Development and field evaluation of an online monitor for near-continuous measurement of iron, manganese, and chromium in coarse airborne particulate matter (PM)

A novel air sampling monitor was developed for near-continuous (i.e., 2-h time resolution) measurement of iron (Fe), manganese (Mn), and chromium (Cr) concentrations in ambient coarse particulate matter (PM) (i.e., PM10–2.5). The developed monitor consists of two modules: (1) the coarse PM collection module, utilizing two virtual impactors (VIs) connected to a modified BioSampler to collect ambient coarse PM into aqueous slurry samples; (2) the metal concentration measurement module, which quantifies the light absorption of colored complexes formed through the reactions between the soluble and solubilized target metals and pertinent analytical reagents in the collected slurries using a micro volume flow cell (MVFC) coupled with UV/VIS spectrophotometry. The developed monitor was deployed in the field for continuous ambient PM collection and measurements from January to April 2016 to evaluate its performance and reliability. Overall, the developed monitor could achieve accurate and reliable measurements of the trace metals Fe, Mn, and Cr over long sampling periods, based on the agreement between the metal concentrations measured via this online monitor and off-line parallel measurements obtained using filter samplers. Based on our results, it can be concluded that the developed monitor is a promising technology for near-continuous measurements of metal concentrations in ambient coarse PM. Moreover, this monitor can be readily configured to measure the speciation (i.e., water-soluble portion as well as specific oxidation states) of these metal species. These unique abilities are essential tools in investigations of sources and atmospheric processes influencing the concentrations of these redox-active metals in coarse PM. Copyright © 2016 American Association for Aerosol Research © 2016 American Association for Aerosol Research

Neither dust nor black carbon causing apparent albedo decline in Greenland\u27s dry snow zone: Implications for MODIS C5 surface reflectance

Remote sensing observations suggest Greenland ice sheet (GrIS) albedo has declined since 2001, even in the dry snow zone. We seek to explain the apparent dry snow albedo decline. We analyze samples representing 2012–2014 snowfall across NW Greenland for black carbon and dust light-absorbing impurities (LAI) and model their impacts on snow albedo. Albedo reductions due to LAI are small, averaging 0.003, with episodic enhancements resulting in reductions of 0.01–0.02. No significant increase in black carbon or dust concentrations relative to recent decades is found. Enhanced deposition of LAI is not, therefore, causing significant dry snow albedo reduction or driving melt events. Analysis of Collection 5 Moderate Resolution Imaging Spectroradiometer (MODIS) surface reflectance data indicates that the decline and spectral shift in dry snow albedo contains important contributions from uncorrected Terra sensor degradation. Though discrepancies are mostly below the stated accuracy of MODIS products, they will require revisiting some prior conclusions with C6 data

Lipooligosaccharide Structure is an Important Determinant in the Resistance of Neisseria Gonorrhoeae to Antimicrobial Agents of Innate Host Defense

The strict human pathogen Neisseria gonorrhoeae has caused the sexually transmitted infection termed gonorrhea for thousands of years. Over the millennia, the gonococcus has likely evolved mechanisms to evade host defense systems that operate on the genital mucosal surfaces in both males and females. Past research has shown that the presence or modification of certain cell envelope structures can significantly impact levels of gonococcal susceptibility to host-derived antimicrobial compounds that bathe genital mucosal surfaces and participate in innate host defense against invading pathogens. In order to facilitate the identification of gonococcal genes that are important in determining levels of bacterial susceptibility to mediators of innate host defense, we used the Himar I mariner in vitro mutagenesis system to construct a transposon insertion library in strain F62. As proof of principle that this strategy would be suitable for this purpose, we screened the library for mutants expressing decreased susceptibility to the bacteriolytic action of normal human serum (NHS). We found that a transposon insertion in the lgtD gene, which encodes an N-acetylgalactosamine transferase involved in the extension of the α-chain of lipooligosaccharide (LOS), could confer decreased susceptibility of strain F62 to complement-mediated killing by NHS. By complementation and chemical analyses, we demonstrated both linkage of the transposon insertion to the NHS-resistance phenotype and chemical changes in LOS structure that resulted from loss of LgtD production. Further truncation of the LOS α-chain or loss of phosphoethanolamine (PEA) from the lipid A region of LOS also impacted levels of NHS-resistance. PEA decoration of lipid A also increased gonococcal resistance to the model cationic antimicrobial polymyxin B. Taken together, we conclude that the Himar I mariner in vitro mutagenesis procedure can facilitate studies on structures involved in gonococcal pathogenesis

Alkaline proteases from the gut fluids of detritus-feeding larvae of the crane fly, Tipula abdominalis (say) (diptera, tipulidae)

