Temporal trends in satellite-derived erythemal UVB and implications for ambient sun exposure assessment

Ultraviolet radiation (UVR) has been associated with various health outcomes, including skin cancers, vitamin D insufficiency, and multiple sclerosis. Measurement of UVR has been difficult, traditionally relying on subject recall. We investigated trends in satellite-derived UVB from 1978 to 2014 within the continental United States (US) to inform UVR exposure assessment and determine the potential magnitude of misclassification bias created by ignoring these trends. Monthly UVB data remotely sensed from various NASA satellites were used to investigate changes over time in the United States using linear regression with a harmonic function. Linear regression models for local geographic areas were used to make inferences across the entire study area using a global field significance test. Temporal trends were investigated across all years and separately for each satellite type due to documented differences in UVB estimation. UVB increased from 1978 to 2014 in 48% of local tests. The largest UVB increase was found in Western Nevada (0.145 kJ/m2 per five-year increment), a total 30-year increase of 0.87 kJ/m2. This largest change only represented 17% of total ambient exposure for an average January and 2% of an average July in Western Nevada. The observed trends represent cumulative UVB changes of less than a month, which are not relevant when attempting to estimate human exposure. The observation of small trends should be interpreted with caution due to measurement of satellite parameter inputs (ozone and climatological factors) that may impact derived satellite UVR nearly 20% compared to ground level sources. If the observed trends hold, satellite-derived UVB data may reasonably estimate ambient UVB exposures even for outcomes with long latency phases that predate the satellite record

Women\u27s Quest to Occupy Executive Positions in Corporate America

Women comprise 50.8% of the United States population and 47% of the workforce, and over the past few decades, many women have been promoted to midmanagement positions in Fortune 500 and other major corporations, but few run companies at the executive levels. The research problem addressed the underrepresentation of women in top leadership positions in the executive suite. The purpose of this study was to explore the perceptions of women in upper level management in large corporations on rising to the C-suite. A basic qualitative naturalistic inquiry was used employing interviews in collecting and analyzing the data. The targeted population was 15 women in senior positions between the ages of 25 and 60, who have worked for a company with a minimum of 5 years\u27 experience. Introductions by friends and snowballing sampling were used to select 15 participants for the semistructured interviews. The results of the interviews were analyzed through the completion of a content analysis obtained through coding to allow for the identification of emergent themes. Key findings indicated the emergence of the following themes: loss of confidence, mentoring, sponsoring, and diversity. The study was socially significant in that it provided information for policy changes, access to sponsorship and mentorship programs, and promotion of social change in relation to gender equality in the workplace

The financial analysis of industrial securities

Thesis (M.A.)--Boston University, 1949. This item was digitized by the Internet Archive

Environmental Education

The need for a new profession devoted to environmental matters is asserted. The qualities of such a profession are sketched, and it is argued that new initiatives in environmental education are needed in the form of graduate, professional programs with primary emphasis on practice. An example 2-year program is presented. A fundamental requirement is scientific competence; undergraduate preparation in the sciences or engineering is mandatory. The graduate curriculum itself is built on three primary cores: environmental science and engineering, business and management, and public policy. Additionally, an environmental round table is proposed as a focal point for academic, industrial, governmental, and public discussion on environmental matters. The round table would provide oversight for the professional educational program and an affiliated research institute

Learning Rich Geographical Representations: Predicting Colorectal Cancer Survival in the State of Iowa

Neural networks are capable of learning rich, nonlinear feature representations shown to be beneficial in many predictive tasks. In this work, we use these models to explore the use of geographical features in predicting colorectal cancer survival curves for patients in the state of Iowa, spanning the years 1989 to 2012. Specifically, we compare model performance using a newly defined metric -- area between the curves (ABC) -- to assess (a) whether survival curves can be reasonably predicted for colorectal cancer patients in the state of Iowa, (b) whether geographical features improve predictive performance, and (c) whether a simple binary representation or richer, spectral clustering-based representation perform better. Our findings suggest that survival curves can be reasonably estimated on average, with predictive performance deviating at the five-year survival mark. We also find that geographical features improve predictive performance, and that the best performance is obtained using richer, spectral analysis-elicited features.Comment: 8 page

Modeling radio networks

We describe a modeling framework and collection of foundational composition results for the study of probabilistic distributed algorithms in synchronous radio networks. Though the radio setting has been studied extensively by the distributed algorithms community, their results rely on informal descriptions of the channel behavior and therefore lack easy comparability and are prone to error caused by definition subtleties. Our framework rectifies these issues by providing: (1) a method to precisely describe a radio channel as a probabilistic automaton; (2) a mathematical notion of implementing one channel using another channel, allowing for direct comparisons of channel strengths and a natural decomposition of problems into implementing a more powerful channel and solving the problem on the powerful channel; (3) a mathematical definition of a problem and solving a problem; (4) a pair of composition results that simplify the tasks of proving properties about channel implementation algorithms and combining problems with channel implementations. Our goal is to produce a model streamlined for the needs of the radio network algorithms community