PMF and PSCF based source apportionment of PM2.5 at a regional background site in North China

NASA Astrophysics Data System (ADS)

Zong, Zheng; Wang, Xiaoping; Tian, Chongguo; Chen, Yingjun; Fu, Shanfei; Qu, Lin; Ji, Ling; Li, Jun; Zhang, Gan

2018-05-01

To apportion regional PM2.5 (atmospheric particles with aerodynamic diameter < 2.5 μm) source types and their geographic pattern in North China, 120 daily PM2.5 samples on Beihuangcheng Island (BH, a regional background site in North China) were collected from August 20th, 2014 to September 15th, 2015 showing one-year period. After the chemical analyses on carbonaceous species, water-soluble ions and inorganic elements, various approaches, such as Mann-Kendall test, chemical mass closure, ISORROPIA II model, Positive Matrix Factorization (PMF) linked with Potential Source Contribution Function (PSCF), were used to explore the PM2.5 speciation, sources, and source regions. Consequently, distinct seasonal variations of PM2.5 and its main species were found and could be explained by varying emission source characteristics. Based on PMF model, seven source factors for PM2.5 were identified, which were coal combustion + biomass burning, vehicle emission, mineral dust, ship emission, sea salt, industry source, refined chrome industry with the contribution of 48.21%, 30.33%, 7.24%, 6.63%, 3.51%, 3.2%, and 0.88%, respectively. In addition, PSCF analysis using the daily contribution of each factor from PMF result suggested that Shandong peninsula and Hebei province were identified as the high potential region for coal combustion + biomass burning; Beijing-Tianjin-Hebei (BTH) region was the main source region for industry source; Bohai Sea and East China Sea were found to be of high source potential for ship emission; Geographical region located northwest of BH Island was possessed of high probability for sea salt; Mineral dust presumably came from the region of Mongolia; Refined chrome industry mostly came from Liaoning, Jilin province; The vehicle emission was primarily of BTH region origin, centring on metropolises, such as Beijing and Tianjin. These results provided precious implications for PM2.5 control strategies in North China.

Source Apportionment of PM2.5 in Delhi, India Using PMF Model.

PubMed

Sharma, S K; Mandal, T K; Jain, Srishti; Saraswati; Sharma, A; Saxena, Mohit

2016-08-01

Chemical characterization of PM2.5 [organic carbon, elemental carbon, water soluble inorganic ionic components, and major and trace elements] was carried out for a source apportionment study of PM2.5 at an urban site of Delhi, India from January, 2013, to December, 2014. The annual average mass concentration of PM2.5 was 122 ± 94.1 µg m(-3). Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon. A receptor model, positive matrix factorization (PMF) was applied for source apportionment of PM2.5 mass concentration. The PMF model resolved the major sources of PM2.5 as secondary aerosols (21.3 %), followed by soil dust (20.5 %), vehicle emissions (19.7 %), biomass burning (14.3 %), fossil fuel combustion (13.7 %), industrial emissions (6.2 %) and sea salt (4.3 %).

ASXL1/EZH2 mutations promote clonal expansion of neoplastic HSC and impair erythropoiesis in PMF.

PubMed

Triviai, Ioanna; Zeschke, Silke; Rentel, Jan; Spanakis, Marios; Scherer, Theo; Gabdoulline, Razif; Panagiota, Victoria; Thol, Felicitas; Heuser, Michael; Stocking, Carol; Kröger, Nicolaus

2018-06-15

Primary myelofibrosis (PMF) is a hematopoietic stem cell (HSC) disease, characterized by aberrant differentiation of all myeloid lineages and profound disruption of the bone marrow niche. PMF samples carry several mutations, but their cell origin and hierarchy in regulating the different waves of clonal and aberrant myeloproliferation from the prime HSC compartment is poorly understood. Genotyping of >2000 colonies from CD133+HSC and progenitors from PMF patients confirmed the complex genetic heterogeneity within the neoplastic population. Notably, mutations in chromatin regulators ASXL1 and/or EZH2 were identified as the first genetic lesions, preceding both JAK2-V617F and CALR mutations, and are thus drivers of clonal myelopoiesis in a PMF subset. HSC from PMF patients with double ASXL1/EZH2 mutations exhibited significantly higher engraftment in immunodeficient mice than those from patients without histone modifier mutations. EZH2 mutations correlate with aberrant erythropoiesis in PMF patients, exemplified by impaired maturation and cell cycle arrest of erythroid progenitors. These data underscore the importance of post-transcriptional modifiers of histones in neoplastic stem cells, whose clonal growth sustains aberrant myelopoiesis and expansion of pre-leukemic clones in PMF.

Water quality assessment and apportionment of pollution sources using APCS-MLR and PMF receptor modeling techniques in three major rivers of South Florida.

PubMed

Haji Gholizadeh, Mohammad; Melesse, Assefa M; Reddi, Lakshmi

2016-10-01

In this study, principal component analysis (PCA), factor analysis (FA), and the absolute principal component score-multiple linear regression (APCS-MLR) receptor modeling technique were used to assess the water quality and identify and quantify the potential pollution sources affecting the water quality of three major rivers of South Florida. For this purpose, 15years (2000-2014) dataset of 12 water quality variables covering 16 monitoring stations, and approximately 35,000 observations was used. The PCA/FA method identified five and four potential pollution sources in wet and dry seasons, respectively, and the effective mechanisms, rules and causes were explained. The APCS-MLR apportioned their contributions to each water quality variable. Results showed that the point source pollution discharges from anthropogenic factors due to the discharge of agriculture waste and domestic and industrial wastewater were the major sources of river water contamination. Also, the studied variables were categorized into three groups of nutrients (total kjeldahl nitrogen, total phosphorus, total phosphate, and ammonia-N), water murkiness conducive parameters (total suspended solids, turbidity, and chlorophyll-a), and salt ions (magnesium, chloride, and sodium), and average contributions of different potential pollution sources to these categories were considered separately. The data matrix was also subjected to PMF receptor model using the EPA PMF-5.0 program and the two-way model described was performed for the PMF analyses. Comparison of the obtained results of PMF and APCS-MLR models showed that there were some significant differences in estimated contribution for each potential pollution source, especially in the wet season. Eventually, it was concluded that the APCS-MLR receptor modeling approach appears to be more physically plausible for the current study. It is believed that the results of apportionment could be very useful to the local authorities for the control and

Source apportionment of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH) associated to airborne PM10 by a PMF model.

PubMed

Callén, M S; Iturmendi, A; López, J M; Mastral, A M

2014-02-01

In order to perform a study of the carcinogenic potential of polycyclic aromatic hydrocarbons (PAH), benzo(a)pyrene equivalent (BaP-eq) concentration was calculated and modelled by a receptor model based on positive matrix factorization (PMF). Nineteen PAH associated to airborne PM10 of Zaragoza, Spain, were quantified during the sampling period 2001-2009 and used as potential variables by the PMF model. Afterwards, multiple linear regression analysis was used to quantify the potential sources of BaP-eq. Five sources were obtained as the optimal solution and vehicular emission was identified as the main carcinogenic source (35 %) followed by heavy-duty vehicles (28 %), light-oil combustion (18 %), natural gas (10 %) and coal combustion (9 %). Two of the most prevailing directions contributing to this carcinogenic character were the NE and N directions associated with a highway, industrial parks and a paper factory. The lifetime lung cancer risk exceeded the unit risk of 8.7 x 10(-5) per ng/m(3) BaP in both winter and autumn seasons and the most contributing source was the vehicular emission factor becoming an important issue in control strategies.

Datasets for Ostrava PMF paper

EPA Pesticide Factsheets

These data support a published journal paper described as follows:A 14-week investigation during a warm and cold seasons was conducted to improve understanding of airpollution sources that might be impacting air quality in Ostrava, the Czech Republic. Fine particulatematter (PM2.5) samples were collected in consecutive 12-h day and night increments during spring andfall 2012 sampling campaigns. Sampling sites were strategically located to evaluate conditions in closeproximity of a large steel works industrial complex, as well as away from direct influence of theindustrial complex. These samples were analyzed for metals and other elements, organic and elemental(black) carbon, and polycyclic aromatic hydrocarbons (PAHs). The PM2.5 samples were supplementedwith pollutant gases and meteorological parameters. We applied the EPA PMF v5.1 model with uncertainty estimate features to the Ostrava data set. Using the model's bootstrapping procedure and other considerations, six factors were determined to provide the optimum solution. Each model run consisted of 100 iterations to ensure that the solution represents a global minimum. The resulting factors were identified as representing coal (power plants), mixed Cl, crustal, industrial 1 (alkali metals and PAHs), industrial 2 (transition metals), and home heat/transportation. The home heating source is thought to be largely domestic boilers burning low quality fuels such as lignite, wood, and domestic waste.Transportation-r

A GRAPHICAL DIAGNOSTIC METHOD FOR ASSESSING THE ROTATION IN FACTOR ANALYTICAL MODELS OF ATMOSPHERIC POLLUTION. (R831078)

EPA Science Inventory

Factor analytic tools such as principal component analysis (PCA) and positive matrix factorization (PMF), suffer from rotational ambiguity in the results: different solutions (factors) provide equally good fits to the measured data. The PMF model imposes non-negativity of both...

76 FR 21783 - Submission for Review: Presidential Management Fellows (PMF) Nomination Form, OPM 1300, 3206-0082

Federal Register 2010, 2011, 2012, 2013, 2014

2011-04-18

... Form 1300, Presidential Management Fellows (PMF) Nomination Form, is used by accredited colleges and... OFFICE OF PERSONNEL MANAGEMENT Submission for Review: Presidential Management Fellows (PMF) Nomination Form, OPM 1300, 3206-0082 AGENCY: U.S. Office of Personnel Management. ACTION: 60-Day notice and...

Source apportionment of heavy metals in agricultural soil based on PMF: A case study in Hexi Corridor, northwest China.

PubMed

Guan, Qingyu; Wang, Feifei; Xu, Chuanqi; Pan, Ninghui; Lin, Jinkuo; Zhao, Rui; Yang, Yanyan; Luo, Haiping

2018-02-01

Hexi Corridor is the most important base of commodity grain and producing area for cash crops. However, the rapid development of agriculture and industry has inevitably led to heavy metal contamination in the soils. Multivariate statistical analysis, GIS-based geostatistical methods and Positive Matrix Factorization (PMF) receptor modeling techniques were used to understand the levels of heavy metals and their source apportionment for agricultural soil in Hexi Corridor. The results showed that the average concentrations of Cr, Cu, Ni, Pb and Zn were lower than the secondary standard of soil environmental quality; however, the concentrations of eight metals (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn) were higher than background values, and their corresponding enrichment factor values were significantly greater than 1. Different degrees of heavy metal pollution occurred in the agricultural soils; specifically, Ni had the most potential for impacting human health. The results from the multivariate statistical analysis and GIS-based geostatistical methods indicated both natural sources (Co and W) and anthropogenic sources (Cr, Cu, Mn, Ni, Pb, Ti, V and Zn). To better identify pollution sources of heavy metals in the agricultural soils, the PMF model was applied. Further source apportionment revealed that enrichments of Pb and Zn were attributed to traffic sources; Cr and Ni were closely related to industrial activities, including mining, smelting, coal combustion, iron and steel production and metal processing; Zn and Cu originated from agricultural activities; and V, Ti and Mn were derived from oil- and coal-related activities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Source apportionment of atmospheric particulate matter (PM) using a constrained US-EPA-PMF5.0 model at different urban environments in France

NASA Astrophysics Data System (ADS)

Salameh, Dalia; Favez, Olivier; Golly, Benjamin; Besombes, Jean Luc; Alleman, Laurent; Albinet, Alexandre; Jaffrezo, Jean Luc

2017-04-01

Particulate matter (PM) is one of the most studied atmospheric pollutant in urban areas due to their adverse effects on human health (Pope et al., 2009). Intrinsic properties of PM (e.g. chemical composition and morphology) are directly linked to their origins. Therefore, a harmonized and comprehensive apportionment study of PM sources in urban environments is extremely required to connect source contributions with PM concentration levels and then develop effective PM abatement strategies. Multivariate receptor models such as Positive Matrix Factorization (PMF) are very useful and have been used worldwide for PM source apportionment (Viana et al., 2008). PMF uses a weighted least-squares fit and quantitatively determines source fingerprints (factors) and their contributions to the total PM mass. However, in many cases, it could be tricky to separate two factors that co-vary due to similar seasonal variations, making unclear the physical sense of the extracted factors. To address such issues of source collinearities, additional specific constraints are incorporated into the model (i.e., constrained PMF) based on user's external knowledge allowing better apportionment results. In this work and within the framework of the SOURCES project, a harmonized source apportionment approach has been implemented and applied for the determination of PM sources on a large number of sites (up to 20) of different typologies (e.g. urban background, industrial, traffic, rural and/or alpine sites) distributed all over France and previously investigated with annual or multiannual studies (2012-2016). A constrained PMF approach (using US-EPA PMF5.0 software) was applied to the comprehensive PM-offline chemical datasets (i.e. carbonaceous fraction, major ions, metals/trace elements, specific organic markers) in a harmonized way for all the investigated sites. Different types of specific chemical constraints from well-characterized sources were defined based on external knowledge and were

Source apportionment and location by selective wind sampling and Positive Matrix Factorization.

PubMed

Venturini, Elisa; Vassura, Ivano; Raffo, Simona; Ferroni, Laura; Bernardi, Elena; Passarini, Fabrizio

2014-10-01

In order to determine the pollution sources in a suburban area and identify the main direction of their origin, PM2.5 was collected with samplers coupled with a wind select sensor and then subjected to Positive Matrix Factorization (PMF) analysis. In each sample, soluble ions, organic carbon, elemental carbon, levoglucosan, metals, and Polycyclic Aromatic Hydrocarbons (PAHs) were determined. PMF results identified six main sources affecting the area: natural gas home appliances, motor vehicles, regional transport, biomass combustion, manufacturing activities, and secondary aerosol. The connection of factor temporal trends with other parameters (i.e., temperature, PM2.5 concentration, and photochemical processes) confirms factor attributions. PMF analysis indicated that the main source of PM2.5 in the area is secondary aerosol. This should be mainly due to regional contributions, owing to both the secondary nature of the source itself and the higher concentration registered in inland air masses. The motor vehicle emission source contribution is also important. This source likely has a prevalent local origin. The most toxic determined components, i.e., PAHs, Cd, Pb, and Ni, are mainly due to vehicular traffic. Even if this is not the main source in the study area, it is the one of greatest concern. The application of PMF analysis to PM2.5 collected with this new sampling technique made it possible to obtain more detailed results on the sources affecting the area compared to a classical PMF analysis.

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

NASA Astrophysics Data System (ADS)

Amato, F.; Pandolfi, M.; Escrig, A.; Querol, X.; Alastuey, A.; Pey, J.; Perez, N.; Hopke, P. K.

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available. In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM 10 and PM 2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM 10 in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650-1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called "pulling equations". ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m -3 (17%) in PM 10, 2.2 μg m -3 (8%) of PM 2.5 and 0.3 μg m -3 (2%) of PM 1. This reveals that resuspension was responsible of the 37%, 15% and 3% of total

Accounting for Intraligand Interactions in Flexible Ligand Docking with a PMF-Based Scoring Function.

PubMed

Lizunov, A Y; Gonchar, A L; Zaitseva, N I; Zosimov, V V

2015-10-26

We analyzed the frequency with which intraligand contacts occurred in a set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. Our analysis showed that flexible ligands often form intraligand hydrophobic contacts, while intraligand hydrogen bonds are rare. The test set was also thoroughly investigated and classified. We suggest a universal method for enhancement of a scoring function based on a potential of mean force (PMF-based score) by adding a term accounting for intraligand interactions. The method was implemented via in-house developed program, utilizing an Algo_score scoring function [ Ramensky et al. Proteins: Struct., Funct., Genet. 2007 , 69 , 349 - 357 .] based on the Tarasov-Muryshev PMF [ Muryshev et al. J. Comput.-Aided Mol. Des. 2003 , 17 , 597 - 605 .]. The enhancement of the scoring function was shown to significantly improve the docking and scoring quality for flexible ligands in the test set of 1300 protein-ligand complexes [ Plewczynski et al. J. Comput. Chem. 2011 , 32 , 742 - 755 .]. We then investigated the correlation of the docking results with two parameters of intraligand interactions estimation. These parameters are the weight of intraligand interactions and the minimum number of bonds between the ligand atoms required to take their interaction into account.

Receptor modelling of fine particles in southern England using CMB including comparison with AMS-PMF factors

NASA Astrophysics Data System (ADS)

Yin, J.; Cumberland, S. A.; Harrison, R. M.; Allan, J.; Young, D. E.; Williams, P. I.; Coe, H.

2015-02-01

similar for the two methods. However, appreciably different concentrations were calculated for the individual primary organic matter contributions, although for most source categories the CMB and AMS-PMF results were highly correlated (r2 = 0.69-0.91). In comparison with the CMB model, the AMS appears to overestimate the biomass burning/coal and food cooking sources by a factor of around 1.5 to 2 while estimates of the traffic source are rather similar for each model. The largest divergence is in the primary/secondary organic matter split, with the AMS estimating an appreciably smaller secondary component. Possible reasons for these discrepancies are discussed, but despite these substantial divergences, the strong correlation of the two methods gives some confidence in their application.

Receptor modelling of fine particles in Southern England using CMB including comparison with AMS-PMF factors

NASA Astrophysics Data System (ADS)

Yin, J.; Cumberland, S. A.; Harrison, R. M.; Allan, J.; Young, D. E.; Williams, P. I.; Coe, H.

2014-09-01

rather similar for the two methods. However, appreciably different concentrations were calculated for the individual primary organic matter contributions, although for most source categories the CMB and AMS-PMF results were highly correlated (r2 = 0.69-0.91). In comparison with the CMB model, the AMS appears to over-estimate the biomass burning/coal and food cooking sources by a factor of around 1.5 to 2 while estimates of the traffic source are rather similar for each model. The largest divergence is in the primary/secondary organic matter split, with the AMS estimating an appreciably smaller secondary component. Possible reasons for these discrepancies are discussed, but despite these substantial divergences, the strong correlation of the two methods gives some confidence in their application.

Comparison of source apportionments of PM2.5 using three receptor models (CMB, PMF, and SMP) in Seoul, Korea

NASA Astrophysics Data System (ADS)

Heo, J.; Kim, J. Y.; Kim, S. W.

2017-12-01

We compared source apportionments of PM2.5 in Seoul, Korea by three receptor models, Chemical Mass Balance (CMB), Positive Matrix Factorization (PMF), and Solver for Mixture Problem (SMP). The CMB model can estimate source apportionment with suitable source profiles of emissions, but it is difficult to find location-specific source profiles. In contrary, the multivariate receptor model does not need source profiles, but fundamental natural physical constraints (FNPCs) required for aerosol source apportionment are different in PMF and SMP. Ninety-six PM2.5 daily samples collected at Korea Institute of Science and Technology (KIST) in Seoul, Korea from October 2012 to September 2013 were analyzed in this study. The average PM2.5 mass concentration over the study period was 41.5 ± 27.7 mg m-3 and secondary inorganic species and organic matter were the main chemical species occupying about 73.7% - 87.9% of the PM2.5 mass concentration in all seasons. Secondary sulfate (18.0% - 26.1%), secondary nitrate (12.1% - 28.5%), vehicle (2.9% - 32.9%), biomass burning (13.2% - 21.3%) were identified by all three receptor models as the major sources accounting for approximately 76.3%-82.7% of the total PM2.5 and contributions of main sources represented their seasonality. However, three receptor models showed significant differences, especially for vehicle emission due to their measured/estimated source profiles. In this presentation, more detailed comparisons among CMB, PMF and SMP models will be presented focusing on the source profiles and contributions.

77 FR 38681 - Submission for review: Presidential Management Fellows (PMF) Application, 3206-0082

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-28

... OFFICE OF PERSONNEL MANAGEMENT Submission for review: Presidential Management Fellows (PMF) Application, 3206-0082 AGENCY: U.S. Office of Personnel Management. ACTION: 60-day notice and request for comments. SUMMARY: The Office of Personnel Management (OPM) offers the general public and other Federal...

Poly-4-vinylphenol (PVP) and Poly(melamine-co-formaldehyde) (PMF)-Based Atomic Switching Device and Its Application to Logic Gate Circuits with Low Operating Voltage.

PubMed

Kang, Dong-Ho; Choi, Woo-Young; Woo, Hyunsuk; Jang, Sungkyu; Park, Hyung-Youl; Shim, Jaewoo; Choi, Jae-Woong; Kim, Sungho; Jeon, Sanghun; Lee, Sungjoo; Park, Jin-Hong

2017-08-16

In this study, we demonstrate a high-performance solid polymer electrolyte (SPE) atomic switching device with low SET/RESET voltages (0.25 and -0.5 V, respectively), high on/off-current ratio (10 5 ), excellent cyclic endurance (>10 3 ), and long retention time (>10 4 s), where poly-4-vinylphenol (PVP)/poly(melamine-co-formaldehyde) (PMF) is used as an SPE layer. To accomplish these excellent device performance parameters, we reduce the off-current level of the PVP/PMF atomic switching device by improving the electrical insulating property of the PVP/PMF electrolyte through adjustment of the number of cross-linked chains. We then apply a titanium buffer layer to the PVP/PMF switching device for further improvement of bipolar switching behavior and device stability. In addition, we first implement SPE atomic switch-based logic AND and OR circuits with low operating voltages below 2 V by integrating 5 × 5 arrays of PVP/PMF switching devices on the flexible substrate. In particular, this low operating voltage of our logic circuits was much lower than that (>5 V) of the circuits configured by polymer resistive random access memory. This research successfully presents the feasibility of PVP/PMF atomic switches for flexible integrated circuits for next-generation electronic applications.

