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Columbia, CA, United States

Claremont McKenna College is a private, coeducational liberal arts college and a member of the Claremont Colleges located in Claremont, California, United States.Founded as a men's college in 1946, CMC became co-educational in 1976. Its 69-acre campus is located 35 miles east of Downtown Los Angeles. The college focuses primarily on undergraduate education, but in 2007 it established the Robert Day School of Economics and Finance, which offers a masters program in finance. As of 2013, there are 1,254 undergraduate students and 20 graduate students.Claremont McKenna is ranked tied for eighth out of all liberal arts colleges by U.S. News & World Report. The Princeton Review rated Claremont McKenna 2nd in the nation for happiest students; The Daily Beast placed Claremont McKenna as one of the top 25 most rigorous colleges in the nation; and College Factual has Claremont McKenna as the 14th most selective college in the nation . Wikipedia.


Valdesolo P.,Claremont McKenna College | Graham J.,University of Southern California
Psychological Science | Year: 2014

Across five studies, we found that awe increases both supernatural belief (Studies 1, 2, and 5) and intentional-pattern perception (Studies 3 and 4)-two phenomena that have been linked to agency detection, or the tendency to interpret events as the consequence of intentional and purpose-driven agents. Effects were both directly and conceptually replicated, and mediational analyses revealed that these effects were driven by the influence of awe on tolerance for uncertainty. Experiences of awe decreased tolerance for uncertainty, which, in turn, increased the tendency to believe in nonhuman agents and to perceive human agency in random events. © The Author(s) 2013.


Morhardt J.E.,Claremont McKenna College
Business Strategy and the Environment | Year: 2010

All material related to environmental and social performance on the corporate internet sites of 454 Fortune Global 500 and Fortune 1000 companies in 25 industrial sectors was analyzed using the Pacific Sustainability Index. Maximum scores for individual sectors were 20-75 percent of the total possible, highest in the largest and most environmentally sensitive sectors and ranging generally linearly, as shown by plotting score versus rank, down to nearly zero in every sector. None of the variation in score is explained by corporate revenue in the Asian and European firms in this sample (revenues greater than about $9 billion), but there is a very weak correlation between score and revenue for American firms of this size, and a stronger one when Fortune 1000 companies (all American) with revenues smaller than this are included, suggesting that, as corporate size reaches a certain threshold, sustainability reporting becomes independent of it. © 2009 John Wiley & Sons, Ltd and ERP Environment.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: COMPUTATIONAL MATHEMATICS | Award Amount: 413.53K | Year: 2014

A signal is any data set that one would like to acquire, for example, an image, a large block of data, or an audio clip. One can imagine asking how quickly one would need to sample an audio clip so that from those samples alone, the audio clip could be accurately recovered. Would you need to sample every nanosecond, every millisecond, or every second? Compressive Signal Processing (CSP) shows that the important information in many signals can be obtained and recovered from far fewer samples than traditionally thought. The applications of CSP are widespread and include imaging (medical, hyperspectral, microscopy, biological), analog-to-information conversion, radar, large scale information synthesis, geophysical data analysis, computational biology, and many more. Although these applications are astounding, there has been a disconnect between the theoretical work in CSP and the use of CSP in practical settings. The goals of this project will bridge this gap by providing methods and analysis for CSP that apply to real-world signals and settings. Such work will lead to decreased scan time in MRI, reduced cost and energy consumption in computing infrastructures, improved detection of diseased crops from hyperspectral images, increased accuracy in radar, and improved compression and analysis in many other large-data applications. In addition, this project will involve students at all levels and introduce them to rigorous scientific research. The PI actively recruits members from under-represented populations, and will continue to promote diversity through her own research and outreach programs.

Early CSP models restrict the class of signals to those compressible in a very specific sense (sparse with respect to an orthonormal or incoherent basis). One goal of this project is to relax this restriction to allow for signals actually encountered in practice, such as those sparse in redundant, coherent, and highly overcomplete dictionaries. We will utilize both greedy approaches and optimization-based methods, tailored to specific dictionaries of interest, as well as more general methods for arbitrary bases. In addition, this project will develop adaptive CSP sampling schemes, where measurements of the signal are designed on the fly, as they are being taken. Traditional measurement schemes ignore this information, while adaptive schemes have the potential to significantly reduce reconstruction error, number of measurements, and computation time. We will identify optimal measurement strategies for constrained and unconstrained settings, and analyze how much one can actually gain from adaptivity from an information theoretic point of view. The project will also involve work in one-bit CSP, a new and exciting branch of CSP which handles extreme (and often more realistic) quantization. We will draw on sub-linear methods, where large errors appear naturally, and also use optimization based techniques along with adaptive quantization thresholds to reduce the recovery error below the best possible for non-adaptive quantization. In studying these topics, the research will bridge a large gap in the theory of CSP and provide a unified framework for both practitioners and researchers.


