Controversy and Conversation

In this research study, we examined the relationship between the degree of controversy (referred to as controversiality henceforth) of subject matter and the amount of conversation generated by the subject matter. In the first step of the research project, we analyzed online conversations. Our data set included data on the attributes of 207 news articles linked to Topix.com. Our analysis of these articles indicated that on average, articles of medium controversy generated the largest volume of conversation when using the number of comments as the metric. These findings led us to create a survey to determine if these results would be replicated in a laboratory study. In the survey, the likelihood of sharing the article was designated as the metric for the volume of conversation. Survey results showed that people were more likely to share articles of high controversy, which is contrary to conclusions drawn from our analysis of data from Topix.com. The findings are applicable to any writers who disseminate information and opinions

Microfabricated Substrate to Achieve In Vivo-Like Cardiomyocyte Morphology and Electrical Propagation in Neonatal Cell Culture

Because of the complexity of the in vivo environment, much physiological and pathological understanding of the human body is obtained through cell culture. To gain clinically relevant knowledge, having a cell culture model that mimics the corresponding in vivo tissue would be advantageous. For example, when studying the mechanical and electrical coupling between cardiac cells, imitating in vivo cellular morphology correlates with improved electrical coupling. This has applications within drug screening; by being able to test for cardiotoxicity with a cell culture model, this reduces the resources needed to screen pharmaceuticals for negative side effects. In conventional cardiomyocyte culture, cells spread randomly and express irregular, star-like morphology without forming in vivo-like structures. The purpose of this aim was to utilize microfabricated features such as wrinkles on polydimethylsiloxane (PDMS) and examine the effects of substrate topography on cardiomyocyte morphology and function. Of the substrate topographical parameters that result in optimal cellular alignment, we evaluate the electrical cohesiveness of these cell culture models via cellular calcium transients. Mammalian cardiomyocytes use the calcium-induced calcium release (CICR) pathway to induce calcium transients that are integral to the excitation-contraction cycle. Their efficiency in this is an indication of their electrophysiological maturity. Due to the intimate dynamics between physical and functional maturity, we examined how substrate topography affects the ability of cultured neonatal cardiomyocytes to cycle calcium ions in response to external stimulation

Is a Computer Science Degree the Golden Ticket? Effects of Race, Place, and Degree Institution on First Job Outcomes in Texas

Research and policy efforts to increase the racial diversity of STEM fields have focused on how to prime the educational pipeline through interventions in schools and universities. This thesis focuses on recent college graduates who have successfully cleared a key hurdle and graduated with a bachelor’s degree in computer science. I use original survey data from three public universities across Texas to determine whether there are differences in first job outcomes between Hispanic and non-Hispanic computer scientists on the elite tech labor market. I find that university attended is the most consistent predictor of labor market success. Differences between Hispanics and non-Hispanics in job outcomes are mostly attributable to the concentration of Hispanic computer science degree holders in a non-elite, geographically peripheral university. Controlling for university attended, Hispanics are as likely to work in a prestige tech hub and in a core software job as their white and Asian peers; however, they earn lower wages. In addition, results suggest a positive association between geographic mobility, higher earnings, and the likelihood of working in desirable, degree-related jobs. Results suggest that a closer inspection of segregational mechanisms at the post-secondary level is needed to fully understand its effects on elite job opportunities. Although a degree in computer science can provide a ticket to one of the most lucrative occupational fields in Texas, racial stratification within this field occurs early in the career and likely translates into long-lasting socioeconomic inequalities

Ada : context-sensitive context-sensing on mobile devices

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 67-72).This thesis describes the design, implementation, and evaluation of Ada, a context-sensing service for mobile devices. Ada explores new points in the accuracy-energy-responsiveness design space for mobile context sensing. The service exports an API that allows a client to express interest in one or more context types (mode-of-movement, indoor/outdoor, and entry/exit to/from named regions), and subscribe to specific modes within each context (e.g., "walking" or "running", but not any other movement mode). Each context type in Ada can be in one of a set of mutually exclusive states. Each context has a detector that returns its estimate of the mode. To achieve high accuracy and low energy consumption, the detectors take both the existing context and the desired subscriptions into account, adjusting both the types of sensors and the sampling rates. To accurately determine the movement mode, Ada uses a new peak frequency feature from acceleration magnitudes, combining it with two other features. We present results from trace-driven experiments over carefully labeled data from real users, finding that our mode-of-movement detector achieves an accuracy of 93%, out-performing previous proposals like UCLA (55%), EEMSS (83%) and SociableSense (72%), while consuming between 2 and 3x less energy.by Yu-Han Chen.S.M

Designing a Context-Sensitive Context Detection Service for Mobile Devices

This paper describes the design, implementation, and evaluation of Amoeba, a context-sensitive context detection service for mobile devices. Amoeba exports an API that allows a client to express interest in one or more context types (activity, indoor/outdoor, and entry/exit to/from named regions), subscribe to specific modes within each context (e.g., "walking" or "running", but no other activity), and specify a response latency (i.e., how often the client is notified). Each context has a detector that returns its estimate of the mode. The detectors take both the desired subscriptions and the current context detection into account, adjusting both the types of sensors and the sampling rates to achieve high accuracy and low energy consumption. We have implemented Amoeba on Android. Experiments with Amoeba on 45+ hours of data show that our activity detector achieves an accuracy between 92% and 99%, outperforming previous proposals like UCLA* (59%), EEMSS (82%) and SociableSense (72%), while consuming 4 to 6× less energy

Pantheon 1.0, a manually verified dataset of globally famous biographies

We present the Pantheon 1.0 dataset: a manually verified dataset of individuals that have transcended linguistic, temporal, and geographic boundaries. The Pantheon 1.0 dataset includes the 11,341 biographies present in more than 25 languages in Wikipedia and is enriched with: (i) manually verified demographic information (place and date of birth, gender) (ii) a taxonomy of occupations classifying each biography at three levels of aggregation and (iii) two measures of global popularity including the number of languages in which a biography is present in Wikipedia (L), and the Historical Popularity Index (HPI) a metric that combines information on L, time since birth, and page-views (2008-2013). We compare the Pantheon 1.0 dataset to data from the 2003 book, Human Accomplishments, and also to external measures of accomplishment in individual games and sports: Tennis, Swimming, Car Racing, and Chess. In all of these cases we find that measures of popularity (L and HPI) correlate highly with individual accomplishment, suggesting that measures of global popularity proxy the historical impact of individuals