A methodological framework to assess PMP and PMF in snow-dominated watersheds under changing climate conditions - A case study of three watersheds in Québec (Canada)

NASA Astrophysics Data System (ADS)

Rouhani, Hassan; Leconte, Robert

2018-06-01

Climate change will affect precipitation and flood regimes. It is anticipated that the Probable Maximum Precipitation (PMP) and Probable Maximum Flood (PMF) will be modified in a changing climate. This paper aims to quantify and analyze climate change influences on PMP and PMF in three watersheds with different climatic conditions across the province of Québec, Canada. Output data from the Canadian Regional Climate Model (CRCM) was used to estimate PMP and Probable Maximum Snow Accumulation (PMSA) in future climate projections, which was then used to force the SWAT hydrological model to estimate PMF. PMP and PMF values were estimated for two time horizons each spanning 30 years: 1961-1990 (recent past) and 2041-2070 (future). PMP and PMF were separately analyzed for two seasons: summer-fall and spring. Results show that PMF in the watershed located in southern Québec would remain unchanged in the future horizon, but the trend for the watersheds located in the northeastern and northern areas of the province is an increase of up to 11%.

Source apportionment of 1 h semi-continuous data during the 2005 Study of Organic Aerosols in Riverside (SOAR) using positive matrix factorization

NASA Astrophysics Data System (ADS)

Eatough, Delbert J.; Grover, Brett D.; Woolwine, Woods R.; Eatough, Norman L.; Long, Russell; Farber, Robert

Positive matrix factorization (PMF2) was used to elucidate sources of fine particulate material (PM 2.5) for a study conducted during July and August 2005, in Riverside, CA. One-hour averaged semi-continuous measurements were made with a suite of instruments to provide PM 2.5 mass and chemical composition data. Total PM 2.5 mass concentrations (non-volatile plus semi-volatile) were measured with an R&P filter dynamic measurement system (FDMS TEOM) and a conventional TEOM monitor was used to measure non-volatile mass concentrations. PM 2.5 chemical species monitors included a dual-oven Sunset monitor to measure both non-volatile and semi-volatile carbonaceous material, an ion chromatographic-based monitor to measure sulfate and nitrate and an Anderson Aethalometer to measure black carbon (BC). Gas phase data including CO, NO 2, NO x and O 3 were also collected during the sampling period. In addition, single-particle measurements were made using aerosol time-of-flight mass spectrometry (ATOFMS). Twenty different single-particle types consistent with those observed in previous ATOFMS studies in Riverside were identified for the PMF2 analysis. Finally, time-of-flight aerosol mass spectrometry (ToF-AMS) provided data on markers of primary and secondary organic aerosol. Two distinct PMF2 analyses were performed. In analysis 1, all the data except for the ATOFMS and ToF-AMS data were used in an initial evaluation of sources at Riverside during the study. PMF2 was able to identify six factors from the data set corresponding to both primary and secondary sources, primarily from automobile emissions, diesel emissions, secondary nitrate formation, a secondary photochemical associated source, organic emissions and Basin transported pollutants. In analysis 2, the ATOFMS and ToF-AMS data were included in the analysis. In the second analysis, PMF2 was able to identify 16 factors with a variety of both primary and secondary factors being identified, corresponding to both primary

76 FR 44052 - Submission for Review: Presidential Management Fellows (PMF); Nomination Form, OPM 1300

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-22

... accredited colleges and universities to nominate eligible graduate students to the Presidential Management... OFFICE OF PERSONNEL MANAGEMENT Submission for Review: Presidential Management Fellows (PMF); Nomination Form, OPM 1300 AGENCY: U.S. Office of Personnel Management. ACTION: 30-Day Notice and request for...

Investigating the Impact of a Metals Foundry on Neighborhood Air Quality through PM2.5 PMF Analysis and Mobile Environmental Odor Diaries App

NASA Astrophysics Data System (ADS)

Espinoza, D.; Clayton, I.; George, L. A.

2015-12-01

Chapman Elementary School in Portland, OR was identified by USA Today as being in the 2nd percentile of schools in the nation for poor air quality. This ranking was based on the EPA Risk-Screening Environmental Indicators (RSEI) model using the EPA's Toxics Release Inventory (TRI) program. The metals foundry identified in the report as the leading contributor to the poor air quality at Chapman currently meets its Title V permit and reports these permitted emissions to the TRI program. However, the poor air quality ranking is based on models that rely on emissions from permits and are not necessarily reflective of actual emissions. Several observational approaches were employed to assess the potential source contributors to air quality at Chapman. Two MiniVol Tactical Air Samplers (TAS) were co-located 1km from the facility at Chapman Elementary to sample according to the EPA six-day monitoring schedule for one year, filters were analyzed for mass and metals via XRF. Ogawa NO2 samplers were placed at various points around the Chapman neighborhood to develop an NO2 high-density measurement campaign to assess pollutant transport. In addition, a novel mobile environmental odor diaries app was developed and deployed to collect and geo-locate resident observation of odors. All observations were analyzed through mapping, dispersion modeling (AERMOD) and positive-matrix-factorization (PMF) analysis. This multi-dimensional analysis is designed to provide a framework for future studies to address increasing citizen concern about neighborhood level pollution.

Study on the Application of the Combination of TMD Simulation and Umbrella Sampling in PMF Calculation for Molecular Conformational Transitions

PubMed Central

Wang, Qing; Xue, Tuo; Song, Chunnian; Wang, Yan; Chen, Guangju

2016-01-01

Free energy calculations of the potential of mean force (PMF) based on the combination of targeted molecular dynamics (TMD) simulations and umbrella samplings as a function of physical coordinates have been applied to explore the detailed pathways and the corresponding free energy profiles for the conformational transition processes of the butane molecule and the 35-residue villin headpiece subdomain (HP35). The accurate PMF profiles for describing the dihedral rotation of butane under both coordinates of dihedral rotation and root mean square deviation (RMSD) variation were obtained based on the different umbrella samplings from the same TMD simulations. The initial structures for the umbrella samplings can be conveniently selected from the TMD trajectories. For the application of this computational method in the unfolding process of the HP35 protein, the PMF calculation along with the coordinate of the radius of gyration (Rg) presents the gradual increase of free energies by about 1 kcal/mol with the energy fluctuations. The feature of conformational transition for the unfolding process of the HP35 protein shows that the spherical structure extends and the middle α-helix unfolds firstly, followed by the unfolding of other α-helices. The computational method for the PMF calculations based on the combination of TMD simulations and umbrella samplings provided a valuable strategy in investigating detailed conformational transition pathways for other allosteric processes. PMID:27171075

Source apportionment of stack emissions from research and development facilities using positive matrix factorization

NASA Astrophysics Data System (ADS)

Ballinger, Marcel Y.; Larson, Timothy V.

2014-12-01

Research and development (R&D) facility emissions are difficult to characterize due to their variable processes, changing nature of research, and large number of chemicals. Positive matrix factorization (PMF) was applied to volatile organic compound (VOC) concentrations measured in the main exhaust stacks of four different R&D buildings to identify the number and composition of major contributing sources. PMF identified between 9 and 11 source-related factors contributing to stack emissions, depending on the building. Similar factors between buildings were major contributors to trichloroethylene (TCE), acetone, and ethanol emissions; other factors had similar profiles for two or more buildings but not all four. At least one factor for each building was identified that contained a broad mix of many species and constraints were used in PMF to modify the factors to resemble more closely the off-shift concentration profiles. PMF accepted the constraints with little decrease in model fit.

PMF: The front end electronic of the ALFA detector

NASA Astrophysics Data System (ADS)

Barrillon, P.; Blin, S.; Cheikali, C.; Cuisy, D.; Gaspard, M.; Fournier, D.; Heller, M.; Iwanski, W.; Lavigne, B.; De la Taille, C.; Puzo, P.; Socha, J.-L.

2010-11-01

The front end electronic (PMF) of the future ATLAS luminometer is described here. It is composed of a MAPMT and a compact stack of three PCBs, which deliver high voltage, route and read out of the output signals. The third board contains an FPGA and MAROC, a 64-channel ASIC, which can correct the non-uniformity of the MAPMT channels gain, thanks to a variable gain preamplifier. Its main role is to shape and discriminate the input signals at 1/3 photo-electron and produce 64 trigger outputs. Laboratory tests performed on prototype and pre-series PMFs have showed performances in good agreement with the requirements and have fulfilled the approval criteria for the final production of all elements.

Source Apportionment Using Positive Matrix Factorization on Daily Measurements of Inorganic and Organic Speciated PM2.5

PubMed Central

Dutton, Steven J.; Vedal, Sverre; Piedrahita, Ricardo; Milford, Jana B.; Miller, Shelly L.; Hannigan, Michael P.

2012-01-01

Particulate matter less than 2.5 microns in diameter (PM2.5) has been linked with a wide range of adverse health effects. Determination of the sources of PM2.5 most responsible for these health effects could lead to improved understanding of the mechanisms of such effects and more targeted regulation. This has provided the impetus for the Denver Aerosol Sources and Health (DASH) study, a multi-year source apportionment and health effects study relying on detailed inorganic and organic PM2.5 speciation measurements. In this study, PM2.5 source apportionment is performed by coupling positive matrix factorization (PMF) with daily speciated PM2.5 measurements including inorganic ions, elemental carbon (EC) and organic carbon (OC), and organic molecular markers. A qualitative comparison is made between two models, PMF2 and ME2, commonly used for solving the PMF problem. Many previous studies have incorporated chemical mass balance (CMB) for organic molecular marker source apportionment on limited data sets, but the DASH data set is large enough to use multivariate factor analysis techniques such as PMF. Sensitivity of the PMF2 and ME2 models to the selection of speciated PM2.5 components and model input parameters was investigated in depth. A combination of diagnostics was used to select an optimum, 7-factor model using one complete year of daily data with pointwise measurement uncertainties. The factors included 1) a wintertime/methoxyphenol factor, 2) an EC/sterane factor, 3) a nitrate/polycyclic aromatic hydrocarbon (PAH) factor, 4) a summertime/selective aliphatic factor, 5) an n-alkane factor, 6) a middle oxygenated PAH/alkanoic acid factor and 7) an inorganic ion factor. These seven factors were qualitatively linked with known PM2.5 emission sources with varying degrees of confidence. Mass apportionment using the 7-factor model revealed the contribution of each factor to the mass of OC, EC, nitrate and sulfate. On an annual basis, the majority of OC and EC mass

Assessing the long-range transport of PAH to a sub-Arctic site using positive matrix factorization and potential source contribution function

NASA Astrophysics Data System (ADS)

Sofowote, Uwayemi M.; Hung, Hayley; Rastogi, Ankit K.; Westgate, John N.; Deluca, Patrick F.; Su, Yushan; McCarry, Brian E.

2011-02-01

Gas-phase and particle-phase atmospheric samples collected in a sparsely populated sub-Arctic environment in the Yukon Territory, Canada were analyzed for a wide range of organic pollutants including polycyclic aromatic hydrocarbons (PAH). Receptor modeling using positive matrix factorization (PMF) was applied to a PAH data set from samples collected between August 2007 and December 2008 to afford four factors. These factors were designated as fossil fuel combustion emissions, particle-phase wood combustion emissions, gas-phase wood combustion emissions, and unburned petroleum/petrogenic emissions. The multiple linear regression-derived average contributions of these factors to the total PAH concentrations were 14% for fossil fuel combustion, 6% for particle-phase wood combustion emissions, 46% for gas-phase wood combustion emissions and 34% for petrogenic emissions. When the total PAH concentrations (defined as the sum of twenty-two PAH) and the PMF-modeled PAH concentrations set were compared, the correlation was excellent ( R2 = 0.97). Ten-day back trajectories starting at four different heights were used in a potential source contribution function analysis (PSCF) to assess the potential source regions of these PAH factors. Mapping the computed PSCF values for the four PMF factors revealed different source regions in the northern hemisphere for each PMF factor. Atmospheric transport of PAH occurred from both relatively short and long distances with both continental (North American) and trans-oceanic (Asian) sources contributing significantly to the total PAH. This study provides evidence of the transport of fossil fuel and wood combustion emissions from Asia, continental North America and northern Europe to sub-Arctic Canada (and by extension to the Canadian Arctic) primarily during cooler (fall-winter) months. This study demonstrates for the first time that the combined PMF-PSCF methodology can be used to identify geographically-disperse PAH source contributors

Source apportionment by PMF on elemental concentrations obtained by PIXE analysis of PM10 samples collected at the vicinity of lignite power plants and mines in Megalopolis, Greece

NASA Astrophysics Data System (ADS)

Manousakas, M.; Diapouli, E.; Papaefthymiou, H.; Migliori, A.; Karydas, A. G.; Padilla-Alvarez, R.; Bogovac, M.; Kaiser, R. B.; Jaksic, M.; Bogdanovic-Radovic, I.; Eleftheriadis, K.

2015-04-01

Particulate matter (PM) is an important constituent of atmospheric pollution especially in areas under the influence of industrial emissions. Megalopolis is a small city of 10,000 inhabitants located in central Peloponnese in close proximity to three coal opencast mines and two lignite fired power plants. 50 PM10 samples were collected in Megalopolis during the years 2009-11 for elemental and multivariate analysis. For the elemental analysis PIXE was used as one of the most effective techniques in APM analytical characterization. Altogether, the concentrations of 22 elements (Z = 11-33), whereas Black Carbon was also determined for each sample using a reflectometer. Factorization software was used (EPA PMF 3.0) for source apportionment analysis. The analysis revealed that major emission sources were soil dust 33% (7.94 ± 0.27 μg/m3), biomass burning 19% (4.43 ± 0.27 μg/m3), road dust 15% (3.63 ± 0.37 μg/m3), power plant emissions 13% (3.01 ± 0.44 μg/m3), traffic 12% (2.82 ± 0.37 μg/m3), and sea spray 8% (1.99 ± 0.41 μg/m3). Wind trajectories have suggested that metals associated with emission from the power plants came mainly from west and were connected with the locations of the lignite mines located in this area. Soil resuspension, road dust and power plant emissions increased during the warm season of the year, while traffic/secondary, sea spray and biomass burning become dominant during the cold season.

Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

NASA Astrophysics Data System (ADS)

Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

2017-07-01

Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

Evaluating Oil and Gas Speciation Profiles with Factor Analysis of Ambient Volatile Organic Compound Concentrations in the Colorado Front Range

NASA Astrophysics Data System (ADS)

Capps, S.; Paranjothi, G.; Pierce, G. E.; Milford, J. B.

2016-12-01

Increased oil and gas (O&G) development, particularly through the use of hydraulic fracturing, in the Denver-Julesburg Basin (DJB) in Colorado over the last decade has been identified as a source of emissions of air pollutants, which are now included in chemical transport modeling. As one effort to evaluate its impact, ambient concentrations of volatile organic compounds (VOCs) that serve as precursors to ozone formation were measured in an Ozone Precursor Study conducted by the Colorado Department of Public Health and Environment during 2013 and 2014. The study included 6 - 9 a.m. measurements of an extensive suite of ozone-precursor VOCs from a site in an area of intensive O&G development in Platteville, CO, and another site in downtown Denver, CO. To evaluate the influences of urban activity or O&G development on these ambient concentrations, we used the U.S. EPA's Positive Matrix Factorization (PMF) tool. A five-factor PMF solution was selected as providing the best fit to the dataset comprised of VOC measurements for both years and both sites. One PMF factor matches the VOC emissions speciation profile for the flashing gas composition for condensate tanks in the DJB that was developed by the Western Regional Air Partnership for use in chemical transport modeling in the region. The contribution of this factor to individual and total VOC concentrations and ozone production reactivity is evaluated for Platteville and Denver.

Source apportionment of methane and nitrous oxide in California's San Joaquin Valley at CalNex 2010 via positive matrix factorization

NASA Astrophysics Data System (ADS)

Guha, A.; Gentner, D. R.; Weber, R. J.; Provencal, R.; Goldstein, A. H.

2015-03-01

Sources of methane (CH4) and nitrous oxide (N2O) were investigated using measurements from a site in southeast Bakersfield as part of the CalNex (California at the Nexus of Air Quality and Climate Change) experiment from 15 May to 30 June 2010. Typical daily minimum mixing ratios of CH4 and N2O were higher than daily averages that were simultaneously observed at a similar latitude background station (NOAA, Mauna Loa) by approximately 70 and 0.5 ppb, respectively. Substantial enhancements of CH4 and N2O (hourly averages > 500 ppb and > 7 ppb, respectively) were routinely observed suggesting the presence of large regional sources. Collocated measurements of carbon monoxide (CO) and a range of volatile organic compounds (VOCs) (e.g. straight-chain and branched alkanes, cycloalkanes, chlorinated alkanes, aromatics, alcohols, isoprene, terpenes and ketones) were used with a Positive Matrix Factorization (PMF) source apportionment method to estimate the contribution of regional sources to observed enhancements of CH4 and N2O. The PMF technique provided a "top-down" deconstruction of ambient gas-phase observations into broad source categories, yielding a 7-factor solution. We identified these source factors as emissions from evaporative and fugitive; motor vehicles; livestock and dairy; agricultural and soil management; daytime light and temperature driven; non-vehicular urban; and nighttime terpene biogenics and anthropogenics. The dairy and livestock factor accounted for a majority of the CH4 (70-90%) enhancements during the duration of the experiments. Propagation of uncertainties in the PMF-derived factor profiles and time series from bootstrapping analysis resulted in a 29% uncertainty in the CH4 apportionment to this factor. The dairy and livestock factor was also a principal contributor to the daily enhancements of N2O (60-70%) with an uncertainty of 33%. Agriculture and soil management accounted for ~20-25% of N2O enhancements over the course of a day, not

RECEPTOR MODELING OF AMBIENT PARTICULATE MATTER DATA USING POSITIVE MATRIX FACTORIZATION REVIEW OF EXISTING METHODS

EPA Science Inventory

Methods for apportioning sources of ambient particulate matter (PM) using the positive matrix factorization (PMF) algorithm are reviewed. Numerous procedural decisions must be made and algorithmic parameters selected when analyzing PM data with PMF. However, few publications docu...

Source Apportionment of PM2.5 using PMF and CMB: Comparison of the Effects of Transboundary and Local Pollutions in the Western Japan

NASA Astrophysics Data System (ADS)

Iijima, A.; Sugata, S.

2014-12-01

PM2.5 has become one of the most important aspects in recent air pollution issues. In Japan, the achievement rate of the environmental quality standard for PM2.5 is in a worse situation so far (43.3% for ambient air monitoring station, 33.3% for roadside air pollution monitoring station in FY2012). Therefore, source apportionment will be essential to policy and decision making for improving the PM2.5 pollution. Since 2011, we started the field monitoring study called "Current Status Elucidation and Source Contribution Assessment of PM2.5 Pollution in Collaboration with Environmental Research Institutes across Japan" which was granted by the Environment Research and Technology Development Fund (5B-1101) of the Ministry of the Environment, Japan. PM2.5 samples were collected at 14 sites during four campaigns. Chemical analyses of carbonaceous compounds, ionic species, and elements were conducted. Source apportionment was performed by using Positive Matrix Factorization (PMF, EPA PMF 3.0) and Chemical Mass Balance (CMB, EPA CMB 8.1) models. PMF model resolved a six-factor solution. Each of these factors has a distinctive grouping of species that can be associated with a specific source sector (F1: Biomass burning, F2: Sulfate + Oil combustion, F3: Industry, F4: Nitrate, F5: Sulfate + Coal combustion, and F6: Chloride). In the winter campaign (Jan. 24 to Feb. 7) in 2013, F5 accounted for 50% of total PM2.5 mass at Tsushima (34.2°N 129.3°E, the westernmost remote site). The contribution of F5 tended to decrease toward the eastern sites (27% at Fukuoka (33.5°N 130.5°E, urban site), 22% at Higashi-Osaka (34.7°N 135.6°E, urban site)). CMB model showed similar results in the same campaign. Coal combustion accounted for 49%, 30%, and 22% of total PM2.5 mass at Tsushima, Fukuoka, and Higashi-Osaka, respectively (Fig.1). On the other hand, at urban sites, higher contributions from local sources such as secondary nitrate (16% at Fukuoka, 21% at Higashi-Osaka), diesel fuel

Source apportionment of methane and nitrous oxide in California's San Joaquin Valley at CalNex 2010 via positive matrix factorization

NASA Astrophysics Data System (ADS)

Guha, A.; Gentner, D. R.; Weber, R. J.; Provencal, R.; Goldstein, A. H.

