Investigating the observed sensitivities of air-quality extremes to meteorological drivers via quantile regression

Air pollution variability is strongly dependent on meteorology. However, quantifying the impacts of changes in regional climatology on pollution extremes can be difficult due to the many non-linear and competing meteorological influences on the production, transport, and removal of pollutant species. Furthermore, observed pollutant levels at many sites show sensitivities at the extremes that differ from those of the overall mean, indicating relationships that would be poorly characterized by simple linear regressions. To address this challenge, we apply quantile regression to observed daily ozone (O[subscript 3]) and fine particulate matter (PM[subscript 2.5]) levels and reanalysis meteorological fields in the USA over the past decade to specifically identify the meteorological sensitivities of higher pollutant levels. From an initial set of over 1700 possible meteorological indicators (including 28 meteorological variables with 63 different temporal options), we generate reduced sets of O[subscript 3] and PM[subscript 2.5] indicators for both summer and winter months, analyzing pollutant sensitivities to each for response quantiles ranging from 2 to 98 %. Primary covariates connected to high-quantile O[subscript 3] levels include temperature and relative humidity in the summer, while winter O[subscript 3] levels are most commonly associated with incoming radiation flux. Covariates associated with summer PM[subscript 2.5] include temperature, wind speed, and tropospheric stability at many locations, while stability, humidity, and planetary boundary layer height are the key covariates most frequently associated with winter PM[subscript 2.5]. We find key differences in covariate sensitivities across regions and quantiles. For example, we find nationally averaged sensitivities of 95th percentile summer O[subscript 3] to changes in maximum daily temperature of approximately 0.9 ppb °C[superscript −1], while the sensitivity of 50th percentile summer O[subscript 3] (the annual median) is only 0.6 ppb °C[superscript −1]. This gap points to differing sensitivities within various percentiles of the pollutant distribution, highlighting the need for statistical tools capable of identifying meteorological impacts across the entire response spectrum.United States. Environmental Protection Agency (Grant/Cooperative Agreement RD-83522801

Cytoplasmic Dynein Heavy Chain 1b Is Required for Flagellar Assembly in Chlamydomonas

A second cytoplasmic dynein heavy chain (cDhc) has recently been identified in several organisms, and its expression pattern is consistent with a possible role in axoneme assembly. We have used a genetic approach to ask whether cDhc1b is involved in flagellar assembly in Chlamydomonas. Using a modified PCR protocol, we recovered two cDhc sequences distinct from the axonemal Dhc sequences identified previously. cDhc1a is closely related to the major cytoplasmic Dhc, whereas cDhc1b is closely related to the minor cDhc isoform identified in sea urchins, Caenorhabditis elegans, and Tetrahymena. TheChlamydomonas cDhc1b transcript is a low-abundance mRNA whose expression is enhanced by deflagellation. To determine its role in flagellar assembly, we screened a collection of stumpy flagellar (stf) mutants generated by insertional mutagenesis and identified two strains in which portions of the cDhc1bgene have been deleted. The two mutants assemble short flagellar stumps (<1–2 μm) filled with aberrant microtubules, raft-like particles, and other amorphous material. The results indicate that cDhc1b is involved in the transport of components required for flagellar assembly in Chlamydomonas

PEER Testbed Study on a Laboratory Building: Exercising Seismic Performance Assessment

From 2002 to 2004 (years five and six of a ten-year funding cycle), the PEER Center organized the majority of its research around six testbeds. Two buildings and two bridges, a campus, and a transportation network were selected as case studies to “exercise” the PEER performance-based earthquake engineering methodology. All projects involved interdisciplinary teams of researchers, each producing data to be used by other colleagues in their research. The testbeds demonstrated that it is possible to create the data necessary to populate the PEER performancebased framing equation, linking the hazard analysis, the structural analysis, the development of damage measures, loss analysis, and decision variables. This report describes one of the building testbeds—the UC Science Building. The project was chosen to focus attention on the consequences of losses of laboratory contents, particularly downtime. The UC Science testbed evaluated the earthquake hazard and the structural performance of a well-designed recently built reinforced concrete laboratory building using the OpenSees platform. Researchers conducted shake table tests on samples of critical laboratory contents in order to develop fragility curves used to analyze the probability of losses based on equipment failure. The UC Science testbed undertook an extreme case in performance assessment—linking performance of contents to operational failure. The research shows the interdependence of building structure, systems, and contents in performance assessment, and highlights where further research is needed. The Executive Summary provides a short description of the overall testbed research program, while the main body of the report includes summary chapters from individual researchers. More extensive research reports are cited in the reference section of each chapter

Genetic Connectivity and Diversity of a Protected, Habitat-Forming Species:Evidence Demonstrating the Need for Wider Environmental Protection and Integration of the Marine Protected Area Network

Funding Information: This work was largely funded by Heriot-Watt University (James Watt Scholarship) and NatureScot (formerly Scottish Natural Heritage). Additional funding was received from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS was funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions.Peer reviewedPublisher PD

A basic optimization problem in linear systems

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/48017/1/224_2005_Article_BF01691464.pd

The reflective learning continuum: reflecting on reflection

The importance of reflection to marketing educators is increasingly recognized. However, there is a lack of empirical research which considers reflection within the context of both the marketing and general business education literature. This paper describes the use of an instrument which can be used to measure four identified levels of a reflection hierarchy: habitual action, understanding, reflection and intensive reflection and two conditions for reflection: instructor to student interaction and student to student interaction. Further we demonstrate the importance of reflective learning in predicting graduates’ perception of program quality. Although the focus was on assessment of MBA level curricula, the findings have great importance to marketing education and educators