The high level of proteolytic activity present in the midgut fluids of the detritus-feeding larvae of the crane fly, Tipula abdominalis, is due to a mixture of enzymes, consisting largely of serine proteases with trypsin- or chymotrypsin-like substrate specificities. These enzymes have high alkaline pH optima (pH > 11) and high stability at pH values of 8.5-11.5 at 15[deg]C, properties that enable them to function effectively in the highly alkaline gut fluids (pH 9.5-11.5) of an insect that feeds and grows in cold water (0-25[deg]C). The enzymes also have very low isoelectric points (pH in vivo. Possibly their anionic character prevents their inactivation through adsorption on ingested lignin, humic acid or clay. These serine enzymes arise from the midgut epithelial cells, and not from microbes residing in the gut or from ingested detrital food. The digestive system of T. abdominalis larvae is adapted for the efficient utilization of the limited quantities of dietary protein present in detrital food.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/24947/1/0000374.pd

The EDAM Project: Mining Atmospheric Aerosol Datasets

Data mining has been a very active area of research in the database, machine learning, and mathematical programming communities in recent years. EDAM (Exploratory Data Analysis and Management) is a joint project between researchers in Atmospheric Chemistry and Computer Science at Carleton College and the University of Wisconsin-Madison that aims to develop data mining techniques for advancing the state of the art in analyzing atmospheric aerosol datasets. There is a great need to better understand the sources, dynamics, and compositions of atmospheric aerosols. The traditional approach for particle measurement, which is the collection of bulk samples of particulates on filters, is not adequate for studying particle dynamics and real-time correlations. This has led to the development of a new generation of real-time instruments that provide continuous or semi-continuous streams of data about certain aerosol properties. However, these instruments have added a significant level of complexity to atmospheric aerosol data, and dramatically increased the amounts of data to be collected, managed, and analyzed. Our abilit y to integrate the data from all of these new and complex instruments now lags far behind our data-collection capabilities, and severely limits our ability to understand the data and act upon it in a timely manner. In this paper, we present an overview of the EDAM project. The goal of the project, which is in its early stages, is to develop novel data mining algorithms and approaches to managing and monitoring multiple complex data streams. An important objective is data quality assurance, and real-time data mining offers great potential. The approach that we take should also provide good techniques to deal with gas-phase and semi-volatile data. While atmospheric aerosol analysis is an important and challenging domain that motivates us with real problems and serves as a concrete test of our results, our objective is to develop techniques that have broader applicability, and to explore some fundamental challenges in data mining that are not specific to any given application domain

Inferential models: A framework for prior-free posterior probabilistic inference

Posterior probabilistic statistical inference without priors is an important but so far elusive goal. Fisher's fiducial inference, Dempster-Shafer theory of belief functions, and Bayesian inference with default priors are attempts to achieve this goal but, to date, none has given a completely satisfactory picture. This paper presents a new framework for probabilistic inference, based on inferential models (IMs), which not only provides data-dependent probabilistic measures of uncertainty about the unknown parameter, but does so with an automatic long-run frequency calibration property. The key to this new approach is the identification of an unobservable auxiliary variable associated with observable data and unknown parameter, and the prediction of this auxiliary variable with a random set before conditioning on data. Here we present a three-step IM construction, and prove a frequency-calibration property of the IM's belief function under mild conditions. A corresponding optimality theory is developed, which helps to resolve the non-uniqueness issue. Several examples are presented to illustrate this new approach.Comment: 29 pages with 3 figures. Main text is the same as the published version. Appendix B is an addition, not in the published version, that contains some corrections and extensions of two of the main theorem

Leading strategies in competitive on-line prediction

We start from a simple asymptotic result for the problem of on-line regression with the quadratic loss function: the class of continuous limited-memory prediction strategies admits a "leading prediction strategy", which not only asymptotically performs at least as well as any continuous limited-memory strategy but also satisfies the property that the excess loss of any continuous limited-memory strategy is determined by how closely it imitates the leading strategy. More specifically, for any class of prediction strategies constituting a reproducing kernel Hilbert space we construct a leading strategy, in the sense that the loss of any prediction strategy whose norm is not too large is determined by how closely it imitates the leading strategy. This result is extended to the loss functions given by Bregman divergences and by strictly proper scoring rules.Comment: 20 pages; a conference version is to appear in the ALT'2006 proceeding

Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients.

In December 2017, the National Academy of Neuropsychology convened an interorganizational Summit on Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients in Denver, Colorado. The Summit brought together representatives of a broad range of stakeholders invested in the care of older adults to focus on the topic of cognitive health and aging. Summit participants specifically examined questions of who should be screened for cognitive impairment and how they should be screened in medical settings. This is important in the context of an acute illness given that the presence of cognitive impairment can have significant implications for care and for the management of concomitant diseases as well as pose a major risk factor for dementia. Participants arrived at general principles to guide future screening approaches in medical populations and identified knowledge gaps to direct future research. Key learning points of the summit included: recognizing the importance of educating patients and healthcare providers about the value of assessing current and baseline cognition;emphasizing that any screening tool must be appropriately normalized and validated in the population in which it is used to obtain accurate information, including considerations of language, cultural factors, and education; andrecognizing the great potential, with appropriate caveats, of electronic health records to augment cognitive screening and tracking of changes in cognitive health over time