2015-10-01

conducted bootstrapping analysis. This is most likely due to an asynchronous pattern of soil-mediated N2O emissions from fertilizer usage and collocated biogenic emissions from crops from the surrounding agricultural operations that is difficult to apportion statistically when using PMF. The evaporative/fugitive source profile, which resembled a mix of petroleum operation and non-tailpipe evaporative gasoline sources, did not include a PMF resolved-CH4 contribution that was significant (< 2 %) compared to the uncertainty in the livestock-associated CH4 emissions. The uncertainty of the CH4 estimates in this source factor, derived from the bootstrapping analysis, is consistent with the ~ 3 % contribution of fugitive oil and gas emissions to the statewide CH4 inventory. The vehicle emission source factor broadly matched VOC profiles of on-road exhaust sources. This source factor had no statistically significant detected contribution to the N2O signals (confidence interval of 3 % of livestock N2O enhancements) and negligible CH4 (confidence interval of 4 % of livestock CH4 enhancements) in the presence of a dominant dairy and livestock factor. The CalNex PMF study provides a measurement-based assessment of the state CH4 and N2O inventories for the southern San Joaquin Valley (SJV). The state inventory attributes ~ 18 % of total N2O emissions to the transportation sector. Our PMF analysis directly contradicts the state inventory and demonstrates there were no discernible N2O emissions from the transportation sector in the southern SJV region.

Methods for Estimating Uncertainty in Factor Analytic Solutions

EPA Science Inventory

The EPA PMF (Environmental Protection Agency positive matrix factorization) version 5.0 and the underlying multilinear engine-executable ME-2 contain three methods for estimating uncertainty in factor analytic models: classical bootstrap (BS), displacement of factor elements (DI...

Application of positive matrix factorization to identify potential sources of PAHs in soil of Dalian, China.

PubMed

Wang, Degao; Tian, Fulin; Yang, Meng; Liu, Chenlin; Li, Yi-Fan

2009-05-01

Soil derived sources of polycyclic aromatic hydrocarbons (PAHs) in the region of Dalian, China were investigated using positive matrix factorization (PMF). Three factors were separated based on PMF for the statistical investigation of the datasets both in summer and winter. These factors were dominated by the pattern of single sources or groups of similar sources, showing seasonal and regional variations. The main sources of PAHs in Dalian soil in summer were the emissions from coal combustion average (46%), diesel engine (30%), and gasoline engine (24%). In winter, the main sources were the emissions from coal-fired boiler (72%), traffic average (20%), and gasoline engine (8%). These factors with strong seasonality indicated that coal combustion in winter and traffic exhaust in summer dominated the sources of PAHs in soil. These results suggested that PMF model was a proper approach to identify the sources of PAHs in soil.

Source identification and spatial distribution of arsenic and heavy metals in agricultural soil around Hunan industrial estate by positive matrix factorization model, principle components analysis and geo statistical analysis.

PubMed

Zhang, Xiaowen; Wei, Shuai; Sun, Qianqian; Wadood, Syed Abdul; Guo, Boli

2018-09-15

Characterizing the distribution and defining potential sources of arsenic and heavy metals are the basic preconditions for reducing the contamination of heavy metals and metalloids. 71 topsoil samples and 61 subsoil samples were collected by grid method to measure the concentration of cadmium (Cd), arsenic (As), lead (Pb), copper (Cu), zinc (Zn), nickel (Ni) and chromium (Cr). Principle components analysis (PCA), GIS-based geo-statistical methods and Positive Matrix Factorization (PMF) were applied. The results showed that the mean concentrations were 9.59 mg kg -1 , 51.28 mg kg -1 , 202.07 mg kg -1 , 81.32 mg kg -1 and 771.22 mg kg -1 for Cd, As, Pb, Cu and Zn, respectively, higher than the guideline values of Chinese Environmental Quality Standard for Soils; while the concentrations of Ni and Cr were very close to recommended value (50 mg kg -1 , 200 mg kg -1 ), and some site were higher than guideline values. The soil was polluted by As and heavy metals in different degree, which had harmful impact on human health. The results from principle components analysis methods extracted three components, namely industrial sources (Cd, Zn and Pb), agricultural sources (As and Cu) and nature sources (Cr and Ni). GIS-based geo-statistical combined with local conditions further apportioned the sources of these trace elements. To better identify pollution sources of As and heavy metals in soil, the PMF was applied. The results of PMF demonstrated that the enrichment of Zn, Cd and Pb were attributed to industrial activities and their contribution was 24.9%; As was closely related to agricultural activities and its contribution was 19.1%; Cr, a part of Cu and Ni were related to subsoil and their contribution was 30.1%; Cu and Pb came from industry and traffic emission and their contribution was 25.9%. Copyright © 2018 Elsevier Inc. All rights reserved.

Source apportionment to PM10 and PM2.5 at multiple sites in the Bay of Gibraltar (S Spain) by PMF: estimate of shipping emission

NASA Astrophysics Data System (ADS)

Pandolfi, M.; Gonzalez-Castanedo, Y.; Alastuey, A.; Pey, J.; Querol, X.; de La Rosa, J. D.

2009-04-01

The recognized adverse health effect of the PM10 and PM2.5 particles leads to an increasing demand of a more efficient control of pollutant emissions especially in industrial and/or urban sites. The degree with which the control of the emissions can be accomplished depends on the identification of the pollutant sources and the estimation of their contribution. The chemical speciation of ambient PM coupled with receptor modelling can be considered as a powerful tool to estimate origin of the sources and their contribution to the PM10 and PM2.5 fractions. This work aims to evaluate the effect on air quality of the anthropogenic activities performed in one of the most important industrial estates of Southern Spain located in the Bay of Gibraltar. The area under study is characterized by the presence of metallurgy industries and oil refineries around which four urban agglomerates are located, namely: Los Barrios (36°11'7.39"N, 5°29'33.89"O), La Linea (36° 9'40.24"N, 5°20'53.72"O), Algeciras (36°7'47.21"N, 5°26'51.71"O) y Puente Mayorga (36°10'54.60"N, 5°23'8.32"O). Traffic is consequently another important source of pollutants in the considered area together with an intense shipping activity. The estimation of the pollutant sources and their contribution was obtained by applying the Positive Matrix Factorization (PMF) model to the PM10 and PM2.5 levels and chemical speciation data simultaneously obtained in the four urban agglomerates during a period of 4 years (March 2003 - December 2007). Given the small size of the area under study, the PM data collected in all the four stations was simultaneously introduced within the PMF model. This procedure allowed the PMF to use a higher number of data rather than using the 4 database separately, thus improving the performances of the model. Following this procedure a total of 567 and 341 samples for the PM10 and PM2.5 fractions respectively were introduced within the PMF. Moreover, before running the model, a detailed

Diurnal and seasonal trends and source apportionment of redox-active metals in Los Angeles using a novel online metal monitor and Positive Matrix Factorization (PMF)

NASA Astrophysics Data System (ADS)

Mousavi, Amirhosein; Sowlat, Mohammad H.; Sioutas, Constantinos

2018-02-01

In the present study, we identified the sources of four redox-active metals, including Iron (Fe), Chromium (Cr), Cupper (Cu), and Manganese (Mn) and quantified the contribution of these sources to PM2.5 concentrations in central Los Angeles, California, by employing time-resolved measurements (i.e., a time resolution of 2 h) with a recently developed online metal monitor and Positive Matrix Factorization (PMF). Size distribution of ambient PM (14 nm-10 μm) was measured using the Scanning Mobility Particle Sizer (SMPS) and Optical Particle Sizer (OPS). Auxiliary variables were also collected, including elemental (EC) and organic carbon (OC), gaseous pollutants (NO2 and O3), meteorological parameters (including relative humidity (RH) and temperature), and traffic data (for heavy- (HDVs) and light-duty vehicles (LDVs)). A 4-factor solution was found to be optimum for the chemically-speciated dataset, whereas a 5-factor solution appeared to be most plausible for the size distribution data. The factors included fresh traffic, soil/road dust, urban background aerosol, secondary aerosol, and nucleation (only resolved for the size distribution data). Fresh traffic was the major contributor to Fe and Cu concentrations, whereas Cr was mostly found in the urban background aerosol (reflecting a mixture of small local sources as well as aged traffic emissions), and Mn mostly came from both soil/road dust and was to a lesser degree found in urban background aerosol. Secondary aerosol did not contribute to the concentrations of any of these metals, but was associated with very high loading of OC, as expected. Even though the urban background aerosol and secondary aerosol appeared to be characterized by "aged" particles and have a rather homogeneous spatial distribution, the reactions and processes involved in their formation are entirely different. Our results provide insights into the sources of redox-active metals in central Los Angeles. They also underscore the benefits of

Composition and source apportionment of PM1 at urban site Kanpur in India using PMF coupled with CBPF

NASA Astrophysics Data System (ADS)

Rai, Pragati; Chakraborty, Abhishek; Mandariya, Anil Kumar; Gupta, Tarun

2016-09-01

This study addresses the three major questions: (1) what are the emission sources of PM1 which are affecting the study area; (2) where do these emission sources come from; and (3) is there any temporal variation in the emission sources. To address these issues, two advanced statistical methods are described in this paper. Identification of emission sources was performed by EPA PMF (v 5.0) and to understand the temporal variability, sampling was done for three winter seasons 2008-09, 2009-10 and 2011-12 within Kanpur city. To identify the possible source directions, Conditional Bivariate Probability function (CBPF) was used. The average PM1 concentration was higher in 2008-09 followed by 2011-12 and 2009-10 winter seasons. 2008-09 winter showed sources such as secondary sources mixed with power plant emission (42.8%), industrial emission (32.3%), coal combustion, brick kilns and vehicular emission (13.2%) and residual oil combustion and road dust (11.7%). The major contributors during winter season 2009-10 were secondary sources (33.1%), biomass burning (23.3%), heavy oil combustion (13%), vehicular emission mixed with crustal dust (11.3%), leather tanning industries (10.3%), industrial emission (4%), coal combustion and brick kilns (3.4%) and solid waste burning and incineration (1.5%) compared to secondary sources mixed with biomass burning (42.3%), industrial emission and crustal dust (35.1%) and vehicular emission and brick kilns (22.6%) during 2011-12 winter season. PMF model revealed that secondary sources were the main contributors for all the three winter seasons followed by biomass burning and power plant emission. The results of CBPF analysis agreed well with the locations of known local point sources., e.g. in the case of industrial emissions, the maximum probability was in the direction between NES direction where almost all the major industries are located in and around Kanpur while in the opposite direction the probability of biomass burning was high

Positive matrix factorization and trajectory modelling for source identification: A new look at Indian Ocean Experiment ship observations

NASA Astrophysics Data System (ADS)

Bhanuprasad, S. G.; Venkataraman, Chandra; Bhushan, Mani

The sources of aerosols on a regional scale over India have only recently received attention in studies using back trajectory analysis and chemical transport modelling. Receptor modelling approaches such as positive matrix factorization (PMF) and the potential source contribution function (PSCF) are effective tools in source identification of urban and regional-scale pollution. In this work, PMF and PSCF analysis is applied to identify categories and locations of sources that influenced surface concentrations of aerosols in the Indian Ocean Experiment (INDOEX) domain measured on-board the research vessel Ron Brown [Quinn, P.K., Coffman, D.J., Bates, T.S., Miller, T.L., Johnson, J.E., Welton, E.J., et al., 2002. Aerosol optical properties during INDOEX 1999: means, variability, and controlling factors. Journal of Geophysical Research 107, 8020, doi:10.1029/2000JD000037]. Emissions inventory information is used to identify sources co-located with probable source regions from PSCF. PMF analysis identified six factors influencing PM concentrations during the INDOEX cruise of the Ron Brown including a biomass combustion factor (35-40%), three industrial emissions factors (35-40%), primarily secondary sulphate-nitrate, balance trace elements and Zn, and two dust factors (20-30%) of Si- and Ca-dust. The identified factors effectively predict the measured submicron PM concentrations (slope of regression line=0.90±0.20; R2=0.76). Probable source regions shifted based on changes in surface and elevated flows during different times in the ship cruise. They were in India in the early part of the cruise, but in west Asia, south-east Asia and Africa, during later parts of the cruise. Co-located sources include coal-fired electric utilities, cement, metals and petroleum production in India and west Asia, biofuel combustion for energy and crop residue burning in India, woodland/forest burning in north sub-Saharan Africa and forest burning in south-east Asia. Significant findings

Positive matrix factorization of PM2.5 - eliminating the effects of gas/particle partitioning of semivolatile organic compounds.

PubMed

Xie, M; Barsanti, K C; Hannigan, M P; Dutton, S J; Vedal, S

2013-01-01

Gas-phase concentrations of semi-volatile organic compounds (SVOCs) were calculated from gas/particle (G/P) partitioning theory using their measured particle-phase concentrations. The particle-phase data were obtained from an existing filter measurement campaign (27 January 2003-2 October 2005) as a part of the Denver Aerosol Sources and Health (DASH) study, including 970 observations of 71 SVOCs (Xie et al., 2013). In each compound class of SVOCs, the lighter species (e.g. docosane in n alkanes, fluoranthene in PAHs) had higher total concentrations (gas + particle phase) and lower particle-phase fractions. The total SVOC concentrations were analyzed using positive matrix factorization (PMF). Then the results were compared with source apportionment results where only particle-phase SVOC concentrations were used (particle only-based study; Xie et al., 2013). For the particle only-based PMF analysis, the factors primarily associated with primary or secondary sources ( n alkane, EC/sterane and inorganic ion factors) exhibit similar contribution time series ( r = 0.92-0.98) with their corresponding factors ( n alkane, sterane and nitrate+sulfate factors) in the current work. Three other factors (light n alkane/PAH, PAH and summer/odd n alkane factors) are linked with pollution sources influenced by atmospheric processes (e.g. G/P partitioning, photochemical reaction), and were less correlated ( r = 0.69-0.84) with their corresponding factors (light SVOC, PAH and bulk carbon factors) in the current work, suggesting that the source apportionment results derived from particle-only SVOC data could be affected by atmospheric processes. PMF analysis was also performed on three temperature-stratified subsets of the total SVOC data, representing ambient sampling during cold (daily average temperature < 10 °C), warm (≥ 10 °C and ≤ 20 °C) and hot (> 20 °C) periods. Unlike the particle only-based study, in this work the factor characterized by the low molecular weight (MW

Positive matrix factorization as source apportionment of soil lead and cadmium around a battery plant (Changxing County, China).

PubMed

Xue, Jian-long; Zhi, Yu-you; Yang, Li-ping; Shi, Jia-chun; Zeng, Ling-zao; Wu, Lao-sheng

2014-06-01

Chemical compositions of soil samples are multivariate in nature and provide datasets suitable for the application of multivariate factor analytical techniques. One of the analytical techniques, the positive matrix factorization (PMF), uses a weighted least square by fitting the data matrix to determine the weights of the sources based on the error estimates of each data point. In this research, PMF was employed to apportion the sources of heavy metals in 104 soil samples taken within a 1-km radius of a lead battery plant contaminated site in Changxing County, Zhejiang Province, China. The site is heavily contaminated with high concentrations of lead (Pb) and cadmium (Cd). PMF successfully partitioned the variances into sources related to soil background, agronomic practices, and the lead battery plants combined with a geostatistical approach. It was estimated that the lead battery plants and the agronomic practices contributed 55.37 and 29.28%, respectively, for soil Pb of the total source. Soil Cd mainly came from the lead battery plants (65.92%), followed by the agronomic practices (21.65%), and soil parent materials (12.43%). This research indicates that PMF combined with geostatistics is a useful tool for source identification and apportionment.

Identification and apportionment of hazardous elements in the sediments in the Yangtze River estuary.

PubMed

Wang, Jiawei; Liu, Ruimin; Wang, Haotian; Yu, Wenwen; Xu, Fei; Shen, Zhenyao

2015-12-01

In this study, positive matrix factorization (PMF) and principal components analysis (PCA) were combined to identify and apportion pollution-based sources of hazardous elements in the surface sediments in the Yangtze River estuary (YRE). Source identification analysis indicated that PC1, including Al, Fe, Mn, Cr, Ni, As, Cu, and Zn, can be defined as a sewage component; PC2, including Pb and Sb, can be considered as an atmospheric deposition component; and PC3, containing Cd and Hg, can be considered as an agricultural nonpoint component. To better identify the sources and quantitatively apportion the concentrations to their sources, eight sources were identified with PMF: agricultural/industrial sewage mixed (18.6 %), mining wastewater (15.9 %), agricultural fertilizer (14.5 %), atmospheric deposition (12.8 %), agricultural nonpoint (10.6 %), industrial wastewater (9.8 %), marine activity (9.0 %), and nickel plating industry (8.8 %). Overall, the hazardous element content seems to be more connected to anthropogenic activity instead of natural sources. The PCA results laid the foundation for the PMF analysis by providing a general classification of sources. PMF resolves more factors with a higher explained variance than PCA; PMF provided both the internal analysis and the quantitative analysis. The combination of the two methods can provide more reasonable and reliable results.

Source apportionments of PM2.5 organic carbon using molecular marker Positive Matrix Factorization and comparison of results from different receptor models

NASA Astrophysics Data System (ADS)

Heo, Jongbae; Dulger, Muaz; Olson, Michael R.; McGinnis, Jerome E.; Shelton, Brandon R.; Matsunaga, Aiko; Sioutas, Constantinos; Schauer, James J.

2013-07-01

Four hundred fine particulate matter (PM2.5) samples collected over a 1-year period at two sites in the Los Angeles Basin were analyzed for organic carbon (OC), elemental carbon (EC), water soluble organic carbon (WSOC) and organic molecular markers. The results were used in a Positive Matrix Factorization (PMF) receptor model to obtain daily, monthly and annual average source contributions to PM2.5 OC. Results of the PMF model showed similar source categories with comparable year-long contributions to PM2.5 OC across the sites. Five source categories providing reasonably stable profiles were identified: mobile, wood smoke, primary biogenic, and two types of secondary organic carbon (SOC) (i.e., anthropogenic and biogenic emissions). Total primary emission factors and total SOC factors contributed approximately 60% and 40%, respectively, to the annual-average OC concentrations. Primary sources showed strong seasonal patterns with high winter peaks and low summer peaks, while SOC showed a reverse pattern with highs in the spring and summer in the region. Interestingly, smoke from forest fires which occurred episodically in California during the summer and fall of 2009 was identified and combined with the primary biogenic source as one distinct factor to the OC budget. The PMF resolved factors were further investigated and compared to a chemical mass balance (CMB) model and a second multi-variant receptor model (UNMIX) using molecular markers considered in the PMF. Good agreement between the source contribution from mobile sources and biomass burning for three models were obtained, providing additional weight of evidence that these source apportionment techniques are sufficiently accurate for policy development. However, the CMB model did not quantify primary biogenic emissions, which were included in other sources with the SOC. Both multivariate receptor models, the PMF and the UNMIX, were unable to separate source contributions from diesel and gasoline engines.

PM 10 metal concentrations and source identification using positive matrix factorization and wind sectoring in a French industrial zone

NASA Astrophysics Data System (ADS)

Alleman, Laurent Y.; Lamaison, Laure; Perdrix, Esperanza; Robache, Antoine; Galloo, Jean-Claude

2010-06-01

The elemental composition data of ambient aerosols collected upon selected wind sectors in the highly industrialised harbour of Dunkirk (France) were interpreted using pollution roses, elemental ratios, Enrichment Factors (EF), Principal Component Analysis (PCA) and Positive Matrix Factorization (PMF) receptor model. The objective was to identify the possible sources of PM10 aerosols, their respective chemical tracers and to determine their relative contribution at the sampling site. PM10 particles samples were collected from June 2003 to March 2005 in order to analyse up to 35 elements (Ag, Al, As, Ba, Bi, Ca, Cd, Ce, Co, Cr, Cs, Cu, Eu, Fe, K, La, Mg, Mn, Mo, Na, Ni, Pb, Rb, S, Sb, Sc, Si, Sm, Sr, Th, Ti, U, V, Zn and Zr) using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES) and ICP-Mass Spectrometry (MS). A significant effort has been made on estimating the total uncertainty of each result by regularly analysing blanks, quality controls and SRM NIST standards. Based on this procedure, a selected set of 24 "robust" elements was compared to the 35-element matrix in order to evaluate the sturdiness of our PMF statistical treatment. Eight source factors were resolved by PCA for all the wind sectors explaining 90% of the total data variance. The PMF results confirmed that eight physically interpretable factors contributed to the ambient particulate pollution at the sampling site: crustal dust (11%), marine aerosols (12%), petrochemistry activities (9.2%), metallurgical sintering plant (8.6%), metallurgical coke plant (12.6%), ferromanganese plant (6.6%), road transport (15%) and a less clearly interpretable profile probably associated to dust resuspension (13%). These weighted contributions against wind direction frequencies demonstrate that industrial sources are the most important contributors to this site (37%) followed by the natural sources (detrital and marine sources) (23%) and the road transport (15%).

