scholarly journals Quantitative sampling and analysis of trace elements in atmospheric aerosols: impactor characterization and Synchrotron-XRF mass calibration

2010 ◽  
Vol 3 (5) ◽  
pp. 1473-1485 ◽  
Author(s):  
A. Richard ◽  
N. Bukowiecki ◽  
P. Lienemann ◽  
M. Furger ◽  
M. Fierz ◽  
...  
Keyword(s):  
Trace Elements ◽  
Atmospheric Aerosols ◽  
Collection Efficiency ◽  
Ambient Air ◽  
Pollution Source ◽  
Data Sets ◽  
Size Segregation ◽  
Ambient Aerosols ◽  
Experimental Conditions ◽  
Time Resolved

Abstract. Identification of trace elements in ambient air can add substantial information to pollution source apportionment studies, although they do not contribute significantly to emissions in terms of mass. A method for quantitative size and time-resolved trace element evaluation in ambient aerosols with a rotating drum impactor and synchrotron radiation based X-ray fluorescence is presented. The impactor collection efficiency curves and size segregation characteristics were investigated in an experiment with oil and salt particles. Cutoff diameters were determined through the ratio of size distributions measured with two particle sizers. Furthermore, an external calibration technique to empirically link fluorescence intensities to ambient concentrations was developed. Solutions of elemental standards were applied with an ink-jet printer on thin films and area concentrations were subsequently evaluated with external wet chemical methods. These customized and reusable reference standards enable quantification of different data sets analyzed under varying experimental conditions.

scholarly journals Quantitative sampling and analysis of trace elements in ambient air: impactor characterization and Synchrotron-XRF mass calibration

2010 ◽  
Vol 3 (3) ◽  
pp. 2477-2513
Author(s):  
A. Richard ◽  
N. Bukowiecki ◽  
P. Lienemann ◽  
M. Furger ◽  
B. Weideli ◽  
...  
Keyword(s):  
Trace Elements ◽  
Collection Efficiency ◽  
Ambient Air ◽  
Pollution Source ◽  
Data Sets ◽  
Size Segregation ◽  
Ambient Aerosols ◽  
Experimental Conditions ◽  
Time Resolved ◽  
Ambient Concentrations

Abstract. Identification of trace elements in ambient air can add substantial information to pollution source apportionment studies, although they do not contribute significantly to emissions in terms of mass. A method for quantitative size and time-resolved trace element evaluation in ambient aerosols with a rotating drum impactor and synchrotron radiation based X-ray fluorescence is presented. The impactor collection efficiency curves and size segregation characteristics were investigated in an experiment with oil and salt particles. Cutoff diameters were determined through the ratio of size distributions measured with two particles sizers. Furthermore, an external calibration technique to empirically link fluorescence intensities to ambient concentrations was developed. Solutions of elemental standards were applied with an ink-jet printer on thin films and area concentrations were subsequently evaluated with external wet chemical methods. These customized and reusable reference standards enable quantification of different data sets analyzed under varying experimental conditions.

scholarly journals Elemental Composition of Particulate Matter in South-Asian Megacity (Faisalabad-Pakistan): Seasonal Behaviors, Source Apportionment and Health Risk Assessment

2020 ◽  
Vol 71 (2) ◽  
pp. 288-301 ◽  
Author(s):  
Muhammad Usman Alvi ◽  
Tariq Mahmud ◽  
Magdalena Kistler ◽  
Anne Kasper-Giebl ◽  
Imran Shahid ◽  
...  
Keyword(s):  
Trace Elements ◽  
Health Risk ◽  
Atmospheric Aerosols ◽  
Inductively Coupled Plasma ◽  
Principal Component ◽  
Ambient Air ◽  
Enrichment Factors ◽  
Average Concentration ◽  
Emission Spectrometry ◽  
Us Epa

