Development of New Arsenic Based Amidation Catalysts

The formation of amides is a reaction that is contucted on a multi-ton scale annually in the pharmaceutical industry. Because the reaction requires the use of toxic and expensive reagents and because a substantial ammount of waste is generated, much effort is being devoted to eliminating both of these limitations. Current research is aimed at finding an efficient catalyst for this reaction that will significantly reduce waste and can be recycled. While some catalysts have been developed for this reaction, currently there are no catalysts that are efficient enough to be used on a large scale. Studies in the Boisvert lab have identified that arsenic compounds can catalyze the direct amidation between a carboxylic acid and amine. While it was discovered that arsenic compounds can act as catalysts, their activity is not yet high enough to be generally useful in synthesis. These previous studies focused on modifying the electron density at the arsenic center in order to influence reactivity. In order to possibly increase reactivity, new arsenic-based catalysts constrained in small rings were pursued

The effects of entrepreneurship education

Entrepreneurship education ranks high on policy agendas in Europe and the US, but little research is available to assess its impact. To help close this gap we investigate whether entrepreneurship education a?ects intentions to be entrepreneurial uniformly or whether it leads to greater sorting of students. The latter can reduce the average intention to be entrepreneurial and yet be socially beneficial. This paper provides a model of learning in which entrepreneurship education generates signals to students. Drawing on the signals, students evaluate their aptitude for entrepreneurial tasks. The model is tested using data from a compulsory entrepreneurship course. Using ex ante and ex post survey responses from students, we find that intentions to found decline somewhat although the course has significant positive e?ects on students’ self-assessed entrepreneurial skills. The empirical analysis supports the hypothesis that students receive informative signals and learn about their entrepreneurial aptitude. We outline implications for educators and public policy

Bifactor Model of the Sport Concussion Assessment Tool Symptom Checklist: Replication and Invariance Across Time in the CARE Consortium Sample

Background: Identifying separate dimensions of concussion symptoms may inform a precision medicine approach to treatment. It was previously reported that a bifactor model identified distinct acute postconcussion symptom dimensions. Purpose: To replicate previous findings of a bifactor structure of concussion symptoms in the Concussion Assessment Research and Education (CARE) Consortium sample, examine measurement invariance from pre- to postinjury, and evaluate whether factors are associated with other clinical and biomarker measures. Study design: Cohort study (Diagnosis); Level of evidence, 2. Methods: Collegiate athletes were prospectively evaluated using the Sport Concussion Assessment Tool-3 (SCAT-3) during preseason (N = 31,557); 2789 were followed at <6 hours and 24 to 48 hours after concussion. Item-level SCAT-3 ratings were analyzed using exploratory and confirmatory factor analyses. Bifactor and higher-order models were compared for their fit and interpretability. Measurement invariance tested the stability of the identified factor structure across time. The association between factors and criterion measures (clinical and blood-based markers of concussion severity, symptom duration) was evaluated. Results: The optimal structure for each time point was a 7-factor bifactor model: a General factor, on which all items loaded, and 6 specific factors-Vestibulo-ocular, Headache, Sensory, Fatigue, Cognitive, and Emotional. The model manifested strict invariance across the 2 postinjury time points but only configural invariance from baseline to postinjury. From <6 to 24-48 hours, some dimensions increased in severity (Sensory, Fatigue, Emotional), while others decreased (General, Headache, Vestibulo-ocular). The factors correlated with differing clinical and biomarker criterion measures and showed differing patterns of association with symptom duration at different time points. Conclusion: Bifactor modeling supported the predominant unidimensionality of concussion symptoms while revealing multidimensional properties, including a large dominant General factor and 6 independent factors: Headache, Vestibulo-ocular, Sensory, Cognitive, Fatigue, and Emotional. Unlike the widely used SCAT-3 symptom severity score, which declines gradually after injury, the bifactor model revealed separable symptom dimensions that have distinct trajectories in the acute postinjury period and different patterns of association with other markers of injury severity and outcome. Clinical relevance: The SCAT-3 total score remains a valuable, robust index of overall concussion symptom severity, and the specific factors identified may inform management strategies. Because some symptom dimensions continue to worsen in the first 24 to 48 hours after injury (ie, Sensory, Fatigue, Emotional), routine follow-up in this time frame may be valuable to ensure that symptoms are managed effectively

CMS physics technical design report : Addendum on high density QCD with heavy ions

Peer reviewe

Micro-Foundations of Organizational Design and Sustainability: The Mediating Role of Learning Ambidexterity

This paper builds on prior scholarly works by examining the relationship between organizing paradox (formalization and decentralization), and organizational levels of learning paradoxes, i.e. exploration and exploitation, and firms’ outcomes (organizational creativity, organizational resilience and organizational energy). Using data from 98 executives and 325 senior employees working across a diverse range of firms operating in the Middle East, the findings suggest that organizing paradox (formalization and decentralization) has a positive impact on learning ambidexterity. In addition, we also found that learning ambidexterity has a positive impact on both organizational resilience and organizational energy. Furthermore, the results indicate that learning ambidexterity mediates the relationship between organizing paradox and organizational creativity. These findings provide important insights into the micro-foundation aspects of organizational ambidexterity

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security

A comparison of grid-based techniques for Navier-Stokes fluid simulation in computer graphics

Fluid simulation is becoming increasingly common in the film industry and in computer games, however, understanding and implementing a numerical solution to the Navier-Stokes equation can be a daunting task. In this thesis we present an introduction to fluid simulation in computer graphics with a full derivation of the compressible and incompressible Navier-Stokes equation from Newton's Second Law, explaining concepts such as pressure and viscosity as they are derived. We also present a survey and comparison of four different methods for solving the advection equation: a simple 1st order differencing method, a 4 th order QUICK scheme, the popular semi-lagrangian method, and the PIC & FLIP particle based methods. We present these advection scheme comparisons in a series simplified 1D channel plots, and a set of 2D fluid animations. Based on these results, we classify algorithms as stable or unstable, and discuss methods to prevent divergence in unstable solvers

A Comparison of Grid-Based Techniques for Navier-Stokes Fluid Simulation in Computer Graphics

Fluid simulation is becoming increasingly common in the film industry and in computer games, however, understanding and implementing a numerical solution to the Navier-Stokes equation can be a daunting task. In this thesis we present an introduction to fluid simulation in computer graphics with a full derivation of the compressible and incompressible Navier-Stokes equation from Newton's Second Law, explaining concepts such as pressure and viscosity as they are derived. We also present a survey and comparison of four different methods for solving the advection equation: a simple 1st order differencing method, a 4th order QUICK scheme, the popular semi-lagrangian method, and the PIC &amp; FLIP particle based methods. We present these advection scheme comparisons in a series simplified 1D channel plots, and a set of 2D fluid animations. Based on these results, we classify algorithms as stable or unstable, and discuss methods to prevent divergence in unstable solvers