Organic tracer-based source analysis of PM2.5 organic and elemental carbon: A case study at Dongguan in the Pearl River Delta, China

NASA Astrophysics Data System (ADS)

Wang, Qiong Qiong; Huang, X. H. Hilda; Zhang, Ting; Zhang, Qingyan; Feng, Yongming; Yuan, Zibing; Wu, Dui; Lau, Alexis K. H.; Yu, Jian Zhen

2015-10-01

Organic carbon (OC) and elemental carbon (EC) are major constituents of PM2.5 and their source apportionment remains a challenging task due to the great diversity of their sources and lack of source-specific tracer data. In this work, sources of OC and EC are investigated using positive matrix factorization (PMF) analysis of PM2.5 chemical composition data, including major ions, OC, EC, elements, and organic molecular source markers, for a set of 156 filter samples collected over three years from 2010 to 2012 at Dongguan in the Pearl River Delta, China. The key organic tracers include levoglucosan, mannosan, hopanes, C27-C33n-alkanes, and polycyclic aromatic hydrocarbons (PAHs). Using these species as input for the PMF model, nine factors were resolved. Among them, biomass burning and coal combustion were significant sources contributing 15-17% of OC and 24-30% and 34-35% of EC, respectively. Industrial emissions and ship emissions, identified through their characteristic metal signatures, contributed 16-24% and 7-8% of OC and 8-11% and 16-17% of EC, respectively. Vehicle exhaust was a less significant source, accounting for 3-4% of OC and 5-8% of EC. Secondary OC, taken to be the sum of OC present in secondary sulfate and nitrate formation source factors, made up 27-36% of OC. Plastic burning, identified through 1,3,5-triphenylbenzene as a tracer, was a less important source for OC(≤4%) and EC (5-10%), but a significant source for PAHs at this site. The utility of organic source tracers was demonstrated by comparing PMF runs with different combinations of organic tracers removed from the input species list. Levoglucosan and mannosan were important additions to distinguish biomass burning from coal combustion by reducing collinearity among source profiles. Inclusion of hopanes and 1,3,5-triphenylbenzene was found to be necessary in resolving the less significant sources vehicle exhaust and plastic burning. Inclusion of C27-C33n-alkanes and PAHs can influence the

Physical factors influence for biologic systems

NASA Astrophysics Data System (ADS)

Piruzyan, L. A.

2005-08-01

Physical methods are widely spread in diagnostics and therapy of different pathologies, especially in oncology. The application of lasers occurred to be the perspective approach for combined methods application in medicine. Our work is devoted to investigation of thermal effect of focused laser beam in the model of Garding-Passi melanoma and also to the study of free radicals activity after the radiation with non-focused laser beam. The histologic alterations correlated with theoretical calculations of temperature distribution in irradiated tissue for energies 30-60 J attracted our interest. The values of maximal temperatures in depths of tissue for energies 30-60 J were carried out. In the model of permanent magnetic field (PMF) effect for mice ascites sarcoma 37 we have showed the linear dependence of tumor growth inhibition from the period of PMF treatment. Simultaneously we investigated PMF influence for free radical"s (FR) concentrations in mice organs and tissues and potentially appearing questions of PMF effect for biopotential in connection with FR formation. We have also studied the alterations of K, Na and Ca ions concentrations in ascetic fluids after animal"s PMF treatment. We revealed some reasons of biopotential generation and concluded that biopotential is not the result of specific ions gradient only but its generation can be followed by free radicals states appearance and occurrence of semi-conductivity in biostructures.

Coupling chemical transport model source attributions with positive matrix factorization: application to two IMPROVE sites impacted by wildfires.

PubMed

Sturtz, Timothy M; Schichtel, Bret A; Larson, Timothy V

2014-10-07

Source contributions to total fine particle carbon predicted by a chemical transport model (CTM) were incorporated into the positive matrix factorization (PMF) receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was varied using a weighting parameter applied to an object function as implemented in the Multilinear Engine (ME-2). The methodology provides the ability to separate features that would not be identified using PMF alone, without sacrificing fit to observations. The hybrid model was applied to IMPROVE data taken from 2006 through 2008 at Monture and Sula Peak, Montana. It was able to separately identify major contributions of total carbon (TC) from wildfires and minor contributions from biogenic sources. The predictions of TC had a lower cross-validated RMSE than those from either PMF or CTM alone. Two unconstrained, minor features were identified at each site, a soil derived feature with elevated summer impacts and a feature enriched in sulfate and nitrate with significant, but sporadic contributions across the sampling period. The respective mean TC contributions from wildfires, biogenic emissions, and other sources were 1.18, 0.12, and 0.12 ugC/m(3) at Monture and 1.60, 0.44, and 0.06 ugC/m(3) at Sula Peak.

Source apportionment and toxicity of atmospheric polycyclic aromatic hydrocarbons by PMF: Quantifying the influence of coal usage in Taiyuan, China

NASA Astrophysics Data System (ADS)

Yan, Yulong; He, Qiusheng; Guo, Lili; Li, Hongyan; Zhang, Hefeng; Shao, Min; Wang, Yuhang

2017-09-01

Atmospheric polycyclic aromatic hydrocarbons (PAHs) were analyzed in the gas phase and total suspended particulate (TSP) from summer 2014 to spring 2015 in Taiyuan, northern China. Taiyuan is an area with some of the highest atmospheric PAH levels in the world, and the total PAHs was highest in winter, followed by autumn, spring and summer. Low air temperature and a southern wind with low speed often led to higher PAH levels in Taiyuan. Although less than a half fraction, the benzo[a]pyrene equivalent concentration (BEQ) of particulate PAHs was almost equal to that of the total PAHs. Four sources, coal combustion, vehicle emissions, coke processing and biomass burning, were determined by positive matrix factorization (PMF), with contributions of 41.36%, 24.74%, 19.71% and 14.18% to the total PAHs in Taiyuan, respectively. Compared with the total PAHs, the particulate PAH solution underestimated the contribution of the coke processing, especially in winter, and overestimated vehicle emissions. The coke processing had a greater contribution to atmospheric PAHs with a southern wind at low speeds in winter in Taiyuan. Ultimately, the coke plants distributed in the Taiyuan-Linfen-Yuncheng basin should receive greater attention for air quality improvement in Taiyuan.

A new method to quantify the health risks from sources of perfluoroalkyl substances, combined with positive matrix factorization and risk assessment models.

PubMed

Xu, Jiao; Shi, Guo-Liang; Guo, Chang-Sheng; Wang, Hai-Ting; Tian, Ying-Ze; Huangfu, Yan-Qi; Zhang, Yuan; Feng, Yin-Chang; Xu, Jian

2018-01-01

A hybrid model based on the positive matrix factorization (PMF) model and the health risk assessment model for assessing risks associated with sources of perfluoroalkyl substances (PFASs) in water was established and applied at Dianchi Lake to test its applicability. The new method contains 2 stages: 1) the sources of PFASs were apportioned by the PMF model and 2) the contribution of health risks from each source was calculated by the new hybrid model. Two factors were extracted by PMF, with factor 1 identified as aqueous fire-fighting foams source and factor 2 as fluoropolymer manufacturing and processing and perfluorooctanoic acid production source. The health risk of PFASs in the water assessed by the health risk assessment model was 9.54 × 10 -7  a -1 on average, showing no obvious adverse effects to human health. The 2 sources' risks estimated by the new hybrid model ranged from 2.95 × 10 -10 to 6.60 × 10 -6  a -1 and from 1.64 × 10 -7 to 1.62 × 10 -6  a -1 , respectively. The new hybrid model can provide useful information on the health risks of PFAS sources, which is helpful for pollution control and environmental management. Environ Toxicol Chem 2018;37:107-115. © 2017 SETAC. © 2017 SETAC.

Emission sources estimation of size-segregated suburban aerosols measured in continental part of Balkan region using PMF5.0 multivariate receptor model

NASA Astrophysics Data System (ADS)

Petrovic, Srdjan; Đuričić-Milanković, Jelena; Anđelković, Ivan; Pantelić, Ana; Gambaro, Andrea; Đorđević, Dragana

2017-04-01

Using Low-Pressure Cascade Impactors by Dr Berner size segregated particulate matter in the size ranges: 0.27 ≤ Dp ≤ 0.53 μm, 0.53 ≤ Dp ≤ 1.06 μm, 1.06 ≤ Dp ≤ 2.09 μm, 2.09 ≤ Dp ≤ 4.11 μm, 4.11 ≤ Dp ≤ 8.11 μm and 8.11 ≤ Dp ≤ 16 μm were collected. Forty-eight-hour size segregated particulate matter samples from atmospheric aerosols in the sub-urban site of Belgrade were measured during two years (in 2012th to 2013in). ICP-MS was used to quantify next elements: Ag, Al, As, Ba, Be, Ca, Cd, Co, Cr, Cu, Fe, K, Hg, Na, Ni, Mg, Mn, Mo, Pb, Se, Sb, Ti, Tl, V and Zn. In order to examine the number of sources and their fingerprints, EPA PMF 5.0 multivariate receptor tool was used. Error estimation methods (bootstrap, displacement, and bootstrap enhanced by displacement) in the analysis of the obtained solutions have enabled proper detection of the number and types of sources. This analysis of the results indicated the existence of four main sources that contribute to air pollution in the suburban area of Belgrade.

Constrained positive matrix factorization: Elemental ratios, spatial distinction, and chemical transport model source contributions

NASA Astrophysics Data System (ADS)

Sturtz, Timothy M.

Source apportionment models attempt to untangle the relationship between pollution sources and the impacts at downwind receptors. Two frameworks of source apportionment models exist: source-oriented and receptor-oriented. Source based apportionment models use presumed emissions and atmospheric processes to estimate the downwind source contributions. Conversely, receptor based models leverage speciated concentration data from downwind receptors and apply statistical methods to predict source contributions. Integration of both source-oriented and receptor-oriented models could lead to a better understanding of the implications sources have on the environment and society. The research presented here investigated three different types of constraints applied to the Positive Matrix Factorization (PMF) receptor model within the framework of the Multilinear Engine (ME-2): element ratio constraints, spatial separation constraints, and chemical transport model (CTM) source attribution constraints. PM10-2.5 mass and trace element concentrations were measured in Winston-Salem, Chicago, and St. Paul at up to 60 sites per city during two different seasons in 2010. PMF was used to explore the underlying sources of variability. Information on previously reported PM10-2.5 tire and brake wear profiles were used to constrain these features in PMF by prior specification of selected species ratios. We also modified PMF to allow for combining the measurements from all three cities into a single model while preserving city-specific soil features. Relatively minor differences were observed between model predictions with and without the prior ratio constraints, increasing confidence in our ability to identify separate brake wear and tire wear features. Using separate data, source contributions to total fine particle carbon predicted by a CTM were incorporated into the PMF receptor model to form a receptor-oriented hybrid model. The level of influence of the CTM versus traditional PMF was

Clinical study on mandibular fracture after marginal resection of the mandible.

PubMed

Okuyama, Kohei; Michi, Yasuyuki; Mizutani, Miho; Yamashiro, Masashi; Kaida, Atsushi; Harada, Kiyoshi

2016-05-01

Postoperative mandibular fracture (PMF) after marginal resection (MR) of the mandible remains an unresolved issue, and it has been reported that at least 10 mm of postoperative mandibular body height (PMBH) is required to prevent PMF. This study evaluated the clinical, physical, and structural risk factors for PMF in MR patients and determined appropriate preventive measures for PMF. This retrospective study included 44 patients with lower gingival carcinoma who underwent MR. PMF occurred in four of these patients. Thirteen associated factors identified from medical records and radiographs were statistically analyzed. Mandibular body height (MBH) preservation ratio originally evaluated as less than 0.3, more than 20 remaining teeth after surgery, and inferior alveolar canal (IAC) exposure were significant risk factors for PMF. Prostheses and number of remaining teeth were also correlated with PMF. The preserved mandibular bone should be reinforced in patients with an MBH preservation ratio of less than 0.3, more than 20 remaining teeth after surgery, and intraoperative IAC exposure. Patients with prostheses are at an increased risk of PMF compared with those without because of stable occlusion and a strong occlusal force. Our novel findings provide useful reference standards for PMF prevention in MR patients. Copyright © 2016 Elsevier Inc. All rights reserved.

Chemical composition of atmospheric aerosols resolved via positive matrix factorization

NASA Astrophysics Data System (ADS)

Äijälä, Mikko; Junninen, Heikki; Heikkinen, Liine; Petäjä, Tuukka; Kulmala, Markku; Worsnop, Douglas; Ehn, Mikael

2017-04-01

Atmospheric particulate matter is a complex mixture of various chemical species such as organic compounds, sulfates, nitrates, ammonia, chlorides, black carbon and sea salt. As aerosol chemical composition strongly influences aerosol climate effects (via cloud condensation nucleus activation, hygroscopic properties, aerosol optics, volatility and condensation) as well as health effects (toxicity, carcinogenicity, particle morphology), detailed understanding of atmospheric fine particle composition is widely beneficial for understanding these interactions. Unfortunately the comprehensive, detailed measurement of aerosol chemistry remains difficult due to the wide range of compounds present in the atmosphere as well as for the miniscule mass of the particles themselves compared to their carrier gas. Aerosol mass spectrometer (AMS; Canagaratna et al., 2007) is an instrument often used for characterization of non-refractive aerosol types: the near-universal vaporization and ionisation technique allows for measurement of most atmospheric-relevant compounds (with the notable exception of refractory matter such as sea salt, black carbon, metals and crustal matter). The downside of the hard ionisation applied is extensive fragmentation of sample molecules. However, the apparent loss of information in fragmentation can be partly offset by applying advanced statistical methods to extract information from the fragmentation patterns. In aerosol mass spectrometry statistical analysis methods, such as positive matrix factorization (PMF; Paatero, 1999) are usually applied for aerosol organic component only, to keep the number of factors to be resolved manageable, to retain the inorganic components for solution validation via correlation analysis, and to avoid inorganic species dominating the factor model. However, this practice smears out the interactions between organic and inorganic chemical components, and hinders the understanding of the connections between primary and

Source identification of PM10 pollution in subway passenger cabins using positive matrix factorization

NASA Astrophysics Data System (ADS)

Park, Duckshin; Oh, Miseok; Yoon, Younghun; Park, Eunyoung; Lee, Kiyoung

2012-03-01

Monitoring the air quality in subway passenger cabins is important because of the large number of passengers and potentially high levels of air pollution. This report characterized PM10 levels in subway cabins in Seoul, Korea, and identified PM10 sources using elemental analysis and receptor modeling. PM10 levels in subway cabins were continuously measured using a light scattering monitor during rush and non-rush hours. A total of 41 measurements were taken during rush and non-rush hours, and the measurements were repeated in all four seasons. Filter samples were also collected for elemental composition analysis. Major PM10 sources were identified using positive matrix factorization (PMF). The in-cabin PM10 concentrations were the highest in the winter at 152.8 μg m-3 during rush hours and 90.2 μg m-3 during non-rush hours. While PM10 levels were higher during rush hours than during non-rush hours in three seasons (excluding summer), these levels were not associated with number of passenger. Elemental analysis showed that the PM10 was composed of 52.5% inorganic elements, 10.2% anions, and 37.3% other. Fe was the most abundant element and significantly correlated (p < 0.01) with Mn (r = 0.97), Ti (r = 0.91), Cr (r = 0.88), Ni (r = 0.89), and Cu (r = 0.88). Fe, Mn, Cr, and Cu are indicators of railroad-related PM10 sources. The PM10 sources characterized by PMF were soil and road dust sources (27.2%), railroad-related sources (47.6%), secondary nitrate sources (16.2%), and a chlorine factor mixed with a secondary sulfate source (9.1%). Overall, railroad-related sources contributed the most PM10 to subway cabin air.

Source contributions to PM10 and arsenic concentrations in Central Chile using positive matrix factorization

NASA Astrophysics Data System (ADS)

Hedberg, Emma; Gidhagen, Lars; Johansson, Christer

Sampling of particles (PM10) was conducted during a one-year period at two rural sites in Central Chile, Quillota and Linares. The samples were analyzed for elemental composition. The data sets have undergone source-receptor analyses in order to estimate the sources and their abundance's in the PM10 size fraction, by using the factor analytical method positive matrix factorization (PMF). The analysis showed that PM10 was dominated by soil resuspension at both sites during the summer months, while during winter traffic dominated the particle mass at Quillota and local wood burning dominated the particle mass at Linares. Two copper smelters impacted the Quillota station, and contributed to 10% and 16% of PM10 as an average during summer and winter, respectively. One smelter impacted Linares by 8% and 19% of PM10 in the summer and winter, respectively. For arsenic the two smelters accounted for 87% of the monitored arsenic levels at Quillota and at Linares one smelter contributed with 72% of the measured mass. In comparison with PMF, the use of a dispersion model tended to overestimate the smelter contribution to arsenic levels at both sites. The robustness of the PMF model was tested by using randomly reduced data sets, where 85%, 70%, 50% and 33% of the samples were included. In this way the ability of the model to reconstruct the sources initially found by the original data set could be tested. On average for all sources the relative standard deviation increased from 7% to 25% for the variables identifying the sources, when decreasing the data set from 85% to 33% of the samples, indicating that the solution initially found was very stable to begin with. But it was also noted that sources due to industrial or combustion processes were more sensitive for the size of the data set, compared to the natural sources as local soil and sea spray sources.

Energetic and dynamic analysis of transport of Na + and K + through a cyclic peptide nanotube in water and in lipid bilayers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Yeonho; Lee, Ji Hye; Hwang, Hoon

Potential of mean force (PMF) profiles and position-dependent diffusion coefficients of Na + and K + are calculated to elucidate the translocation of ions through a cyclic peptide nanotube, composed of 8 × cyclo[-(D-Leu-Trp) 4-] rings, in water and in hydrated DMPC bilayers. The PMF profiles and PMF decomposition analysis for the monovalent cations show that favorable interactions of the cations with the CPN as well as the lipid bilayer and dehydration free energy penalties are two major competing factors which determine the free energy surface for ion transport through CPNs both in water and lipid bilayers, and that themore » selectivity of CPNs to cations mainly arises from favorable interaction energies of cations with CPNs and lipid bilayers that are more dominant than the dehydration penalties. Calculations of the position-dependent diffusion coefficients and dynamic friction kernels of the cations indicate that the dehydration process along with the molecular rearrangements occurring outside the channel and the coupling of the ion motions with the chain-structured water movements inside the channel lead to decrease of the diffusion coefficients far away from the channel entrance and also reduced coefficients inside the channel. Here the PMF and diffusivity profiles for Na + and K + reveal that the energetics of ion transport through the CPN are governed by global interactions of ions with all the components in the system while the diffusivity of ions through the channel is mostly determined by local interactions of ions with the confined water molecules inside the channel. Comparison of Na + and K + ion distributions based on overdamped Brownian dynamics simulations based on the PMF and diffusivity profiles with the corresponding results from molecular dynamics shows good agreement, indicating accuracy of the Bayesian inference method for determining diffusion coefficients in this application. In addition this work shows that position-dependent diffusion

Energetic and dynamic analysis of transport of Na + and K + through a cyclic peptide nanotube in water and in lipid bilayers

DOE PAGES

Song, Yeonho; Lee, Ji Hye; Hwang, Hoon; ...

2016-11-04

Potential of mean force (PMF) profiles and position-dependent diffusion coefficients of Na + and K + are calculated to elucidate the translocation of ions through a cyclic peptide nanotube, composed of 8 × cyclo[-(D-Leu-Trp) 4-] rings, in water and in hydrated DMPC bilayers. The PMF profiles and PMF decomposition analysis for the monovalent cations show that favorable interactions of the cations with the CPN as well as the lipid bilayer and dehydration free energy penalties are two major competing factors which determine the free energy surface for ion transport through CPNs both in water and lipid bilayers, and that themore » selectivity of CPNs to cations mainly arises from favorable interaction energies of cations with CPNs and lipid bilayers that are more dominant than the dehydration penalties. Calculations of the position-dependent diffusion coefficients and dynamic friction kernels of the cations indicate that the dehydration process along with the molecular rearrangements occurring outside the channel and the coupling of the ion motions with the chain-structured water movements inside the channel lead to decrease of the diffusion coefficients far away from the channel entrance and also reduced coefficients inside the channel. Here the PMF and diffusivity profiles for Na + and K + reveal that the energetics of ion transport through the CPN are governed by global interactions of ions with all the components in the system while the diffusivity of ions through the channel is mostly determined by local interactions of ions with the confined water molecules inside the channel. Comparison of Na + and K + ion distributions based on overdamped Brownian dynamics simulations based on the PMF and diffusivity profiles with the corresponding results from molecular dynamics shows good agreement, indicating accuracy of the Bayesian inference method for determining diffusion coefficients in this application. In addition this work shows that position-dependent diffusion

Analysis of the variation of the 0°C isothermal altitude during rainfall events

NASA Astrophysics Data System (ADS)

Zeimetz, Fränz; Garcìa, Javier; Schaefli, Bettina; Schleiss, Anton J.

2016-04-01

In numerous countries of the world (USA, Canada, Sweden, Switzerland,…), the dam safety verifications for extreme floods are realized by referring to the so called Probable Maximum Flood (PMF). According to the World Meteorological Organization (WMO), this PMF is determined based on the PMP (Probable Maximum Precipitation). The PMF estimation is performed with a hydrological simulation model by routing the PMP. The PMP-PMF simulation is normally event based; therefore, if no further information is known, the simulation needs assumptions concerning the initial soil conditions such as saturation or snow cover. In addition, temperature series are also of interest for the PMP-PMF simulations. Temperature values can not only be deduced from temperature measurement but also using the temperature gradient method, the 0°C isothermal altitude can lead to temperature estimations on the ground. For practitioners, the usage of the isothermal altitude for referring to temperature is convenient and simpler because one value can give information over a large region under the assumption of a certain temperature gradient. The analysis of the evolution of the 0°C isothermal altitude during rainfall events is aimed here and based on meteorological soundings from the two sounding stations Payerne (CH) and Milan (I). Furthermore, hourly rainfall and temperature data are available from 110 pluviometers spread over the Swiss territory. The analysis of the evolution of the 0°C isothermal altitude is undertaken for different precipitation durations based on the meteorological measurements mentioned above. The results show that on average, the isothermal altitude tends to decrease during the rainfall events and that a correlation between the duration of the altitude loss and the duration of the rainfall exists. A significant difference in altitude loss is appearing when the soundings from Payerne and Milan are compared.