The composition of atmospheric aerosols can help to identify pollution sources, particulate transportation and possible impacts on human health. In this study, seasonal variations and sources of elemental contents in PM10 from Faisalabad area were investigated. In total 117 samples were collected on 24 hours basis from September 2015 to December 2016. The selected trace elements, viz., Al, Ba, Ca, Fe, K, Mg, Mn, Na, P, Pb, S and Zn were measured by inductively coupled plasma optical emission spectrometry (ICP-OES). The average PM10 concentration was found to be 744 � 392 μg m-3, exceeding the limits proposed by Pak-EPA (150 μg m-3), US-EPA (150 μg m-3) and WHO (50 μg m-3). On average concentration basis, the elements were in the order of Ca ] Al ] S ] Fe ] K ] Mg ] Zn ] Na ] Pb ] P ] Mn ] Ba. The elements apparently emitted from natural sources were dominant in spring and summer seasons, while those emitted from anthropogenic inputs were more prominent in winter and autumn seasons. A correlation analysis revealed that pairs of elements originated from common sources were suspended in the ambient air. The enrichment factors (EFs), principal component analysis (PCA) and cluster analysis (CA) indicated wind-blown dust, biomass burning, fossil fuel combustion and vehicular exhaust/non-exhaust emissions as major sources. A health risk caused by non-carcinogenic trace elements such as Pb, Zn and Mn was also assessed according to the method specified by US-EPA.

Evaluation of Acoustic Analyses of Voice in Nonoptimized Conditions

2020 ◽  
Vol 63 (12) ◽  
pp. 3991-3999
Author(s):  
Benjamin van der Woerd ◽  
Min Wu ◽  
Vijay Parsa ◽  
Philip C. Doyle ◽  
Kevin Fung
Keyword(s):  
Repeated Measures ◽  
Voice Quality ◽  
Data Sets ◽  
Acoustic Measurements ◽  
Sample Collection ◽  
Experimental Conditions ◽  
Environment Analysis ◽  
Acoustic Measures ◽  
Recording Conditions ◽  
Cepstral Peak Prominence

Objectives This study aimed to evaluate the fidelity and accuracy of a smartphone microphone and recording environment on acoustic measurements of voice. Method A prospective cohort proof-of-concept study. Two sets of prerecorded samples (a) sustained vowels (/a/) and (b) Rainbow Passage sentence were played for recording via the internal iPhone microphone and the Blue Yeti USB microphone in two recording environments: a sound-treated booth and quiet office setting. Recordings were presented using a calibrated mannequin speaker with a fixed signal intensity (69 dBA), at a fixed distance (15 in.). Each set of recordings (iPhone—audio booth, Blue Yeti—audio booth, iPhone—office, and Blue Yeti—office), was time-windowed to ensure the same signal was evaluated for each condition. Acoustic measures of voice including fundamental frequency ( f o ), jitter, shimmer, harmonic-to-noise ratio (HNR), and cepstral peak prominence (CPP), were generated using a widely used analysis program (Praat Version 6.0.50). The data gathered were compared using a repeated measures analysis of variance. Two separate data sets were used. The set of vowel samples included both pathologic ( n = 10) and normal ( n = 10), male ( n = 5) and female ( n = 15) speakers. The set of sentence stimuli ranged in perceived voice quality from normal to severely disordered with an equal number of male ( n = 12) and female ( n = 12) speakers evaluated. Results The vowel analyses indicated that the jitter, shimmer, HNR, and CPP were significantly different based on microphone choice and shimmer, HNR, and CPP were significantly different based on the recording environment. Analysis of sentences revealed a statistically significant impact of recording environment and microphone type on HNR and CPP. While statistically significant, the differences across the experimental conditions for a subset of the acoustic measures (viz., jitter and CPP) have shown differences that fell within their respective normative ranges. Conclusions Both microphone and recording setting resulted in significant differences across several acoustic measurements. However, a subset of the acoustic measures that were statistically significant across the recording conditions showed small overall differences that are unlikely to have clinical significance in interpretation. For these acoustic measures, the present data suggest that, although a sound-treated setting is ideal for voice sample collection, a smartphone microphone can capture acceptable recordings for acoustic signal analysis.

scholarly journals Spatial and temporal tools for building a human cell atlas

2019 ◽  
Vol 30 (19) ◽  
pp. 2435-2438 ◽  
Author(s):  
Jonah Cool ◽  
Richard S. Conroy ◽  
Sean E. Hanlon ◽  
Shannon K. Hughes ◽  
Ananda L. Roy
Keyword(s):  
Scientific Community ◽  
Large Data ◽  
Large Data Sets ◽  
Data Sets ◽  
Experimental Conditions ◽  
Modeling Tools ◽  
Holistic View ◽  
Multiple Timescales ◽  
Single Cell Sequencing ◽  
Coordination And Collaboration