Grant
Agency: NSF | Branch: Standard Grant | Program: | Phase: ATMOSPHERIC CHEMISTRY | Award Amount: 142.54K | Year: 2015

This project is investigating the potential for agricultural emissions of nitrogen and sulfur gases from sources such as dairy farms, piggeries, and other animal production sources to lead to the formation of very small particles in the atmosphere. Previous studies have shown that gas phase compounds related to waste management practices from animal agriculture could influence the formation of atmospheric particles. This project includes laboratory, field and modeling studies to investigate the environmental fate of nitrogen and sulfur compounds from these sources.

An environmental chamber will be used to quantify secondary aerosol formation potentials at different relative humidities and temperatures for select amines (diethylamine (DEA), trimethylamine (TMA), butylamine (BA), a diamine, or NH3) oxidized in the presence of an organosulfur compound (methanethiol, dimethylsulfide (DMS), or dimethyldisulfide (DMDS)) or hydrogen sulfide. The investigators will perform field sampling of particulate matter and precursors at agricultural operations in Kentucky at the USDA-Agricultural Research Station (ARS) laboratory to determine the impact of elevated amine and sulfur concentrations on atmospheric chemistry.

Kinetic modeling calculations will help clarify the sequence of chemical reactions responsible for the data seen in laboratory experiments. This will, in turn, help explain emission rates observed in field observations. The investigators expect to elucidate the atmospheric oxidation routes for reduced sulfur compounds and amines. Empirical estimates of the aerosol formation potential of key agricultural emissions will be developed for use in predicting local and regional air quality impacts and emissions inventories of the reduced nitrogen and sulfur species will be developed as an additional input to air quality models.


Grant
Agency: NSF | Branch: Continuing grant | Program: | Phase: BIOLOGICAL OCEANOGRAPHY | Award Amount: 369.46K | Year: 2014

This CAREER grant uses a combination of laboratory studies, computer modeling, and field experiments to test the relative influence of temperature stress and energy limitation on the upper vertical limit of an intertidal barnacle (Balanus glandula). Understanding the mechanisms by which temperature limits an organisms success is critical to generating accurate predictions of the effect of climate change on biological systems. Past work in this field has emphasized the direct physiological stress of extreme temperatures, but it is unclear if such extreme conditions limit species in the wild. Alternately, animals may simply lack enough energy to defend against thermal extremes that they could otherwise tolerate. This work has three main objectives: 1) to extend an existing modeling approach in physiology (Dynamic Energy Budget) for use with intertidal species, which alternate daily between marine and terrestrial conditions, 2) to use the model, in conjunction with field experiments, to test the hypothesis that energy limitation, rather than direct thermal stress, limits the success of B. glandula in the wild; and, 3) to use field and laboratory measurements to explore how thermal tolerance and success differ between barnacle populations from California and Washington. Altogether, these projects will improve our understanding of the thermal physiology of B. glandula, specifically, and of the role of energy limitation in thermal stress, more generally.

The integrated education plan of this CAREER grant contains three specific objectives: 1) to use research opportunities to attract and retain students in biology majors, 2) to improve the retention and performance of women and minority undergraduates in an introductory biology course, and 3) to improve the understanding of science by the general college population. The grant activities will include: generating new research opportunities for undergraduate and high school students, the piloting of a research experience program for sophomore-level students, the establishment of a peer-study program for students in an introductory biology course, and the development of a new course for non-science majors that emphasizes scientific literacy. The educational effectiveness of these programs will be rigorously tested and the results will inform the future teaching activities of the PI, her department, and the greater academic science community. The broader impacts of this CAREER grant will be 1) broadening the participation of women and under-represented minorities in science, 2) improving biology education and the educational skills of the PI, 3) increasing public scientific literacy, and 4) informing our understanding of the biological consequences of global climate change, a critical societal need.

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