Hourly elemental concentrations in PM2.5 aerosols sampled simultaneously at urban background and road site during SAPUSS - diurnal variations and PMF receptor modelling

NASA Astrophysics Data System (ADS)

Dall'Osto, M.; Querol, X.; Amato, F.; Karanasiou, A.; Lucarelli, F.; Nava, S.; Calzolai, G.; Chiari, M.

2013-04-01

Hourly-resolved aerosol chemical speciation data can be a highly powerful tool to determine the source origin of atmospheric pollutants in urban environments. Aerosol mass concentrations of seventeen elements (Na, Mg, Al, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Sr and Pb) were obtained by time (1 h) and size (PM2.5 particulate matter < 2.5 μm) resolved aerosol samples analysed by Particle Induced X-ray Emission (PIXE) measurements. In the Marie Curie European Union framework of SAPUSS (Solving Aerosol Problems by Using Synergistic Strategies), the approach used is the simultaneous sampling at two monitoring sites in Barcelona (Spain) during September-October 2010: an urban background site (UB) and a street canyon traffic road site (RS). Elements related to primary non-exhaust traffic emission (Fe, Cu), dust resuspension (Ca) and anthropogenic Cl were found enhanced at the RS, whereas industrial related trace metals (Zn, Pb, Mn) were found at higher concentrations at the more ventilated UB site. When receptor modelling was performed with positive matrix factorization (PMF), nine different aerosol sources were identified at both sites: three types of regional aerosols (regional sulphate (S) - 27%, biomass burning (K) - 5%, sea salt (Na-Mg) - 17%), three types of dust aerosols (soil dust (Al-Ti) - 17%, urban crustal dust (Ca) - 6%, and primary traffic non-exhaust brake dust (Fe-Cu) - 7%), and three types of industrial aerosol plumes-like events (shipping oil combustion (V-Ni) - 17%, industrial smelters (Zn-Mn) - 3%, and industrial combustion (Pb-Cl) - 5%, percentages presented are average source contributions to the total elemental mass measured). The validity of the PMF solution of the PIXE data is supported by very good correlations with external single particle mass spectrometry measurements. Some important conclusions can be drawn about the PM2.5 mass fraction simultaneously measured at the UB and RS sites: (1) the regional aerosol sources impact both

miRNA-mRNA integrative analysis in primary myelofibrosis CD34+ cells: role of miR-155/JARID2 axis in abnormal megakaryopoiesis

PubMed Central

Norfo, Ruggiero; Zini, Roberta; Pennucci, Valentina; Bianchi, Elisa; Salati, Simona; Guglielmelli, Paola; Bogani, Costanza; Fanelli, Tiziana; Mannarelli, Carmela; Rosti, Vittorio; Pietra, Daniela; Salmoiraghi, Silvia; Bisognin, Andrea; Ruberti, Samantha; Rontauroli, Sebastiano; Sacchi, Giorgia; Prudente, Zelia; Barosi, Giovanni; Cazzola, Mario; Rambaldi, Alessandro; Bortoluzzi, Stefania; Ferrari, Sergio; Tagliafico, Enrico; Vannucchi, Alessandro M.

2014-01-01

Primary myelofibrosis (PMF) is a myeloproliferative neoplasm characterized by megakaryocyte (MK) hyperplasia, bone marrow fibrosis, and abnormal stem cell trafficking. PMF may be associated with somatic mutations in JAK2, MPL, or CALR. Previous studies have shown that abnormal MKs play a central role in the pathophysiology of PMF. In this work, we studied both gene and microRNA (miRNA) expression profiles in CD34+ cells from PMF patients. We identified several biomarkers and putative molecular targets such as FGR, LCN2, and OLFM4. By means of miRNA-gene expression integrative analysis, we found different regulatory networks involved in the dysregulation of transcriptional control and chromatin remodeling. In particular, we identified a network gathering several miRNAs with oncogenic potential (eg, miR-155-5p) and targeted genes whose abnormal function has been previously associated with myeloid neoplasms, including JARID2, NR4A3, CDC42, and HMGB3. Because the validation of miRNA-target interactions unveiled JARID2/miR-155-5p as the strongest relationship in the network, we studied the function of this axis in normal and PMF CD34+ cells. We showed that JARID2 downregulation mediated by miR-155-5p overexpression leads to increased in vitro formation of CD41+ MK precursors. These findings suggest that overexpression of miR-155-5p and the resulting downregulation of JARID2 may contribute to MK hyperplasia in PMF. PMID:25097177

SOURCE APPORTIONMENT OF PM 2.5 AND CARBON IN SEATTLE USING CHEMICAL MASS BALANCE AND POSITIVE MATRIX FACTORIZATION

EPA Science Inventory

Three years of PM2.5 speciated data were collected and chemically analyzed using the IMPROVE protocol at the Beacon Hill site in Seattle. The data were analyzed by the Chemical Mass Balance Version 8 (CMB8) and Positive Matrix Factorization (PMF) source apportionment models. T...

Comparing Multipollutant Emissions-Based Mobile Source Indicators to Other Single Pollutant and Multipollutant Indicators in Different Urban Areas

PubMed Central

Oakes, Michelle M.; Baxter, Lisa K.; Duvall, Rachelle M.; Madden, Meagan; Xie, Mingjie; Hannigan, Michael P.; Peel, Jennifer L.; Pachon, Jorge E.; Balachandran, Siv; Russell, Armistead; Long, Thomas C.

2014-01-01

A variety of single pollutant and multipollutant metrics can be used to represent exposure to traffic pollutant mixtures and evaluate their health effects. Integrated mobile source indicators (IMSIs) that combine air quality concentration and emissions data have recently been developed and evaluated using data from Atlanta, Georgia. IMSIs were found to track trends in traffic-related pollutants and have similar or stronger associations with health outcomes. In the current work, we apply IMSIs for gasoline, diesel and total (gasoline + diesel) vehicles to two other cities (Denver, Colorado and Houston, Texas) with different emissions profiles as well as to a different dataset from Atlanta. We compare spatial and temporal variability of IMSIs to single-pollutant indicators (carbon monoxide (CO), nitrogen oxides (NOx) and elemental carbon (EC)) and multipollutant source apportionment factors produced by Positive Matrix Factorization (PMF). Across cities, PMF-derived and IMSI gasoline metrics were most strongly correlated with CO (r = 0.31–0.98), while multipollutant diesel metrics were most strongly correlated with EC (r = 0.80–0.98). NOx correlations with PMF factors varied across cities (r = 0.29–0.67), while correlations with IMSIs were relatively consistent (r = 0.61–0.94). In general, single-pollutant metrics were more correlated with IMSIs (r = 0.58–0.98) than with PMF-derived factors (r = 0.07–0.99). A spatial analysis indicated that IMSIs were more strongly correlated (r > 0.7) between two sites in each city than single pollutant and PMF factors. These findings provide confidence that IMSIs provide a transferable, simple approach to estimate mobile source air pollution in cities with differing topography and source profiles using readily available data. PMID:25405595

Multi-criteria ranking and receptor modelling of airborne fine particles at three sites in the Pearl River Delta region of China.

PubMed

Friend, Adrian J; Ayoko, Godwin A; Guo, Hai

2011-01-15

The multi-criteria decision making methods, Preference Ranking Organization METHods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and the two-way Positive Matrix Factorization (PMF) receptor model were applied to airborne fine particle compositional data collected at three sites in Hong Kong during two monitoring campaigns held from November 2000 to October 2001 and November 2004 to October 2005. PROMETHEE/GAIA indicated that the three sites were worse during the later monitoring campaign, and that the order of the air quality at the sites during each campaign was: rural site>urban site>roadside site. The PMF analysis on the other hand, identified 6 common sources at all of the sites (diesel vehicle, fresh sea salt, secondary sulphate, soil, aged sea salt and oil combustion) which accounted for approximately 68.8±8.7% of the fine particle mass at the sites. In addition, road dust, gasoline vehicle, biomass burning, secondary nitrate, and metal processing were identified at some of the sites. Secondary sulphate was found to be the highest contributor to the fine particle mass at the rural and urban sites with vehicle emission as a high contributor to the roadside site. The PMF results are broadly similar to those obtained in a previous analysis by PCA/APCS. However, the PMF analysis resolved more factors at each site than the PCA/APCS. In addition, the study demonstrated that combined results from multi-criteria decision making analysis and receptor modelling can provide more detailed information that can be used to formulate the scientific basis for mitigating air pollution in the region. Copyright © 2010 Elsevier B.V. All rights reserved.

Enhancing non-refractory aerosol apportionment from an urban industrial site through receptor modeling of complete high time-resolution aerosol mass spectra

NASA Astrophysics Data System (ADS)

McGuire, M. L.; Chang, R. Y.-W.; Slowik, J. G.; Jeong, C.-H.; Healy, R. M.; Lu, G.; Mihele, C.; Abbatt, J. P. D.; Brook, J. R.; Evans, G. J.

2014-08-01

method would be even more useful for HR-ToF-AMS data, due to the ability to understand better the chemical nature of atypical factors from high-resolution mass spectra. Second, utilizing PMF to extract factors containing inorganic species allowed for the determination of the extent of neutralization, which could have implications for aerosol parameterization. Third, subtler differences in organic aerosol components were resolved through the incorporation of inorganic mass into the PMF matrix. The additional temporal features provided by the inorganic aerosol components allowed for the resolution of more types of oxygenated organic aerosol than could be reliably resolved from PMF of organics alone. Comparison of findings from the PMFFull MS and PMFOrg MS methods showed that for the Windsor airshed, the PMFFull MS method enabled additional conclusions to be drawn in terms of aerosol sources and chemical processes. While performing PMFOrg MS can provide important distinctions between types of organic aerosol, it is shown that including inorganic species in the PMF analysis can permit further apportionment of organics for unit mass resolution AMS mass spectra.

Enhancing non-refractory aerosol apportionment from an urban industrial site through receptor modelling of complete high time-resolution aerosol mass spectra

NASA Astrophysics Data System (ADS)

McGuire, M. L.; Chang, R. Y.-W.; Slowik, J. G.; Jeong, C.-H.; Healy, R. M.; Lu, G.; Mihele, C.; Abbatt, J. P. D.; Brook, J. R.; Evans, G. J.

2014-02-01

to better understand the chemical nature of atypical factors from high resolution mass spectra. Second, utilizing PMF to extract factors containing inorganic species allowed for the determination of extent of neutralization, which could have implications for aerosol parameterization. Third, subtler differences in organic aerosol components were resolved through the incorporation of inorganic mass into the PMF matrix. The additional temporal features provided by the inorganic aerosol components allowed for the resolution of more types of oxygenated organic aerosol than could be reliably resolved from PMF of organics alone. Comparison of findings from the PMFFull MS and PMFOrg MS methods showed that for the Windsor airshed, the PMFFull MS method enabled additional conclusions to be drawn in terms of aerosol sources and chemical processes. While performing PMFOrg MS can provide important distinctions between types of organic aerosol, it is shown that including inorganic species in the PMF analysis can permit further apportionment of organics for unit mass resolution AMS mass spectra.

The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

NASA Astrophysics Data System (ADS)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Thrombosis in essential thrombocytemia and early/prefibrotic primary myelofibrosis: the role of the WHO histological diagnosis.

PubMed

Rupoli, Serena; Goteri, Gaia; Picardi, Paola; Micucci, Giorgia; Canafoglia, Lucia; Scortechini, Anna Rita; Federici, Irene; Giantomassi, Federica; Da Lio, Lidia; Zizzi, Antonio; Honorati, Elisa; Leoni, Pietro

2015-04-16

Vascular events represent the most frequent complications of thrombocytemias. We aimed to evaluate their risk in the WHO histologic categories of Essential Thrombocytemia (ET) and early Primary Myelofibrosis (PMF). From our clinical database of 283 thrombocytemic patients, we selected those with available bone marrow histology performed before any treatment, at or within 1 year from diagnosis, and reclassified the 131 cases as true ET or early PMF, with or without fibrosis, according to the WHO histological criteria. Vaso-occlusive events at diagnosis and in the follow-up were compared in the WHO-groups. Histologic review reclassified 61 cases as ET and 72 cases as early PMF (26 prefibrotic and 42 with grade 1 or 2 fibrosis). Compared to ET, early PMF showed a significant higher rate of thrombosis both in the past history (22% vs 8%) and at diagnosis (15.2% vs 1.6%), and an increased leukocyte count (8389 vs 7500/mmc). Venous thromboses (mainly atypical) were relatively more common in PMF than in ET. Patients with prefibrotic PMF, although younger, showed a significant higher 15-year risk of developing thrombosis (48% vs 16% in fibrotic PMF and 17% in ET). At multivariate analysis, age and WHO histology were both independent risk-factors for thrombosis during follow-up; patients >60 yr-old or with prefibrotic PMF showed a significantly higher risk at 20 years than patients <60 yr-old with ET or fibrotic PMF (47% vs 4%, p = 0.005). Our study support the importance of WHO histologic categories in the thrombotic risk stratification of patients with thrombocytemias. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/2020211863144412 .

Drug-disease association and drug-repositioning predictions in complex diseases using causal inference-probabilistic matrix factorization.

PubMed

Yang, Jihong; Li, Zheng; Fan, Xiaohui; Cheng, Yiyu

2014-09-22

The high incidence of complex diseases has become a worldwide threat to human health. Multiple targets and pathways are perturbed during the pathological process of complex diseases. Systematic investigation of complex relationship between drugs and diseases is necessary for new association discovery and drug repurposing. For this purpose, three causal networks were constructed herein for cardiovascular diseases, diabetes mellitus, and neoplasms, respectively. A causal inference-probabilistic matrix factorization (CI-PMF) approach was proposed to predict and classify drug-disease associations, and further used for drug-repositioning predictions. First, multilevel systematic relations between drugs and diseases were integrated from heterogeneous databases to construct causal networks connecting drug-target-pathway-gene-disease. Then, the association scores between drugs and diseases were assessed by evaluating a drug's effects on multiple targets and pathways. Furthermore, PMF models were learned based on known interactions, and associations were then classified into three types by trained models. Finally, therapeutic associations were predicted based upon the ranking of association scores and predicted association types. In terms of drug-disease association prediction, modified causal inference included in CI-PMF outperformed existing causal inference with a higher AUC (area under receiver operating characteristic curve) score and greater precision. Moreover, CI-PMF performed better than single modified causal inference in predicting therapeutic drug-disease associations. In the top 30% of predicted associations, 58.6% (136/232), 50.8% (31/61), and 39.8% (140/352) hit known therapeutic associations, while precisions obtained by the latter were only 10.2% (231/2264), 8.8% (36/411), and 9.7% (189/1948). Clinical verifications were further conducted for the top 100 newly predicted therapeutic associations. As a result, 21, 12, and 32 associations have been studied and

Apportionment of urban aerosol sources in Cork (Ireland) by synergistic measurement techniques.

PubMed

Dall'Osto, Manuel; Hellebust, Stig; Healy, Robert M; O'Connor, Ian P; Kourtchev, Ivan; Sodeau, John R; Ovadnevaite, Jurgita; Ceburnis, Darius; O'Dowd, Colin D; Wenger, John C

2014-09-15

The sources of ambient fine particulate matter (PM2.5) during wintertime at a background urban location in Cork city (Ireland) have been determined. Aerosol chemical analyses were performed by multiple techniques including on-line high resolution aerosol time-of-flight mass spectrometry (Aerodyne HR-ToF-AMS), on-line single particle aerosol time-of-flight mass spectrometry (TSI ATOFMS), on-line elemental carbon-organic carbon analysis (Sunset_EC-OC), and off-line gas chromatography/mass spectrometry and ion chromatography analysis of filter samples collected at 6-h resolution. Positive matrix factorization (PMF) has been carried out to better elucidate aerosol sources not clearly identified when analyzing results from individual aerosol techniques on their own. Two datasets have been considered: on-line measurements averaged over 2-h periods, and both on-line and off-line measurements averaged over 6-h periods. Five aerosol sources were identified by PMF in both datasets, with excellent agreement between the two solutions: (1) regional domestic solid fuel burning--"DSF_Regional," 24-27%; (2) local urban domestic solid fuel burning--"DSF_Urban," 22-23%; (3) road vehicle emissions--"Traffic," 15-20%; (4) secondary aerosols from regional anthropogenic sources--"SA_Regional" 9-13%; and (5) secondary aged/processed aerosols related to urban anthropogenic sources--"SA_Urban," 21-26%. The results indicate that, despite regulations for restricting the use of smoky fuels, solid fuel burning is the major source (46-50%) of PM2.5 in wintertime in Cork, and also likely other areas of Ireland. Whilst wood combustion is strongly associated with OC and EC, it was found that peat and coal combustion is linked mainly with OC and the aerosol from these latter sources appears to be more volatile than that produced by wood combustion. Ship emissions from the nearby port were found to be mixed with the SA_Regional factor. The PMF analysis allowed us to link the AMS cooking organic

Identification of the sources of PM10 in a subway tunnel using positive matrix factorization.

PubMed

Park, Duckshin; Lee, Taejeong; Hwang, Doyeon; Jung, Wonseok; Lee, Yongil; Cho, KiChul; Kim, Dongsool; Lees, Kiyoung

2014-12-01

The level of particulate matter of less than 10 μm diameter (PM10) at subway platforms can be significantly reduced by installing a platform screen-door system. However, both workers and passengers might be exposed to higher PM10 levels while the cars are within the tunnel because it is a more confined environment. This study determined the PM10 levels in a subway tunnel, and identified the sources of PM10 using elemental analysis and receptor modeling. Forty-four PM10 samples were collected in the tunnel between the Gireum and Mia stations on Line 4 in metropolitan Seoul and analyzed using inductively coupled plasma-atomic emission spectrometry and ion chromatography. The major PM10 sources were identified using positive matrix factorization (PMF). The average PM10 concentration in the tunnels was 200.8 ± 22.0 μg/m3. Elemental analysis indicated that the PM10 consisted of 40.4% inorganic species, 9.1% anions, 4.9% cations, and 45.6% other materials. Iron was the most abundant element, with an average concentration of 72.5 ± 10.4 μg/m3. The PM10 sources characterized by PMF included rail, wheel, and brake wear (59.6%), soil combustion (17.0%), secondary aerosols (10.0%), electric cable wear (8.1%), and soil and road dust (5.4%). Internal sources comprising rail, wheel, brake, and electric cable wear made the greatest contribution to the PM10 (67.7%) in tunnel air. Implications: With installation of a platform screen door, PM10 levels in subway tunnels were higher than those on platforms. Tunnel PM10 levels exceeded 150 µg/m3 of the Korean standard for subway platform. Elemental analysis of PM10 in a tunnel showed that Fe was the most abundant element. Five PM10 sources in tunnel were identified by positive matrix factorization. Railroad-related sources contributed 68% of PM10 in the subway tunnel.

A data-driven network model of primary myelofibrosis: transcriptional and post-transcriptional alterations in CD34+ cells.

PubMed

Calura, E; Pizzini, S; Bisognin, A; Coppe, A; Sales, G; Gaffo, E; Fanelli, T; Mannarelli, C; Zini, R; Norfo, R; Pennucci, V; Manfredini, R; Romualdi, C; Guglielmelli, P; Vannucchi, A M; Bortoluzzi, S

2016-06-24

microRNAs (miRNAs) are relevant in the pathogenesis of primary myelofibrosis (PMF) but our understanding is limited to specific target genes and the overall systemic scenario islacking. By both knowledge-based and ab initio approaches for comparative analysis of CD34+ cells of PMF patients and healthy controls, we identified the deregulated pathways involving miRNAs and genes and new transcriptional and post-transcriptional regulatory circuits in PMF cells. These converge in a unique and integrated cellular process, in which the role of specific miRNAs is to wire, co-regulate and allow a fine crosstalk between the involved processes. The PMF pathway includes Akt signaling, linked to Rho GTPases, CDC42, PLD2, PTEN crosstalk with the hypoxia response and Calcium-linked cellular processes connected to cyclic AMP signaling. Nested on the depicted transcriptional scenario, predicted circuits are reported, opening new hypotheses. Links between miRNAs (miR-106a-5p, miR-20b-5p, miR-20a-5p, miR-17-5p, miR-19b-3p and let-7d-5p) and key transcription factors (MYCN, ATF, CEBPA, REL, IRF and FOXJ2) and their common target genes tantalizingly suggest new path to approach the disease. The study provides a global overview of transcriptional and post-transcriptional deregulations in PMF, and, unifying consolidated and predicted data, could be helpful to identify new combinatorial therapeutic strategy. Interactive PMF network model: http://compgen.bio.unipd.it/pmf-net/.

A technique for rapid source apportionment applied to ambient organic aerosol measurements from a thermal desorption aerosol gas chromatograph (TAG)

DOE PAGES

Zhang, Yaping; Williams, Brent J.; Goldstein, Allen H.; ...