Improvements in the sensitivity, content, and throughput of microscopy, in the depth and throughput of single-cell sequencing approaches, and in computational and modeling tools for data integration have created a portfolio of methods for building spatiotemporal cell atlases. Challenges in this fast-moving field include optimizing experimental conditions to allow a holistic view of tissues, extending molecular analysis across multiple timescales, and developing new tools for 1) managing large data sets, 2) extracting patterns and correlation from these data, and 3) integrating and visualizing data and derived results in an informative way. The utility of these tools and atlases for the broader scientific community will be accelerated through a commitment to findable, accessible, interoperable, and reusable data and tool sharing principles that can be facilitated through coordination and collaboration between programs working in this space.

scholarly journals Six-year source apportionment of submicron organic aerosols from near-continuous measurements at SIRTA (Paris area, France)

2019 ◽  
Author(s):  
Yunjiang Zhang ◽  
Olivier Favez ◽  
Jean-Eudes Petit ◽  
Francesco Canonaco ◽  
Francois Truong ◽  
...  
Keyword(s):  
Source Apportionment ◽  
Biomass Burning ◽  
Ambient Air ◽  
Carbonaceous Aerosols ◽  
Time Resolved ◽  
Pronounced Increase ◽  
Paris Area ◽  
Multi Wavelength ◽  
High Concentrations

Abstract. Organic aerosol (OA) particles are recognized as key factors influencing air quality and climate change. However, highly-time resolved year-round characterizations of their composition and sources in ambient air are still very limited due to challenging continuous observations. Here, we present an analysis of long-term variability of submicron OA using the combination of Aerosol Chemical Speciation Monitor (ACSM) and multi-wavelength aethalometer from November 2011 to March 2018 at a background site of the Paris region (France). Source apportionment of OA was achieved via partially constrained positive matrix factorization (PMF) using the multilinear engine (ME-2). Two primary OA (POA) and two oxygenated OA (OOA) factors were identified and quantified over the entire studied period. POA factors were designated as hydrocarbon-like OA (HOA) and biomass burning OA (BBOA). The latter factor presented a significant seasonality with higher concentrations in winter with significant monthly contributions to OA (18–33 %) due to enhanced residential wood burning emissions. HOA mainly originated from traffic emissions but was also influenced by biomass burning in cold periods. OOA factors were distinguished between their less- and more-oxidized fractions (LO-OOA and MO-OOA, respectively). These factors presented distinct seasonal patterns, associated with different atmospheric formation pathways. A pronounced increase of LO-OOA concentrations and contributions (50–66 %) was observed in summer, which may be mainly explained by secondary OA (SOA) formation processes involving biogenic gaseous precursors. Conversely high concentrations and OA contributions (32–62 %) of MO-OOA during winter and spring seasons were partly associated with anthropogenic emissions and/or long-range transport from northeastern Europe. The contribution of the different OA factors as a function of OA mass loading highlighted the dominant roles of POA during pollution episodes in fall and winter, and of SOA for highest springtime and summertime OA concentrations. Finally, long-term trend analyses indicated a decreasing feature (of about 200 ng m−3 yr−1) for MO-OOA, very limited or insignificant decreasing trends for primary anthropogenic carbonaceous aerosols (BBOA and HOA, along with the fossil fuel and biomass burning black carbon components), and no trend for LO-OOA over the 6+-year investigated period.

Dynamics of a metabolic system: what single-action agents reveal about acid secretion

1992 ◽  
Vol 262 (3) ◽  
pp. G581-G592 ◽  
Author(s):  
V. Licko ◽  
E. B. Ekblad
Keyword(s):  
Acid Secretion ◽  
Independent Set ◽  
Nonlinear Least Squares ◽  
Data Sets ◽  
Estimation Of Parameters ◽  
Experimental Conditions ◽  
Metabolic System ◽  
Single Action ◽  
Adequate Representation ◽  
Dynamic Time

