others' harm and suffering to maintain the functional belief that people get what they deserve (e.g., by blaming the victim). Rather than focusing on such reactive responses to harm and suffering, across 7 studies we examined whether people selectively and proactively choose to be exposed to information about deserved rather than undeserved outcomes. We consistently found that participants selectively chose to learn that bad (good) things happened to bad (good) people (Studies 1 to 7)—that is, they selectively exposed themselves to deserved outcomes. This effect was mediated by the perceived deservingness of outcomes (Studies 2 and 3), and was reduced when participants learned that wrongdoers otherwise received “just deserts” for their transgressions (Study 7). Participants were not simply selectively avoiding information about undeserved outcomes but actively sought information about deserved outcomes (Studies 3 and 4), and participants invested effort in this pattern of selective exposure, seeking out information about deserved outcomes even when it was more time-consuming to find than undeserved outcomes (Studies 5 and 6). Taken together, these findings cast light on a more proactive, anticipatory means by which people maintain a commitment to deservingness

A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.BACKGROUND: The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. METHODS: We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. RESULTS: We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. CONCLUSIONS: Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent critical appraisal of network meta-analyses, enhanced standardization of reporting, and integration with health economic evaluations which are frequently Excel-based.CC is a recipient of a Vanier Canada Graduate Scholarship from the Canadian Institutes of Health Research (funding reference number—CGV 121171) and is a trainee on the Canadian Institutes of Health Research Drug Safety and Effectiveness Network team grant (funding reference number—116573). BH is funded by a New Investigator award from the Canadian Institutes of Health Research and the Drug Safety and Effectiveness Network. This research was partly supported by funding from CADTH as part of a project to develop Excel-based tools to support the conduct of health technology assessments. This research was also supported by Cornerstone Research Group

Determinants for the success of software startups: Insights from a regional cluster

In recent years, we have seen a growing interest in technology-based companies and intensive knowledge. Several regional clusters have appeared supported in dynamic entrepreneurial ecosystems which, alongside intrinsic aspects of the business, are important determinants of the success of new companies. However, most startups created in these innovation-oriented spaces do not survive the first years of life, due to the high competitiveness of the technological market, due to deficiencies in the business model, due to the support conditions provided by the surrounding ecosystem, and finally due to a weak adjustment between all these dimensions. Among several models available, the Early-Life Decision Model (ELDM) presents itself as an interesting framework for studying the development and success conditions of software companies. This article discusses the application of the ELDM based on a series of interviews conducted to 15 Portuguese software startups installed in a technological cluster located in the northeast of Portugal. Based on the results obtained, it was appropriate to add a new dimension to the ELDM model (learning) and complementing it with the perspectives of the business type and internal versus external determinants.This work was supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT (Fundação para a Ciência e a Tecnologia) within the Project Scope: UID/CEC/00319/2013

A questionnaire to identify patellofemoral pain in the community: an exploration of measurement properties

Background Community-based studies of patellofemoral pain (PFP) need a questionnaire tool that discriminates between those with and those without the condition. To overcome these issues, we have designed a self-report questionnaire which aims to identify people with PFP in the community. Methods Study designs: comparative study and cross-sectional study. Study population: comparative study: PFP patients, soft-tissue injury patients and adults without knee problems. Cross-sectional study: adults attending a science festival. Intervention: comparative study participants completed the questionnaire at baseline and two weeks later. Cross-sectional study participants completed the questionnaire once. The optimal scoring system and threshold was explored using receiver operating characteristic curves, test-retest reliability using Cohen’s kappa and measurement error using Bland-Altman plots and standard error of measurement. Known-group validity was explored by comparing PFP prevalence between genders and age groups. Results Eighty-four participants were recruited to the comparative study. The receiver operating characteristic curves suggested limiting the questionnaire to the clinical features and knee pain map sections (AUC 0.97 95 % CI 0.94 to 1.00). This combination had high sensitivity and specificity (over 90 %). Measurement error was less than the mean difference between the groups. Test–retest reliability estimates suggest good agreement (N = 51, k = 0.74, 95 % CI 0.52–0.91). The cross-sectional study (N = 110) showed expected differences between genders and age groups but these were not statistically significant. Conclusion A shortened version of the questionnaire, based on clinical features and a knee pain map, has good measurement properties. Further work is needed to validate the questionnaire in community samples

A bayesian meta-analysis of multiple treatment comparisons of systemic regimens for advanced pancreatic cancer

© 2014 Chan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Background: For advanced pancreatic cancer, many regimens have been compared with gemcitabine (G) as the standard arm in randomized controlled trials. Few regimens have been directly compared with each other in randomized controlled trials and the relative efficacy and safety among them remains unclear

A systematic comparison of software dedicated to meta-analysis of causal studies

<p>Abstract</p> <p>Background</p> <p>Our objective was to systematically assess the differences in features, results, and usability of currently available meta-analysis programs.</p> <p>Methods</p> <p>Systematic review of software. We did an extensive search on the internet (Google, Yahoo, Altavista, and MSN) for specialized meta-analysis software. We included six programs in our review: Comprehensive Meta-analysis (CMA), MetAnalysis, MetaWin, MIX, RevMan, and WEasyMA. Two investigators compared the features of the software and their results. Thirty independent researchers evaluated the programs on their usability while analyzing one data set.</p> <p>Results</p> <p>The programs differed substantially in features, ease-of-use, and price. Although most results from the programs were identical, we did find some minor numerical inconsistencies. CMA and MIX scored highest on usability and these programs also have the most complete set of analytical features.</p> <p>Conclusion</p> <p>In consideration of differences in numerical results, we believe the user community would benefit from openly available and systematically updated information about the procedures and results of each program's validation. The most suitable program for a meta-analysis will depend on the user's needs and preferences and this report provides an overview that should be helpful in making a substantiated choice.</p

The effects of supervised exercise training 12-24 months after bariatric surgery oh physical function and body composition: a randomised controlled trial

BACKGROUND: Bariatric surgery is effective for the treatment of stage II and III obesity and its related diseases, although increasing evidence is showing weight regain ~12–24 months postsurgery. Weight regain increases the risk of physical function decline, which negatively affects an individual's ability to undertake activities of daily living. The study assessed the effects of a 12-week supervised exercise intervention on physical function and body composition in patients between 12 and 24 months post bariatric surgery. METHODS: Twenty-four inactive adult bariatric surgery patients whose body mass index remained 30 kg m2 12 to 24 months post surgery were randomised to an exercise intervention (n=12) or control group (n=12). Supervised exercise consisted of three 60-min gym sessions per week of moderate intensity aerobic and resistance training for 12 weeks. Control participants received usual care. The incremental shuttle walk test (ISWT) was used to assess functional walking performance after the 12-week exercise intervention, and at 24 weeks follow-up. Measures of anthropometric, physical activity, cardiovascular and psychological outcomes were also examined. Using an intention-to-treat protocol, independent t-tests were used to compare outcome measures between groups. RESULTS: Significant improvements in the exercise group were observed for the ISWT, body composition, physical function, cardiovascular and self-efficacy measures from baseline to 12 weeks. A large baseline to 12-week change was observed for the ISWT (exercise: 325.00±117.28 m; control: 355.00±80.62 m, P<0.001). The exercise group at 24 weeks recorded an overall mean improvement of 143.3±86.6 m and the control group recorded a reduction of −32.50±75.93 m. Findings show a 5.6 kg difference between groups in body mass change from baseline to 24 weeks favouring the exercise group. CONCLUSION: A 12-week supervised exercise intervention led to significant improvements in body mass and functional walking ability post intervention, with further improvements at the 24-week follow-up