2016-11-25

Here, we present a rapid method for apportioning the sources of atmospheric organic aerosol composition measured by gas chromatography–mass spectrometry methods. Here, we specifically apply this new analysis method to data acquired on a thermal desorption aerosol gas chromatograph (TAG) system. Gas chromatograms are divided by retention time into evenly spaced bins, within which the mass spectra are summed. A previous chromatogram binning method was introduced for the purpose of chromatogram structure deconvolution (e.g., major compound classes) (Zhang et al., 2014). Here we extend the method development for the specific purpose of determining aerosol samples' sources. Chromatogram bins are arrangedmore » into an input data matrix for positive matrix factorization (PMF), where the sample number is the row dimension and the mass-spectra-resolved eluting time intervals (bins) are the column dimension. Then two-dimensional PMF can effectively do three-dimensional factorization on the three-dimensional TAG mass spectra data. The retention time shift of the chromatogram is corrected by applying the median values of the different peaks' shifts. Bin width affects chemical resolution but does not affect PMF retrieval of the sources' time variations for low-factor solutions. A bin width smaller than the maximum retention shift among all samples requires retention time shift correction. A six-factor PMF comparison among aerosol mass spectrometry (AMS), TAG binning, and conventional TAG compound integration methods shows that the TAG binning method performs similarly to the integration method. However, the new binning method incorporates the entirety of the data set and requires significantly less pre-processing of the data than conventional single compound identification and integration. In addition, while a fraction of the most oxygenated aerosol does not elute through an underivatized TAG analysis, the TAG binning method does have the ability to achieve molecular level

A technique for rapid source apportionment applied to ambient organic aerosol measurements from a thermal desorption aerosol gas chromatograph (TAG)

NASA Astrophysics Data System (ADS)

Zhang, Yaping; Williams, Brent J.; Goldstein, Allen H.; Docherty, Kenneth S.; Jimenez, Jose L.

2016-11-01

We present a rapid method for apportioning the sources of atmospheric organic aerosol composition measured by gas chromatography-mass spectrometry methods. Here, we specifically apply this new analysis method to data acquired on a thermal desorption aerosol gas chromatograph (TAG) system. Gas chromatograms are divided by retention time into evenly spaced bins, within which the mass spectra are summed. A previous chromatogram binning method was introduced for the purpose of chromatogram structure deconvolution (e.g., major compound classes) (Zhang et al., 2014). Here we extend the method development for the specific purpose of determining aerosol samples' sources. Chromatogram bins are arranged into an input data matrix for positive matrix factorization (PMF), where the sample number is the row dimension and the mass-spectra-resolved eluting time intervals (bins) are the column dimension. Then two-dimensional PMF can effectively do three-dimensional factorization on the three-dimensional TAG mass spectra data. The retention time shift of the chromatogram is corrected by applying the median values of the different peaks' shifts. Bin width affects chemical resolution but does not affect PMF retrieval of the sources' time variations for low-factor solutions. A bin width smaller than the maximum retention shift among all samples requires retention time shift correction. A six-factor PMF comparison among aerosol mass spectrometry (AMS), TAG binning, and conventional TAG compound integration methods shows that the TAG binning method performs similarly to the integration method. However, the new binning method incorporates the entirety of the data set and requires significantly less pre-processing of the data than conventional single compound identification and integration. In addition, while a fraction of the most oxygenated aerosol does not elute through an underivatized TAG analysis, the TAG binning method does have the ability to achieve molecular level resolution on

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yaping; Williams, Brent J.; Goldstein, Allen H.

Here, we present a rapid method for apportioning the sources of atmospheric organic aerosol composition measured by gas chromatography–mass spectrometry methods. Here, we specifically apply this new analysis method to data acquired on a thermal desorption aerosol gas chromatograph (TAG) system. Gas chromatograms are divided by retention time into evenly spaced bins, within which the mass spectra are summed. A previous chromatogram binning method was introduced for the purpose of chromatogram structure deconvolution (e.g., major compound classes) (Zhang et al., 2014). Here we extend the method development for the specific purpose of determining aerosol samples' sources. Chromatogram bins are arrangedmore » into an input data matrix for positive matrix factorization (PMF), where the sample number is the row dimension and the mass-spectra-resolved eluting time intervals (bins) are the column dimension. Then two-dimensional PMF can effectively do three-dimensional factorization on the three-dimensional TAG mass spectra data. The retention time shift of the chromatogram is corrected by applying the median values of the different peaks' shifts. Bin width affects chemical resolution but does not affect PMF retrieval of the sources' time variations for low-factor solutions. A bin width smaller than the maximum retention shift among all samples requires retention time shift correction. A six-factor PMF comparison among aerosol mass spectrometry (AMS), TAG binning, and conventional TAG compound integration methods shows that the TAG binning method performs similarly to the integration method. However, the new binning method incorporates the entirety of the data set and requires significantly less pre-processing of the data than conventional single compound identification and integration. In addition, while a fraction of the most oxygenated aerosol does not elute through an underivatized TAG analysis, the TAG binning method does have the ability to achieve molecular level

Factor Analysis via Components Analysis

ERIC Educational Resources Information Center

Bentler, Peter M.; de Leeuw, Jan

2011-01-01

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…

Validated reversed phase LC method for quantitative analysis of polymethoxyflavones in citrus peel extracts.

PubMed

Wang, Zhenyu; Li, Shiming; Ferguson, Stephen; Goodnow, Robert; Ho, Chi-Tang

2008-01-01

Polymethoxyflavones (PMFs), which exist exclusively in the citrus genus, have biological activities including anti-inflammatory, anticarcinogenic, and antiatherogenic properties. A validated RPLC method was developed for quantitative analysis of six major PMFs, namely nobiletin, tangeretin, sinensetin, 5,6,7,4'-tetramethoxyflavone, 3,5,6,7,3',4'-hexamethoxyflavone, and 3,5,6,7,8,3',4'-heptamethoxyflavone. The polar embedded LC stationary phase was able to fully resolve the six analogues. The developed method was fully validated in terms of linearity, accuracy, precision, sensitivity, and system suitability. The LOD of the method was calculated as 0.15 microg/mL and the recovery rate was between 97.0 and 105.1%. This analytical method was successfully applied to quantify the individual PMFs in four commercially available citrus peel extracts (CPEs). Each extract shows significant difference in the PMF composition and concentration. This method may provide a simple, rapid, and reliable tool to help reveal the correlation between the bioactivity of the PMF extracts and the individual PMF content.

Integrative analysis of copy number and gene expression data suggests novel pathogenetic mechanisms in primary myelofibrosis.

PubMed

Salati, Simona; Zini, Roberta; Nuzzo, Simona; Guglielmelli, Paola; Pennucci, Valentina; Prudente, Zelia; Ruberti, Samantha; Rontauroli, Sebastiano; Norfo, Ruggiero; Bianchi, Elisa; Bogani, Costanza; Rotunno, Giada; Fanelli, Tiziana; Mannarelli, Carmela; Rosti, Vittorio; Salmoiraghi, Silvia; Pietra, Daniela; Ferrari, Sergio; Barosi, Giovanni; Rambaldi, Alessandro; Cazzola, Mario; Bicciato, Silvio; Tagliafico, Enrico; Vannucchi, Alessandro M; Manfredini, Rossella

2016-04-01

Primary myelofibrosis (PMF) is a Myeloproliferative Neoplasm (MPN) characterized by megakaryocyte hyperplasia, progressive bone marrow fibrosis, extramedullary hematopoiesis and transformation to Acute Myeloid Leukemia (AML). A number of phenotypic driver (JAK2, CALR, MPL) and additional subclonal mutations have been described in PMF, pointing to a complex genomic landscape. To discover novel genomic lesions that can contribute to disease phenotype and/or development, gene expression and copy number signals were integrated and several genomic abnormalities leading to a concordant alteration in gene expression levels were identified. In particular, copy number gain in the polyamine oxidase (PAOX) gene locus was accompanied by a coordinated transcriptional up-regulation in PMF patients. PAOX inhibition resulted in rapid cell death of PMF progenitor cells, while sparing normal cells, suggesting that PAOX inhibition could represent a therapeutic strategy to selectively target PMF cells without affecting normal hematopoietic cells' survival. Moreover, copy number loss in the chromatin modifier HMGXB4 gene correlates with a concomitant transcriptional down-regulation in PMF patients. Interestingly, silencing of HMGXB4 induces megakaryocyte differentiation, while inhibiting erythroid development, in human hematopoietic stem/progenitor cells. These results highlight a previously un-reported, yet potentially interesting role of HMGXB4 in the hematopoietic system and suggest that genomic and transcriptional imbalances of HMGXB4 could contribute to the aberrant expansion of the megakaryocytic lineage that characterizes PMF patients. © 2015 UICC.

Source apportionment of exposures to volatile organic compounds. I. Evaluation of receptor models using simulated exposure data

NASA Astrophysics Data System (ADS)

Miller, Shelly L.; Anderson, Melissa J.; Daly, Eileen P.; Milford, Jana B.

Four receptor-oriented source apportionment models were evaluated by applying them to simulated personal exposure data for select volatile organic compounds (VOCs) that were generated by Monte Carlo sampling from known source contributions and profiles. The exposure sources modeled are environmental tobacco smoke, paint emissions, cleaning and/or pesticide products, gasoline vapors, automobile exhaust, and wastewater treatment plant emissions. The receptor models analyzed are chemical mass balance, principal component analysis/absolute principal component scores, positive matrix factorization (PMF), and graphical ratio analysis for composition estimates/source apportionment by factors with explicit restriction, incorporated in the UNMIX model. All models identified only the major contributors to total exposure concentrations. PMF extracted factor profiles that most closely represented the major sources used to generate the simulated data. None of the models were able to distinguish between sources with similar chemical profiles. Sources that contributed <5% to the average total VOC exposure were not identified.

Finite element analysis of the three different posterior malleolus fixation strategies in relation to different fracture sizes.

PubMed

Anwar, Adeel; Lv, Decheng; Zhao, Zhi; Zhang, Zhen; Lu, Ming; Nazir, Muhammad Umar; Qasim, Wasim

2017-04-01

Appropriate fixation method for the posterior malleolar fractures (PMF) according to the fracture size is still not clear. Aim of this study was to evaluate the outcomes of the different fixation methods used for fixation of PMF by finite element analysis (FEA) and to compare the effect of fixation constructs on the size of the fracture computationally. Three dimensional model of the tibia was reconstructed from computed tomography (CT) images. PMF of 30%, 40% and 50% fragment sizes were simulated through computational processing. Two antero-posterior (AP) lag screws, two postero-anterior (PA) lag screws and posterior buttress plate were analysed for three different fracture volumes. The simulated loads of 350N and 700N were applied to the proximal tibial end. Models were fixed distally in all degrees of freedom. In single limb standing condition, the posterior plate group produced the lowest relative displacement (RD) among all the groups (0.01, 0.03 and 0.06mm). Further nodal analysis of the highest RD fracture group showed a higher mean displacement of 4.77mm and 4.23mm in AP and PA lag screws model (p=0.000). The amounts of stress subjected to these implants, 134.36MPa and 140.75MPa were also significantly lower (p=0.000). There was a negative correlation (p=0.021) between implant stress and the displacement which signifies a less stable fixation using AP and PA lag screws. Progressively increasing fracture size demands more stable fixation construct because RD increases significantly. Posterior buttress plate produces superior stability and lowest RD in PMF models irrespective of the fragment size. Copyright © 2017 Elsevier Ltd. All rights reserved.

Insights into organic-aerosol sources via a novel laser-desorption/ionization mass spectrometry technique applied to one year of PM10 samples from nine sites in central Europe

NASA Astrophysics Data System (ADS)

Daellenbach, Kaspar R.; El-Haddad, Imad; Karvonen, Lassi; Vlachou, Athanasia; Corbin, Joel C.; Slowik, Jay G.; Heringa, Maarten F.; Bruns, Emily A.; Luedin, Samuel M.; Jaffrezo, Jean-Luc; Szidat, Sönke; Piazzalunga, Andrea; Gonzalez, Raquel; Fermo, Paola; Pflueger, Valentin; Vogel, Guido; Baltensperger, Urs; Prévôt, André S. H.

2018-02-01

We assess the benefits of offline laser-desorption/ionization mass spectrometry in understanding ambient particulate matter (PM) sources. The technique was optimized for measuring PM collected on quartz-fiber filters using silver nitrate as an internal standard for m/z calibration. This is the first application of this technique to samples collected at nine sites in central Europe throughout the entire year of 2013 (819 samples). Different PM sources were identified by positive matrix factorization (PMF) including also concomitant measurements (such as NOx, levoglucosan, and temperature). By comparison to reference mass spectral signatures from laboratory wood burning experiments as well as samples from a traffic tunnel, three biomass burning factors and two traffic factors were identified. The wood burning factors could be linked to the burning conditions; the factors related to inefficient burns had a larger impact on air quality in southern Alpine valleys than in northern Switzerland. The traffic factors were identified as primary tailpipe exhaust and most possibly aged/secondary traffic emissions. The latter attribution was supported by radiocarbon analyses of both the organic and elemental carbon. Besides these sources, factors related to secondary organic aerosol were also separated. The contribution of the wood burning emissions based on LDI-PMF (laser-desorption/ionization PMF) correlates well with that based on AMS-PMF (aerosol mass spectrometer PMF) analyses, while the comparison between the two techniques for other components is more complex.

Liquid-liquid extraction of uranyl by TBP: the TBP and ions models and related interfacial features revisited by MD and PMF simulations.

PubMed

Benay, G; Wipff, G

2014-03-20

We report a molecular dynamics (MD) study of biphasic systems involved in the liquid-liquid extraction of uranyl nitrate by tri-n-butylphosphate (TBP) to hexane, from "pH neutral" or acidic (3 M nitric acid) aqueous solutions, to assess the model dependence of the surface activity and partitioning of TBP alone, of its UO2(NO3)2(TBP)2 complex, and of UO2(NO3)2 or UO2(2+) uncomplexed. For this purpose, we first compare several electrostatic representations of TBP with regards to its polarity and conformational properties, its interactions with H2O, HNO3, and UO2(NO3)2 species, its relative free energies of solvation in water or oil environments, the properties of the pure TBP liquid and of the pure-TBP/water interface. The free energies of transfer of TBP, UO2(NO3)2, UO2(2+), and the UO2(NO3)2(TBP)2 complex across the water/oil interface are then investigated by potential of mean force (PMF) calculations, comparing different TBP models and two charge models of uranyl nitrate. Describing uranyl and nitrate ions with integer charges (+2 and -1, respectively) is shown to exaggerate the hydrophilicity and surface activity of the UO2(NO3)2(TBP)2 complex. With more appropriate ESP charges, mimicking charge transfer and polarization effects in the UO2(NO3)2 moiety or in the whole complex, the latter is no more surface active. This feature is confirmed by MD, PMF, and mixing-demixing simulations with or without polarization. Furthermore, with ESP charges, pulling the UO2(NO3)2 species to the TBP phase affords the formation of UO2(NO3)2(TBP)2 at the interface, followed by its energetically favorable extraction. The neutral complexes should therefore not accumulate at the interface during the extraction process, but diffuse to the oil phase. A similar feature is found for an UO2(NO3)2(Amide)2 neutral complex with fatty amide extracting ligands, calling for further simulations and experimental studies (e.g., time evolution of the nonlinear spectroscopic signature and of surface

Periodic magnetic field as a polarized and focusing thermal neutron spectrometer and monochromator.

PubMed

Cremer, J T; Williams, D L; Fuller, M J; Gary, C K; Piestrup, M A; Pantell, R H; Feinstein, J; Flocchini, R G; Boussoufi, M; Egbert, H P; Kloh, M D; Walker, R B

2010-01-01

A novel periodic magnetic field (PMF) optic is shown to act as a prism, lens, and polarizer for neutrons and particles with a magnetic dipole moment. The PMF has a two-dimensional field in the axial direction of neutron propagation. The PMF alternating magnetic field polarity provides strong gradients that cause separation of neutrons by wavelength axially and by spin state transversely. The spin-up neutrons exit the PMF with their magnetic spins aligned parallel to the PMF magnetic field, and are deflected upward and line focus at a fixed vertical height, proportional to the PMF period, at a downstream focal distance that increases with neutron energy. The PMF has no attenuation by absorption or scatter, as with material prisms or crystal monochromators. Embodiments of the PMF include neutron spectrometer or monochromator, and applications include neutron small angle scattering, crystallography, residual stress analysis, cross section measurements, and reflectometry. Presented are theory, experimental results, computer simulation, applications of the PMF, and comparison of its performance to Stern-Gerlach gradient devices and compound material and magnetic refractive prisms.

Periodic magnetic field as a polarized and focusing thermal neutron spectrometer and monochromator

PubMed Central

Cremer, J. T.; Williams, D. L.; Fuller, M. J.; Gary, C. K.; Piestrup, M. A.; Pantell, R. H.; Feinstein, J.; Flocchini, R. G.; Boussoufi, M.; Egbert, H. P.; Kloh, M. D.; Walker, R. B.

2010-01-01

A novel periodic magnetic field (PMF) optic is shown to act as a prism, lens, and polarizer for neutrons and particles with a magnetic dipole moment. The PMF has a two-dimensional field in the axial direction of neutron propagation. The PMF alternating magnetic field polarity provides strong gradients that cause separation of neutrons by wavelength axially and by spin state transversely. The spin-up neutrons exit the PMF with their magnetic spins aligned parallel to the PMF magnetic field, and are deflected upward and line focus at a fixed vertical height, proportional to the PMF period, at a downstream focal distance that increases with neutron energy. The PMF has no attenuation by absorption or scatter, as with material prisms or crystal monochromators. Embodiments of the PMF include neutron spectrometer or monochromator, and applications include neutron small angle scattering, crystallography, residual stress analysis, cross section measurements, and reflectometry. Presented are theory, experimental results, computer simulation, applications of the PMF, and comparison of its performance to Stern–Gerlach gradient devices and compound material and magnetic refractive prisms. PMID:20113108

Source apportionment of aerosol particles at a European air pollution hot spot using particle number size distributions and chemical composition.

PubMed

Leoni, Cecilia; Pokorná, Petra; Hovorka, Jan; Masiol, Mauro; Topinka, Jan; Zhao, Yongjing; Křůmal, Kamil; Cliff, Steven; Mikuška, Pavel; Hopke, Philip K

2018-03-01

Ostrava in the Moravian-Silesian region (Czech Republic) is a European air pollution hot spot for airborne particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and ultrafine particles (UFPs). Air pollution source apportionment is essential for implementation of successful abatement strategies. UFPs or nanoparticles of diameter <100 nm exhibit the highest deposition efficiency in human lungs. To permit apportionment of PM sources at the hot-spot including nanoparticles, Positive Matrix Factorization (PMF) was applied to highly time resolved particle number size distributions (NSD, 14 nm-10 μm) and PM 0.09-1.15 chemical composition. Diurnal patterns, meteorological variables, gaseous pollutants, organic markers, and associations between the NSD factors and chemical composition factors were used to identify the pollution sources. The PMF on the NSD reveals two factors in the ultrafine size range: industrial UFPs (28%, number mode diameter - NMD 45 nm), industrial/fresh road traffic nanoparticles (26%, NMD 26 nm); three factors in the accumulation size range: urban background (24%, NMD 93 nm), coal burning (14%, volume mode diameter - VMD 0.5 μm), regional pollution (3%, VMD 0.8 μm) and one factor in the coarse size range: industrial coarse particles/road dust (2%, VMD 5 μm). The PMF analysis of PM 0.09-1.15 revealed four factors: SIA/CC/BB (52%), road dust (18%), sinter/steel (16%), iron production (16%). The factors in the ultrafine size range resolved with NSD have a positive correlation with sinter/steel production and iron production factors resolved with chemical composition. Coal combustion factor resolved with NSD has moderate correlation with SIA/CC/BB factor. The organic markers homohopanes correlate with coal combustion and the levoglucosan correlates with urban background. The PMF applications to NSD and chemical composition datasets are complementary. PAHs in PM 1 were found to be associated with coal combustion factor. Copyright

Factor Analysis and Counseling Research

ERIC Educational Resources Information Center

Weiss, David J.

1970-01-01

Topics discussed include factor analysis versus cluster analysis, analysis of Q correlation matrices, ipsativity and factor analysis, and tests for the significance of a correlation matrix prior to application of factor analytic techniques. Techniques for factor extraction discussed include principal components, canonical factor analysis, alpha…

Source apportionment revisited for long-term measurements of fine aerosol trace elements at two locations in southern Norway

NASA Astrophysics Data System (ADS)

Maenhaut, Willy

2018-02-01

Five-year-long (1991-1996) aerosol trace element data sets for the fine (PM2) size fraction from the sites of Birkenes and Skreådalen in southern Norway were reanalysed by US EPA positive matrix factorization PMF5 in order to assess the sources and their contribution to the PM2 aerosol. The data sets contained the concentrations of the particulate mass (PM), black carbon (BC) and 21 elements in over 700 samples for each of the two sites. The PM was obtained from weighing with a microbalance and BC was determined with a light reflectance technique. The data for the elements were obtained by a combination of particle-induced X-ray emission and instrumental neutron activation analysis. Eight source factors were retained for each site, i.e., (i) secondary sulfate, which accounted for around 40% of the average measured PM2 mass, (ii) wood burning, with BC, K, Zn and As, which accounted for about 17%, (iii) an iodine factor (with also Br and Se), which is probably related to a marine biogenic source and was responsible for about 6.5%, (iv) aged sea salt with Na, Mg, Cl and Ca, but heavily depleted in Cl; (v) a crustal factor containing Al, Si, Ca, Ti and Fe; (vi) a heavy oil burning factor with V and Ni in a ratio of 3-4; (vii) a general pollution factor (with Cu, Zn, As, Se, Sb and Pb), and (viii) an almost pure manganese factor, which is attributed to Mn and FeMn industries in southern Norway. The results were substantially different from those of an earlier PMF analysis, in which use was made of PMF2.