A simple single-state nonlinear mathematical model of an open metabolic system is shown to be an adequate representation of acid secretion in frog gastric mucosa. The parameters of the elemental model were estimated from data, and subsystems of augmented models were established for histamine, a nonconservative stimulus acting via binding to receptors, and for two inhibitors of acid secretion. The latter included metiamide, a nonconservative histamine antagonist, which affects the formation of acid by competitive binding to the histamine receptors, and nitrite, a conservative inhibitor, which affects the rate of acid translocation. For parameter estimation, two data sets were analyzed by a nonlinear least-squares procedure: a dynamic (time dependent) set consisting of individual acid secretion rate curves and an integral (time independent) set consisting of the curves of acid secreted and suppressed above or below baseline, respectively, as functions of agent exposure. Because the model is instrumental in the estimation of parameters of subsystems that are not accessible through direct observation, it can serve as a research tool in the investigation of the mechanism of gastric acid secretion under a variety of experimental conditions.

scholarly journals Compartment and hub definitions tune metabolic networks for metabolomic interpretations

GigaScience ◽  
2020 ◽  
Vol 9 (1) ◽  
Author(s):  
T Cameron Waller ◽  
Jordan A Berg ◽  
Alexander Lex ◽  
Brian E Chapman ◽  
Jared Rutter
Keyword(s):  
Large Scale ◽  
Metabolic Networks ◽  
Shortest Paths ◽  
Large Data ◽  
Differential Regulation ◽  
Large Data Sets ◽  
Data Sets ◽  
Human Metabolism ◽  
Experimental Conditions ◽  
Systemic Model

Abstract Background Metabolic networks represent all chemical reactions that occur between molecular metabolites in an organism’s cells. They offer biological context in which to integrate, analyze, and interpret omic measurements, but their large scale and extensive connectivity present unique challenges. While it is practical to simplify these networks by placing constraints on compartments and hubs, it is unclear how these simplifications alter the structure of metabolic networks and the interpretation of metabolomic experiments. Results We curated and adapted the latest systemic model of human metabolism and developed customizable tools to define metabolic networks with and without compartmentalization in subcellular organelles and with or without inclusion of prolific metabolite hubs. Compartmentalization made networks larger, less dense, and more modular, whereas hubs made networks larger, more dense, and less modular. When present, these hubs also dominated shortest paths in the network, yet their exclusion exposed the subtler prominence of other metabolites that are typically more relevant to metabolomic experiments. We applied the non-compartmental network without metabolite hubs in a retrospective, exploratory analysis of metabolomic measurements from 5 studies on human tissues. Network clusters identified individual reactions that might experience differential regulation between experimental conditions, several of which were not apparent in the original publications. Conclusions Exclusion of specific metabolite hubs exposes modularity in both compartmental and non-compartmental metabolic networks, improving detection of relevant clusters in omic measurements. Better computational detection of metabolic network clusters in large data sets has potential to identify differential regulation of individual genes, transcripts, and proteins.

scholarly journals Selective time-dependent changes of Cu(DPPE)(DMP)·PF6on photoexcitation

2014 ◽  
Vol 70 (a1) ◽  
pp. C776-C776 ◽  
Author(s):  
Elzbieta Trzop ◽  
Bertrand Fournier ◽  
Katarzyna Jarzembska ◽  
Jesse Sokolow ◽  
Radoslaw Kaminski ◽  
...  
Keyword(s):  
Structural Changes ◽  
Dye Sensitized Solar Cells ◽  
Department Of Energy ◽  
Data Sets ◽  
Monoclinic System ◽  
Time Resolved ◽  
Pump Probe ◽  
Light Emitting Devices ◽  
Potential Applications ◽  
Photon Source

Thanks to their potential applications as light-emitting devices, chemical sensors and dye-sensitized solar cells, heteroleptic copper (I) complexes have been extensively studied. Cu(DPPE)(DMP)·PF6(dppe= 1,2-bis(diphenylphosphino)ethane; dmp = 2,9-dimethyl-1,10-phenanthroline) crystallizes in the monoclinic system, P21/c, with two independent molecules in the asymmetric unit. Previous studies on this system [1,2] show strong temperature-dependent emission. The complex was studied at 90K under 355nm laser excitation. At this temperature, the luminescence decay for Cu(DPPE)(DMP)·PF6is biexponential with lifetimes of ~3μs and ~28μs. Two time-resolved X-ray diffraction techniques were applied for studies: (1) a Laue technique at BioCARS ID-14 beamline at the Advanced Photon Source, and (2) monochromatic diffraction at a newly constructed in-house pump-probe monochromatic facility at the University at Buffalo. Structural changes determined with the two methods are in qualitative agreement; discrepancies in position of the Cu and P atoms were observed. The molecular distortions were smaller than those determined at 16K in the earlier synchrotron study by Vorontsov et al. [2]. Photodeformation maps (see Figure below), in which the increase in temperature on photoexcitation has been eliminated, clearly illustrate the photoinduced atomic shifts for both data sets. Results will be compared with those obtained for other studied heteroleptic copper (I) complexes, for instance Cu[(1,10-phenanthroline-N,N′) bis(triphenylphosphine)]·BF4[3]. The in-house pump-probe facility is discussed by Radoslaw Kaminski at this meeting. Research funded by the National Science Foundation (CHE1213223). BioCARS Sector 14 at APS is supported by NIH (RR007707). The Advanced Photon Source is funded by the Office of Basic Energy Sciences, U.S. Department of Energy, (W-31-109-ENG-38). KNJ is supported by the Polish Ministry of Science and Higher Education through the "Mobility Plus" program.

GENE SELECTION USING LOGISTIC REGRESSIONS BASED ON AIC, BIC AND MDL CRITERIA

2005 ◽  
Vol 01 (01) ◽  
pp. 129-145 ◽  
Author(s):  
XIAOBO ZHOU ◽  
XIAODONG WANG ◽  
EDWARD R. DOUGHERTY
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Gene Selection ◽  
Information Criterion ◽  
Cancer Classification ◽  
Data Sets ◽  
Classification Methods ◽  
Gene Expressions ◽  
Experimental Conditions

In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables (gene expressions) and the small number of experimental conditions. Many gene-selection and classification methods have been proposed; however most of these treat gene selection and classification separately, and not under the same model. We propose a Bayesian approach to gene selection using the logistic regression model. The Akaike information criterion (AIC), the Bayesian information criterion (BIC) and the minimum description length (MDL) principle are used in constructing the posterior distribution of the chosen genes. The same logistic regression model is then used for cancer classification. Fast implementation issues for these methods are discussed. The proposed methods are tested on several data sets including those arising from hereditary breast cancer, small round blue-cell tumors, lymphoma, and acute leukemia. The experimental results indicate that the proposed methods show high classification accuracies on these data sets. Some robustness and sensitivity properties of the proposed methods are also discussed. Finally, mixing logistic-regression based gene selection with other classification methods and mixing logistic-regression-based classification with other gene-selection methods are considered.

scholarly journals A new approach for retrieving the UV–vis optical properties of ambient aerosols

2016 ◽  
Vol 9 (8) ◽  
pp. 3477-3490 ◽  
Author(s):  
Nir Bluvshtein ◽  
J. Michel Flores ◽  
Lior Segev ◽  
Yinon Rudich
Keyword(s):  
Optical Properties ◽  
Atmospheric Aerosols ◽  
Radiative Forcing ◽  
Complex Refractive Index ◽  
Single Scattering ◽  
Aerosol Size Distribution ◽  
Distribution Data ◽  
Ambient Aerosols ◽  
New Approach ◽  
Effective Radiative Forcing

Abstract. Atmospheric aerosols play an important part in the Earth's energy budget by scattering and absorbing incoming solar and outgoing terrestrial radiation. To quantify the effective radiative forcing due to aerosol–radiation interactions, researchers must obtain a detailed understanding of the spectrally dependent intensive and extensive optical properties of different aerosol types. Our new approach retrieves the optical coefficients and the single-scattering albedo of the total aerosol population over 300 to 650 nm wavelength, using extinction measurements from a broadband cavity-enhanced spectrometer at 315 to 345 nm and 390 to 420 nm, extinction and absorption measurements at 404 nm from a photoacoustic cell coupled to a cavity ring-down spectrometer, and scattering measurements from a three-wavelength integrating nephelometer. By combining these measurements with aerosol size distribution data, we retrieved the time- and wavelength-dependent effective complex refractive index of the aerosols. Retrieval simulations and laboratory measurements of brown carbon proxies showed low absolute errors and good agreement with expected and reported values. Finally, we implemented this new broadband method to achieve continuous spectral- and time-dependent monitoring of ambient aerosol population, including, for the first time, extinction measurements using cavity-enhanced spectrometry in the 315 to 345 nm UV range, in which significant light absorption may occur.

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