PM2.5 pollution from household solid fuel burning practices in Central India: 2. Application of receptor models for source apportionment.

PubMed

Matawle, Jeevan Lal; Pervez, Shamsh; Deb, Manas Kanti; Shrivastava, Anjali; Tiwari, Suresh

2018-02-01

USEPA's UNMIX, positive matrix factorization (PMF) and effective variance-chemical mass balance (EV-CMB) receptor models were applied to chemically speciated profiles of 125 indoor PM 2.5 measurements, sampled longitudinally during 2012-2013 in low-income group households of Central India which uses solid fuels for cooking practices. Three step source apportionment studies were carried out to generate more confident source characterization. Firstly, UNMIX6.0 extracted initial number of source factors, which were used to execute PMF5.0 to extract source-factor profiles in second step. Finally, factor analog locally derived source profiles were supplemented to EV-CMB8.2 with indoor receptor PM 2.5 chemical profile to evaluate source contribution estimates (SCEs). The results of combined use of three receptor models clearly describe that UNMIX and PMF are useful tool to extract types of source categories within small receptor dataset and EV-CMB can pick those locally derived source profiles for source apportionment which are analog to PMF-extracted source categories. The source apportionment results have also shown three fold higher relative contribution of solid fuel burning emissions to indoor PM 2.5 compared to those measurements reported for normal households with LPG stoves. The previously reported influential source marker species were found to be comparatively similar to those extracted from PMF fingerprint plots. The comparison between PMF and CMB SCEs results were also found to be qualitatively similar. The performance fit measures of all three receptor models were cross-verified and validated and support each other to gain confidence in source apportionment results.

Source apportionment of PM2.5 at the Lin'an regional background site in China with three receptor models

NASA Astrophysics Data System (ADS)

Deng, Junjun; Zhang, Yanru; Qiu, Yuqing; Zhang, Hongliang; Du, Wenjiao; Xu, Lingling; Hong, Youwei; Chen, Yanting; Chen, Jinsheng

2018-04-01

Source apportionment of fine particulate matter (PM2.5) were conducted at the Lin'an Regional Atmospheric Background Station (LA) in the Yangtze River Delta (YRD) region in China from July 2014 to April 2015 with three receptor models including principal component analysis combining multiple linear regression (PCA-MLR), UNMIX and Positive Matrix Factorization (PMF). The model performance, source identification and source contribution of the three models were analyzed and inter-compared. Source apportionment of PM2.5 was also conducted with the receptor models. Good correlations between the reconstructed and measured concentrations of PM2.5 and its major chemical species were obtained for all models. PMF resolved almost all masses of PM2.5, while PCA-MLR and UNMIX explained about 80%. Five, four and seven sources were identified by PCA-MLR, UNMIX and PMF, respectively. Combustion, secondary source, marine source, dust and industrial activities were identified by all the three receptor models. Combustion source and secondary source were the major sources, and totally contributed over 60% to PM2.5. The PMF model had a better performance on separating the different combustion sources. These findings improve the understanding of PM2.5 sources in background region.

Spinal NMDA receptor activation constrains inactivity-induced phrenic motor facilitation in Charles River Sprague-Dawley rats

PubMed Central

Streeter, K. A.

2014-01-01

Reduced spinal synaptic inputs to phrenic motor neurons elicit a unique form of spinal plasticity known as inactivity-induced phrenic motor facilitation (iPMF). iPMF requires tumor necrosis factor-α (TNF-α) and atypical protein kinase C (aPKC) activity within spinal segments containing the phrenic motor nucleus to stabilize early, transient increases in phrenic burst amplitude into long-lasting iPMF. Here we tested the hypothesis that spinal N-methyl-d-aspartate receptor (NMDAR) activation constrains long-lasting iPMF in some rat substrains. Phrenic motor output was recorded in anesthetized, ventilated Harlan (HSD) and Charles River (CRSD) Sprague-Dawley rats exposed to a 30-min central neural apnea. HSD rats expressed a robust, long-lasting (>60 min) increase in phrenic burst amplitude (i.e., long-lasting iPMF) when respiratory neural activity was restored. By contrast, CRSD rats expressed an attenuated, transient (∼15 min) iPMF. Spinal NMDAR inhibition with DL-2-amino-5-phosphonopentanoic acid (APV) before neural apnea or shortly (4 min) prior to the resumption of respiratory neural activity revealed long-lasting iPMF in CRSD rats that was phenotypically similar to that in HSD rats. By contrast, APV did not alter iPMF expression in HSD rats. Spinal TNF-α or aPKC inhibition impaired long-lasting iPMF enabled by NMDAR inhibition in CRSD rats, suggesting that similar mechanisms give rise to long-lasting iPMF in CRSD rats with NMDAR inhibition as those giving rise to long-lasting iPMF in HSD rats. These results suggest that NMDAR activation can impose constraints on TNF-α-induced aPKC activation after neural apnea, impairing stabilization of transient iPMF into long-lasting iPMF. These data may have important implications for understanding differential responses to reduced respiratory neural activity in a heterogeneous human population. PMID:25103979

Spinal TNFα is necessary for inactivity-induced phrenic motor facilitation

PubMed Central

Broytman, Oleg; Baertsch, Nathan A; Baker-Herman, Tracy L

2013-01-01

A prolonged reduction in central neural respiratory activity elicits a form of plasticity known as inactivity-induced phrenic motor facilitation (iPMF), a ‘rebound’ increase in phrenic burst amplitude apparent once respiratory neural activity is restored. iPMF requires atypical protein kinase C (aPKC) activity within spinal segments containing the phrenic motor nucleus to stabilize an early transient increase in phrenic burst amplitude and to form long-lasting iPMF following reduced respiratory neural activity. Upstream signal(s) leading to spinal aPKC activation are unknown. We tested the hypothesis that spinal tumour necrosis factor-α (TNFα) is necessary for iPMF via an aPKC-dependent mechanism. Anaesthetized, ventilated rats were exposed to a 30 min neural apnoea; upon resumption of respiratory neural activity, a prolonged increase in phrenic burst amplitude (42 ± 9% baseline; P < 0.05) was apparent, indicating long-lasting iPMF. Pretreatment with recombinant human soluble TNF receptor 1 (sTNFR1) in the intrathecal space at the level of the phrenic motor nucleus prior to neural apnoea blocked long-lasting iPMF (2 ± 8% baseline; P > 0.05). Intrathecal TNFα without neural apnoea was sufficient to elicit long-lasting phrenic motor facilitation (pMF; 62 ± 7% baseline; P < 0.05). Similar to iPMF, TNFα-induced pMF required spinal aPKC activity, as intrathecal delivery of a ζ-pseudosubstrate inhibitory peptide (PKCζ-PS) 35 min following intrathecal TNFα arrested TNFα-induced pMF (28 ± 8% baseline; P < 0.05). These data demonstrate that: (1) spinal TNFα is necessary for iPMF; and (2) spinal TNFα is sufficient to elicit pMF via a similar aPKC-dependent mechanism. These data are consistent with the hypothesis that reduced respiratory neural activity elicits iPMF via a TNFα-dependent increase in spinal aPKC activity. PMID:23878370

Source apportionment and pollution evaluation of heavy metals in water and sediments of Buriganga River, Bangladesh, using multivariate analysis and pollution evaluation indices.

PubMed

Bhuiyan, Mohammad Amir Hossain; Dampare, Samuel B; Islam, M A; Suzuki, Shigeyuki

2015-01-01

Concentrations of heavy metals in water and sediment samples of Buriganga River in the capital city Dhaka, Bangladesh, were studied to understand the level of heavy metals and their source apportionment. The results showed that the mean concentrations of heavy metals both in water and sediment samples were very high and, in most cases, exceeded the permissible limits recommended by the Bangladesh government and other international organizations. Significantly higher concentrations of Pb, Cr, Mn, Co, Ni, Cu, Zn, As, and Cd were found in sediment samples. However, average concentrations of metals both in water and sediment samples were above the effect range median. The heavy metal pollution index (HPI) and degree of contamination (Cd) yielded different results in water samples despite significant correlations between them. The heavy metal evaluation index (HEI) showed strong correlations with HPI and Cd and provided better assessment of pollution levels. The enrichment factor (EF) and geoaccumulation index (Igeo) showed the elevated value of Cr, Pb, and Cd in access of background values. The measured elements were subjected to positive matrix factorization (PMF) and examining correlations in order to explain the content, behavior, and source apportionment of metals. PMF resulted in a successful partitioning of variances into sources related to background geochemistry and contaminant influences. However, the PMF approach successfully demarcated the major sources of metals from tannery, paint, municipal sewage, textiles, and agricultural activities.

The dual effects of polar methanolic extract of Hypericum perforatum L. in bladder cancer cells

NASA Astrophysics Data System (ADS)

Nseyo, U. O.; Nseyo, O. U.; Shiverick, K. T.; Medrano, T.; Mejia, M.; Stavropoulos, N.; Tsimaris, I.; Skalkos, D.

2007-02-01

Introduction and background: We have reported on the polar methanolic fraction (PMF) of Hypericum Perforatum L as a novel photosensitizing agent for photodynamic therapy (PDT) and photodynamic diagnosis (PDD). PMF has been tested in human leukemic cells, HL-60 cells, cord blood hemopoietic progenitor cells, bladder cancers derived from metastatic lymph node (T-24) and primary papillary bladder lesion (RT-4). However, the mechanisms of the effects of PMF on these human cell lines have not been elucidated. We have investigated mechanisms of PMF + light versus PMF-alone (dark experiment) in T-24 human bladder cancer cells. Methods: PMF was prepared from an aerial herb of HPL which was brewed in methanol and extracted with ether and methanol. Stock solutions of PMF were made in DSMO and stored in dark conditions. PMF contains 0.57% hypericin and 2.52% hyperforin. The T24 cell line was obtained from American Type Culture Collection (ATCC). In PDT treatment, PMF (60μg/ml) was incubated with cells, which were excited with laser light (630nm) 24 hours later. Apoptosis was determined by DNA fragmentation/laddering assay. DNA isolation was performed according to the manufacture's instructions with the Kit (Oncogene Kit#AM41). Isolated DNA samples were separated by electrophoresis in 1.5% in agarose gels and bands were visualized by ethidium bromide labeling. The initial cell cycle analysis and phase distribution was by flow cytometry. DNA synthesis was measured by [3H] thymidine incorporation, and cell cycle regulatory proteins were assayed by Western immunoblot. Results: The results of the flow cytometry showed PMF +light induced significant (40%) apoptosis in T24 cells, whereas Light or PMF alone produced little apoptosis. The percentage of cells in G 0/G I phase was decreased by 25% and in G2/M phase by 38%. The main impact was observed on the S phase which was blocked by 78% from the specific photocytotoxic process. DNA laddering analysis showed that PMF (60�

A Regional Assessment of Marine Vessel PM2.5 Impacts in the U.S. Pacific Northwest Using a Receptor Based Source Apportionment Method

EPA Science Inventory

This work reports the results of a regional receptor-based source apportionment analysis using the Positive Matrix Factorization (PMF) model on chemically speciated PM2.5 data from 36 urban and rural monitoring sites within the U.S. Pacific Northwest. The approach taken is to mo...

Decreased spinal synaptic inputs to phrenic motor neurons elicit localized inactivity-induced phrenic motor facilitation

PubMed Central

Streeter, K.A.; Baker-Herman, T.L.

2014-01-01

Phrenic motor neurons receive rhythmic synaptic inputs throughout life. Since even brief disruption in phrenic neural activity is detrimental to life, on-going neural activity may play a key role in shaping phrenic motor output. To test the hypothesis that spinal mechanisms sense and respond to reduced phrenic activity, anesthetized, ventilated rats received micro-injections of procaine in the C2 ventrolateral funiculus (VLF) to transiently (~30 min) block axon conduction in bulbospinal axons from medullary respiratory neurons that innervate one phrenic motor pool; during procaine injections, contralateral phrenic neural activity was maintained. Once axon conduction resumed, a prolonged increase in phrenic burst amplitude was observed in the ipsilateral phrenic nerve, demonstrating inactivity-induced phrenic motor facilitation (iPMF). Inhibition of tumor necrosis factor alpha (TNFα) and atypical PKC (aPKC) activity in spinal segments containing the phrenic motor nucleus impaired ipsilateral iPMF, suggesting a key role for spinal TNFα and aPKC in iPMF following unilateral axon conduction block. A small phrenic burst amplitude facilitation was also observed contralateral to axon conduction block, indicating crossed spinal phrenic motor facilitation (csPMF). csPMF was independent of spinal TNFα and aPKC. Ipsilateral iPMF and csPMF following unilateral withdrawal of phrenic synaptic inputs were associated with proportional increases in phrenic responses to chemoreceptor stimulation (hypercapnia), suggesting iPMF and csPMF increase phrenic dynamic range. These data suggest that local, spinal mechanisms sense and respond to reduced synaptic inputs to phrenic motor neurons. We hypothesize that iPMF and csPMF may represent compensatory mechanisms that assure adequate motor output is maintained in a physiological system in which prolonged inactivity ends life. PMID:24681155

BTEX exposures in an area impacted by industrial and mobile sources: Source attribution and impact of averaging time.

PubMed

Presto, Albert A; Dallmann, Timothy R; Gu, Peishi; Rao, Unnati

2016-04-01

The impacts of emissions plumes from major industrial sources on black carbon (BC) and BTEX (benzene, toluene, ethyl benzene, xylene isomers) exposures in communities located >10 km from the industrial source areas were identified with a combination of stationary measurements, source identification using positive matrix factorization (PMF), and dispersion modeling. The industrial emissions create multihour plume events of BC and BTEX at the measurement sites. PMF source apportionment, along with wind patterns, indicates that the observed pollutant plumes are the result of transport of industrial emissions under conditions of low boundary layer height. PMF indicates that industrial emissions contribute >50% of outdoor exposures of BC and BTEX species at the receptor sites. Dispersion modeling of BTEX emissions from known industrial sources predicts numerous overnight plumes and overall qualitative agreement with PMF analysis, but predicts industrial impacts at the measurement sites a factor of 10 lower than PMF. Nonetheless, exposures associated with pollutant plumes occur mostly at night, when residents are expected to be home but are perhaps unaware of the elevated exposure. Averaging data samples over long times typical of public health interventions (e.g., weekly or biweekly passive sampling) misapportions the exposure, reducing the impact of industrial plumes at the expense of traffic emissions, because the longer samples cannot resolve subdaily plumes. Suggestions are made for ways for future distributed pollutant mapping or intervention studies to incorporate high time resolution tools to better understand the potential impacts of industrial plumes. Emissions from industrial or other stationary sources can dominate air toxics exposures in communities both near the source and in downwind areas in the form of multihour plume events. Common measurement strategies that use highly aggregated samples, such as weekly or biweekly averages, are insensitive to such

Using Horn's Parallel Analysis Method in Exploratory Factor Analysis for Determining the Number of Factors

ERIC Educational Resources Information Center

Çokluk, Ömay; Koçak, Duygu

2016-01-01

In this study, the number of factors obtained from parallel analysis, a method used for determining the number of factors in exploratory factor analysis, was compared to that of the factors obtained from eigenvalue and scree plot--two traditional methods for determining the number of factors--in terms of consistency. Parallel analysis is based on…

Potential of mean force analysis of the self-association of leucine-rich transmembrane α-helices: difference between atomistic and coarse-grained simulations.

PubMed

Nishizawa, Manami; Nishizawa, Kazuhisa

2014-08-21

Interaction of transmembrane (TM) proteins is important in many biological processes. Large-scale computational studies using coarse-grained (CG) simulations are becoming popular. However, most CG model parameters have not fully been calibrated with respect to lateral interactions of TM peptide segments. Here, we compare the potential of mean forces (PMFs) of dimerization of TM helices obtained using a MARTINI CG model and an atomistic (AT) Berger lipids-OPLS/AA model (AT(OPLS)). For helical, tryptophan-flanked, leucine-rich peptides (WL15 and WALP15) embedded in a parallel configuration in an octane slab, the AT(OPLS) PMF profiles showed a shallow minimum (with a depth of approximately 3 kJ/mol; i.e., a weak tendency to dimerize). A similar analysis using the CHARMM36 all-atom model (AT(CHARMM)) showed comparable results. In contrast, the CG analysis generally showed steep PMF curves with depths of approximately 16-22 kJ/mol, suggesting a stronger tendency to dimerize compared to the AT model. This CG > AT discrepancy in the propensity for dimerization was also seen for dilauroylphosphatidylcholine (DLPC)-embedded peptides. For a WL15 (and WALP15)/DLPC bilayer system, AT(OPLS) PMF showed a repulsive mean force for a wide range of interhelical distances, in contrast to the attractive forces observed in the octane system. The change from the octane slab to the DLPC bilayer also mitigated the dimerization propensity in the CG system. The dimerization energies of CG (AALALAA)3 peptides in DLPC and dioleoylphosphatidylcholine bilayers were in good agreement with previous experimental data. The lipid headgroup, but not the length of the lipid tails, was a key causative factor contributing to the differences between octane and DLPC. Furthermore, the CG model, but not the AT model, showed high sensitivity to changes in amino acid residues located near the lipid-water interface and hydrophobic mismatch between the peptides and membrane. These findings may help interpret CG

National Dam Inspection Program. Upper Pigeon Hill Dam. (NDI I.D. Number PA-00340, PennDER I.D. Number 67-5) Susquehanna River Basin, Gitts Run, York County, Pennsylvania. Phase I Inspection Report,

DTIC Science & Technology

1980-03-01

recommended guidelines, the Spillway Design Flood (SDF) ranges between the 1 /2-PMF (Probable Maximum Flood) and PMF. Since the dam is near the lower end of...overtopping. A breach analysis indicates that failure under 1 /2-PMF conditions would probably not lead to increased property damage or loss of life at...ii OVERVIEW PHOTOGRAPH ......... .................. V TABLE OF CONTENTS ......... ................... vi SECTION 1 - GENERAL INFORMATION

Determining the Number of Factors in P-Technique Factor Analysis

ERIC Educational Resources Information Center

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

Fine Particle Sources and Cardiorespiratory Morbidity: An Application of Chemical Mass Balance and Factor Analytical Source-Apportionment Methods

PubMed Central

Sarnat, Jeremy A.; Marmur, Amit; Klein, Mitchel; Kim, Eugene; Russell, Armistead G.; Sarnat, Stefanie E.; Mulholland, James A.; Hopke, Philip K.; Tolbert, Paige E.

2008-01-01

Background Interest in the health effects of particulate matter (PM) has focused on identifying sources of PM, including biomass burning, power plants, and gasoline and diesel emissions that may be associated with adverse health risks. Few epidemiologic studies, however, have included source-apportionment estimates in their examinations of PM health effects. We analyzed a time-series of chemically speciated PM measurements in Atlanta, Georgia, and conducted an epidemiologic analysis using data from three distinct source-apportionment methods. Objective The key objective of this analysis was to compare epidemiologic findings generated using both factor analysis and mass balance source-apportionment methods. Methods We analyzed data collected between November 1998 and December 2002 using positive-matrix factorization (PMF), modified chemical mass balance (CMB-LGO), and a tracer approach. Emergency department (ED) visits for a combined cardiovascular (CVD) and respiratory disease (RD) group were assessed as end points. We estimated the risk ratio (RR) associated with same day PM concentrations using Poisson generalized linear models. Results There were significant, positive associations between same-day PM2.5 (PM with aero-dynamic diameter ≤ 2.5 μm) concentrations attributed to mobile sources (RR range, 1.018–1.025) and biomass combustion, primarily prescribed forest burning and residential wood combustion, (RR range, 1.024–1.033) source categories and CVD-related ED visits. Associations between the source categories and RD visits were not significant for all models except sulfate-rich secondary PM2.5 (RR range, 1.012–1.020). Generally, the epidemiologic results were robust to the selection of source-apportionment method, with strong agreement between the RR estimates from the PMF and CMB-LGO models, as well as with results from models using single-species tracers as surrogates of the source-apportioned PM2.5 values. Conclusions Despite differences among the

A comparison of PCA and PMF models for source identification of fugitive methane emissions

NASA Astrophysics Data System (ADS)

Assan, Sabina; Baudic, Alexia; Bsaibes, Sandy; Gros, Valerie; Ciais, Philippe; Staufer, Johannes; Robinson, Rod; Vogel, Felix

2017-04-01

Methane (CH_4) is a greenhouse gas with a global warming potential 28-32 times that of carbon dioxide (CO_2) on a 100 year period, and even greater on shorter timescales [Etminan, et al., 2016, Allen, 2014]. Thus, despite its relatively short life time and smaller emission quantities compared to CO_2, CH4 emissions contribute to approximately 20{%} of today's anthropogenic greenhouse gas warming [Kirschke et al., 2013]. Major anthropogenic sources include livestock (enteric fermentation), oil and gas production and distribution, landfills, and wastewater emissions [EPA, 2011]. Especially in densely populated areas multiple CH4 sources can be found in close vicinity. Thus, when measuring CH4 emissions at local scales it is necessary to distinguish between different CH4 source categories to effectively quantify the contribution of each sector and aid the implementation of greenhouse gas reduction strategies. To this end, source apportionment models can be used to aid the interpretation of spatial and temporal patterns in order to identify and characterise emission sources. The focus of this study is to evaluate two common linear receptor models, namely Principle Component Analysis (PCA) and Positive Matrix Factorisation (PMF) for CH4 source apportionment. The statistical models I will present combine continuous in-situ CH4 , C_2H_6, δ^1^3CH4 measured using a Cavity Ring Down Spectroscopy (CRDS) instrument [Assan et al. 2016] with volatile organic compound (VOC) observations performed using Gas Chromatography (GC) in order to explain the underlying variance of the data. The strengths and weaknesses of both models are identified for data collected in multi-source environments in the vicinity of four different types of sites; an agricultural farm with cattle, a natural gas compressor station, a wastewater treatment plant, and a pari-urban location in the Ile de France region impacted by various sources. To conclude, receptor model results to separate statistically the

[Clinical Analysis of Driver Mutations in Patients with Ph Negative Myeloproliferative Neoplasms].

PubMed

He, Zhi-Peng; Tian, Hui-Yun; Tan, Ming; Wu, Yong

2018-06-01

To explore the relationship between driver mutations and clinical characteristics in patients with Philadelphia chromosome (Ph) negative myeloproliferative neoplasms (MPN), so as to provide evidence for diagno-sis and treatment of the disease. The clinical data of 410 patients with classic Ph negative MPN including 150 cases of polycythemia vera (PV), 188 cases of essential thrombocythemia (ET) and 72 cases of primary myelofibrosis (PMF) from January 2013 to December 2016 in Fujian Medical University Union Hospital were retrospectively analyzed. The PCR or DNA sequencing were used for JAK2 V617F, JAK2 exon12, CALR and MPL W515L/K mutation analyses, and follow-up information on patients was updated by direct phone call or follow-up in outpatient. Among the 410 patients with Ph negative MPN, 136 (33.2%) cases were asymptomatic at diagnosis. 389 cases were sequenced and JAK2 V617F was detected in 87.1% (122/140) of PV, 64.1% (118/184) of ET, 64.6% (42/65) of PMF; JAK2 exon 12 mutation in 1 case of PV; MPL W515L/K mutation in 1 case of ET and PMF, respectively; CALR mutation in 18(9.8%) cases of ET and 5 (7.7%) cases of PMF. JAK2 V617F mutated PV patients ocourred in older age: the white blood cell count, platelet count and incidence of splenomegaly were higher than JAK2-negative PV cases(P<0.05). Compared with JAK2 V617F mutated ET patients, CALR mutated ET cases displayed younger age, lower leukocyte count, higher platelet count and lower incidence of thrombosis; JAK2-negative ET cases had younger age, lower leukocyte count, lower hemoglobin level, higher platelet count and lower incidence of thrombosis(P<0.05). The incidence of splenomegaly in JAK2 V617F or CALR mutated PMF patients was both higher than that in JAK2-negative PMF cases, but the incidence of leukemia transformation in JAK2-negative PMF patients was higher than that in JAK2 V617F mutated cases (P<0.05). The types of driver mutations are closely related with the clinical features and prognosis in Ph

Characterization and source identification of pollutants in runoff from a mixed land use watershed using ordination analyses.

PubMed

Lee, Dong Hoon; Kim, Jin Hwi; Mendoza, Joseph A; Lee, Chang Hee; Kang, Joo-Hyon

2016-05-01

While identification of critical pollutant sources is the key initial step for cost-effective runoff management, it is challenging due to the highly uncertain nature of runoff pollution, especially during a storm event. To identify critical sources and their quantitative contributions to runoff pollution (especially focusing on phosphorous), two ordination methods were used in this study: principal component analysis (PCA) and positive matrix factorization (PMF). For the ordination analyses, we used runoff quality data for 14 storm events, including data for phosphorus, 11 heavy metal species, and eight ionic species measured at the outlets of subcatchments with different land use compositions in a mixed land use watershed. Five factors as sources of runoff pollutants were identified by PCA: agrochemicals, groundwater, native soils, domestic sewage, and urban sources (building materials and automotive activities). PMF identified similar factors to those identified by PCA, with more detailed source mechanisms for groundwater (i.e., nitrate leaching and cation exchange) and urban sources (vehicle components/motor oils/building materials and vehicle exhausts), confirming the sources identified by PCA. PMF was further used to quantify contributions of the identified sources to the water quality. Based on the results, agrochemicals and automotive activities were the two dominant and ubiquitous phosphorus sources (39-61 and 16-47 %, respectively) in the study area, regardless of land use types.

A Novel Pentamethoxyflavone Down-Regulates Tumor Cell Survival and Proliferative and Angiogenic Gene Products through Inhibition of IκB Kinase Activation and Sensitizes Tumor Cells to Apoptosis by Cytokines and Chemotherapeutic Agents

PubMed Central

Phromnoi, Kanokkarn; Reuter, Simone; Sung, Bokyung; Prasad, Sahdeo; Kannappan, Ramaswamy; Yadav, Vivek R.; Chanmahasathien, Wisinee; Limtrakul, Pornngarm

2011-01-01

Most anticancer drugs have their origin in traditional medicinal plants. We describe here a flavone, 5,3′-dihydroxy-3,6,7,8,4′-pentamethoxyflavone (PMF), from the leaves of the Thai plant Gardenia obtusifolia, that has anti-inflammatory and anticancer potential. Because the nuclear factor-κB (NF-κB) pathway is linked to inflammation and tumorigenesis, we investigated the effect of PMF on this pathway. We found that PMF suppressed NF-κB activation induced by inflammatory agents, tumor promoters, and carcinogens. This suppression was not specific to the cell type. Although PMF did not directly modify the ability of NF-κB proteins to bind to DNA, it inhibited IκBα (inhibitory subunit of NF-κB) kinase, leading to suppression of phosphorylation and degradation of IκBα, and suppressed consequent p65 nuclear translocation, thus abrogating NF-κB-dependent reporter gene expression. Suppression of the NF-κB cell signaling pathway by the flavone led to the inhibition of expression of NF-κB-regulated gene products that mediate inflammation (cyclooxygenase-2), survival (XIAP, survivin, Bcl-xL, and cFLIP), proliferation (cyclin D1), invasion (matrix metalloproteinase-9), and angiogenesis (vascular endothelial growth factor). Suppression of antiapoptotic gene products by PMF correlated with the enhancement of apoptosis induced by tumor necrosis factor-α and the chemotherapeutic agents cisplatin, paclitaxel, and 5-flurouracil. Overall, our results indicate that PMF suppresses the activation of NF-κB and NF-κB-regulated gene expression, leading to the enhancement of apoptosis. This is the first report to demonstrate that this novel flavone has anti-inflammatory and anticancer effects by targeting the IKK complex. PMID:20930110

Characterization of heavy-metal-contaminated sediment by using unsupervised multivariate techniques and health risk assessment.

PubMed

Wang, Yeuh-Bin; Liu, Chen-Wuing; Wang, Sheng-Wei

2015-03-01

This study characterized the sediment quality of the severely contaminated Erjen River in Taiwan by using multivariate analysis methods-including factor analysis (FA), self-organizing maps (SOMs), and positive matrix factorization (PMF)-and health risk assessment. The SOMs classified the dataset with similar heavy-metal-contaminated sediment into five groups. FA extracted three major factors-traditional electroplating and metal-surface processing factor, nontraditional heavy-metal-industry factor, and natural geological factor-which accounted for 80.8% of the variance. The SOMs and FA revealed the heavy-metal-contaminated-sediment hotspots in the middle and upper reaches of the major tributary in the dry season. The hazardous index value for health risk via ingestion was 0.302. PMF further qualified the source apportionment, indicating that traditional electroplating and metal-surface-processing industries comprised 47% of the health risk posed by heavy-metal-contaminated sediment. Contaminants discharged from traditional electroplating and metal-surface-processing industries in the middle and upper reaches of the major tributary must be eliminated first to improve the sediment quality in Erjen River. The proposed assessment framework for heavy-metal-contaminated sediment can be applied to contaminated-sediment river sites in other regions. Copyright © 2014 Elsevier Inc. All rights reserved.

Source contributions to total concentrations and carcinogenic potencies of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in ambient air: a case study in Suzhou City, China.

PubMed

Xuan, Zhiqiang; Bi, Chenglu; Li, Jiafu; Nie, Jihua; Chen, Zhihai

2017-10-01

The potential source categories and source contributions of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) in ambient air from Suzhou City, China, were performed by principal component analysis-multiple linear regression (PCA-MLR) and positive matrix factorization (PMF). The carcinogenic potencies of PCDD/Fs were quantitatively apportioned based on the positive matrix factorization-toxic equivalent concentration (PMF-TEQ) method. The results of the present study were summarized as follows. (1) The total concentrations and toxic equivalent concentrations of PCDD/Fs (∑PCDD/Fs and TEQ) in ambient air from Suzhou City were 1.34-42.80 pg N m -3 and 0.081-1.22 pg I-TEQ N m -3 , respectively. (2) PCA-MLR suggested that industrial combustion (IC), electric arc furnaces (EAFs) and secondary aluminum smelters (ALSs), unleaded gas-fueled vehicle sources (UGFVs), ALSs, and hazardous solid waste incinerators (HSWIs) could be the primary PCDD/F contributors, accounting for 13.2, 16.7, 35.5, 19.4, and 15.2% of ∑PCDD/Fs, respectively. (3) PMF and PMF-TEQ indicated that EAFs (carbon steel), UGFVs, IC, ALSs, municipal solid waste incinerators (MSWIs) and hospital waste incinerators (HWIs), and HSWIs contributed 10.9, 10.9, 42.8, 11.3, 10.7, and 13.4% to ∑PCDD/Fs, but contributed 8.3, 12.3, 50.3, 12.7, 6.0, and 10.4% to carcinogenic potencies of PCDD/Fs. This study was the first attempt to quantitatively apportion the source-specific carcinogenic potencies of PCDD/Fs in ambient air.

Cervical spinal erythropoietin induces phrenic motor facilitation via ERK and Akt signaling

PubMed Central

Dale, Erica A.; Satriotomo, Irawan; Mitchell, Gordon S.

2012-01-01

Erythropoietin (EPO) is typically known for its role in erythropoiesis, but is also a potent neurotrophic/neuroprotective factor for spinal motor neurons. Another trophic factor regulated by Hypoxia-Inducible Factor-1, vascular endothelial growth factor (VEGF), signals via ERK and Akt activation to elicit long-lasting phrenic motor facilitation (pMF). Since EPO also signals via ERK and Akt activation, we tested the hypothesis that EPO elicits similar pMF. Using retrograde labeling and immunohistochemical techniques, we demonstrate in adult, male, Sprague-Dawley rats that EPO and its receptor, EPO-R, are expressed in identified phrenic motor neurons. Intrathecal EPO at C4 elicits long-lasting pMF; integrated phrenic nerve burst amplitude increased >90 min post-injection (63±12% baseline 90 min post-injection; p<0.001). EPO increased phosphorylation (and presumed activation) of ERK (1.6 fold vs controls; p<0.05) in phrenic motor neurons; EPO also increased pAkt (1.6 fold vs controls; p<0.05). EPO-induced pMF was abolished by the MEK/ERK inhibitor U0126 and the PI3 kinase/Akt inhibitor LY294002, demonstrating that ERK MAP kinases and Akt are both required for EPO-induced pMF. Pre-treatment with U0126 and LY294002 decreased both pERK and pAkt in phrenic motor neurons (p<0.05), indicating a complex interaction between these kinases. We conclude that EPO elicits spinal plasticity in respiratory motor control. Since EPO expression is hypoxia-sensitive, it may play a role in respiratory plasticity in conditions of prolonged or recurrent low oxygen. PMID:22539857

Combustion characteristics of Malaysian oil palm biomass, sub-bituminous coal and their respective blends via thermogravimetric analysis (TGA).

PubMed

Idris, Siti Shawalliah; Rahman, Norazah Abd; Ismail, Khudzir

2012-11-01

The combustion characteristics of Malaysia oil palm biomass (palm kernel shell (PKS), palm mesocarp fibre (PMF) and empty fruit bunches (EFB)), sub-bituminous coal (Mukah Balingian) and coal/biomass blends via thermogravimetric analysis (TGA) were investigated. Six weight ratios of coal/biomass blends were prepared and oxidised under dynamic conditions from temperature 25 to 1100°C at four heating rates. The thermogravimetric analysis demonstrated that the EFB and PKS evolved additional peak besides drying, devolatilisation and char oxidation steps during combustion. Ignition and burn out temperatures of blends were improved in comparison to coal. No interactions were observed between the coal and biomass during combustion. The apparent activation energy during this process was evaluated using iso-conversional model free kinetics which resulted in highest activation energy during combustion of PKS followed by PMF, EFB and MB coal. Blending oil palm biomass with coal reduces the apparent activation energy value. Copyright © 2012 Elsevier Ltd. All rights reserved.

Limitations to photosynthesis by proton motive force-induced photosystem II photodamage

DOE PAGES

Davis, Geoffry A.; Kanazawa, Atsuko; Schöttler, Mark Aurel; ...

2016-10-04

The thylakoid proton motive force (pmf) generated during photosynthesis is the essential driving force for ATP production; it is also a central regulator of light capture and electron transfer. We investigated the effects of elevated pmf on photosynthesis in a library of Arabidopsis thaliana mutants with altered rates of thylakoid lumen proton efflux, leading to a range of steady-state pmf extents. We observed the expected pmf-dependent alterations in photosynthetic regulation, but also strong effects on the rate of photosystem II (PSII) photodamage. Detailed analyses indicate this effect is related to an elevated electric field (Δψ) component of the pmf, rathermore » than lumen acidification, which in vivo increased PSII charge recombination rates, producing singlet oxygen and subsequent photodamage. The effects are seen even in wild type plants, especially under fluctuating illumination, suggesting that Δψ-induced photodamage represents a previously unrecognized limiting factor for plant productivity under dynamic environmental conditions seen in the field.« less

The treatment options for posterior malleolar fractures in tibial spiral fractures.

PubMed

Guo, Jialiang; Liu, Lei; Yang, Zongyou; Hou, Zhiyong; Chen, Wei; Zhang, Yingze

2017-09-01

The posterior malleolar fracture (PMF) in tibial spiral fractures are a common type of complication that occurs in tibial fractures. However, the indication of fixation for posterior fractures is still under debate and varies between different surgeons'. It is not unusual to find the smaller PMF (<25%), which could be treated conservatively within guidelines, treated with internal fixation in clinic. The aim of this study is to evaluate the clinical outcomes of tibial spiral fractures with PMF and provide proper guidance for the treatment of this special fracture. A total of 284 cases of spiral fractures combined with PMF were collected and analyzed. Demographic data, fragment size (classified by 25% involvement of ankle joint), time to weight-bearing and functional scores post-operatively were recorded. The ankle-hindfoot scale of the American Orthopaedic Foot and Ankle Society (AOFAS), a visual analogue scale (VAS) pain score, assessment of dorsiflexion restriction and arthritis scale were used as the main evaluations. Forty patients with a larger PMF (≥25%) and 72 with smaller ones (<25%) were fixed and categorized as the fixation group (FG). In the nonfixation group (NG), the corresponding numbers were four and 168 patients respectively. A total of 279 PMF were classified as large posterolateral triangular fragment carrying the posterior half of the fibular notch and intra-incisural posterolateral fragment involving one-fourth to one-third of the fibular notch. However, no obvious differences were observed in terms of the clinical outcomes in PMF involving one-fourth to one-third of the fibular notch. In the treatment of smaller PMF (<25%) of this type, there were no obvious differences in the functional outcomes between fixed (SF) and nonfixed PMF (SN). Many patients with smaller PMFs were fixated, but functional outcomes of SF were not better than those of SN. There is no need to emphasize other factors guiding the treatment of PMF involving one-fourth to

Source identification of water-soluble organic aerosols at a roadway site using a positive matrix factorization analysis.

PubMed

Park, Seungshik; Cho, Sung Yong; Bae, Min-Suk

2015-11-15

Daily PM2.5 measurements were carried out at a local roadway every sixth day from May 2011 to August 2013 to obtain seasonal quantitative information on the primary and secondary sources of two water-soluble organic carbon (WSOC) fractions. Filter samples were analyzed for OC, elemental carbon (EC), WSOC, hydrophilic and hydrophobic WSOC fractions (WSOC(HPI) and WSOC(HPO)), and ionic species. An XAD solid phase extraction method and a total organic carbon analyzer were used to isolate the two WSOC fractions and determine their amounts, respectively. The WSOC/OC and WSOC(HPI)/WSOC ratios were 0.62±0.13 and 0.47±0.14, respectively. Similar seasonal profiles in EC, OC, and WSOC concentrations were observed, with higher concentrations occurring in the cold season and lower concentrations in the warm season. However, opposite results were obtained in WSOC/OC and WSOC(HPI)/WSOC ratios, with the higher in the warm season and the lower in the cold season. Correlation analyses indicated that two WSOC fractions in winter were likely attributed to secondary formation processes, biomass burning (BB), and traffic emissions, while WSOC(HPI) observed in other seasons were associated with secondary formation processes similar to those of oxalate and secondary inorganic species. A positive matrix factorization (PMF) model was employed to investigate the sources of two WSOC fractions. PMF indicated that concentrations of WSOC fractions were affected by five sources: secondary NO3(-) related, secondary SO4(2-) and oxalate related, traffic emissions, BB emissions, and sea-salt. Throughout the study period, secondary organic aerosols were estimated to be the most dominant contributor of WSOC fractions, with higher contributions occurring in the warm seasons. The contribution of secondary aerosol formation processes (NO3(-) related+SO4(2-) and oxalate related) to WSOC(HPI) and WSOC(HPO) was on an average 56.2% (45.0-73.8%) and 47.7% (39.6-52.1%), respectively. The seasonal average

STV fueling options

NASA Technical Reports Server (NTRS)

Flemming, Ken

1991-01-01

Lunar vehicles that will be space based and reusable will require resupply of propellants in orbit. Approximately 75 pct. of the total mass delivered to low earth orbit will be propellants. Consequently, the propellant management techniques selected for Space Exploration Initiative (SEI) orbital operations will have a major influence on the overall SEI architecture. Five proposed propellant management facility (PMF) concepts were analyzed and compared in order to determine the best method of resupplying reusable, space based Lunar Transfer Vehicles (LTVs). The processing time needed at the Space Station to prepare LTV for its next lunar mission was estimated for each of the PMF concepts. The estimated times required to assemble and maintain the different PMF concepts were also compared. The results of the maintenance analysis were similar, with co-orbiting depots needing 100 to 350 pct. more annual maintenance. The first few external tanks mating operations at KSC encountered many problems that could cause serious lunar mission schedule delays. The use of drop tanks on lunar vehicles increases by a factor of four the number of critical propellant interface disturbances.

Problems in the fingerprints based polycyclic aromatic hydrocarbons source apportionment analysis and a practical solution.

PubMed

Zou, Yonghong; Wang, Lixia; Christensen, Erik R

2015-10-01

This work intended to explain the challenges of the fingerprints based source apportionment method for polycyclic aromatic hydrocarbons (PAH) in the aquatic environment, and to illustrate a practical and robust solution. The PAH data detected in the sediment cores from the Illinois River provide the basis of this study. Principal component analysis (PCA) separates PAH compounds into two groups reflecting their possible airborne transport patterns; but it is not able to suggest specific sources. Not all positive matrix factorization (PMF) determined sources are distinguishable due to the variability of source fingerprints. However, they constitute useful suggestions for inputs for a Bayesian chemical mass balance (CMB) analysis. The Bayesian CMB analysis takes into account the measurement errors as well as the variations of source fingerprints, and provides a credible source apportionment. Major PAH sources for Illinois River sediments are traffic (35%), coke oven (24%), coal combustion (18%), and wood combustion (14%). Copyright © 2015. Published by Elsevier Ltd.

Inter-comparison of receptor models for PM source apportionment: Case study in an industrial area

NASA Astrophysics Data System (ADS)

Viana, M.; Pandolfi, M.; Minguillón, M. C.; Querol, X.; Alastuey, A.; Monfort, E.; Celades, I.

2008-05-01

Receptor modelling techniques are used to identify and quantify the contributions from emission sources to the levels and major and trace components of ambient particulate matter (PM). A wide variety of receptor models are currently available, and consequently the comparability between models should be evaluated if source apportionment data are to be used as input in health effects studies or mitigation plans. Three of the most widespread receptor models (principal component analysis, PCA; positive matrix factorization, PMF; chemical mass balance, CMB) were applied to a single PM10 data set (n=328 samples, 2002-2005) obtained from an industrial area in NE Spain, dedicated to ceramic production. Sensitivity and temporal trend analyses (using the Mann-Kendall test) were applied. Results evidenced the good overall performance of the three models (r2>0.83 and α>0.91×between modelled and measured PM10 mass), with a good agreement regarding source identification and high correlations between input (CMB) and output (PCA, PMF) source profiles. Larger differences were obtained regarding the quantification of source contributions (up to a factor of 4 in some cases). The combined application of different types of receptor models would solve the limitations of each of the models, by constructing a more robust solution based on their strengths. The authors suggest the combined use of factor analysis techniques (PCA, PMF) to identify and interpret emission sources, and to obtain a first quantification of their contributions to the PM mass, and the subsequent application of CMB. Further research is needed to ensure that source apportionment methods are robust enough for application to PM health effects assessments.

Factors affecting construction performance: exploratory factor analysis

NASA Astrophysics Data System (ADS)

Soewin, E.; Chinda, T.

2018-04-01

The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

Extension Procedures for Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Nagy, Gabriel; Brunner, Martin; Lüdtke, Oliver; Greiff, Samuel

2017-01-01

We present factor extension procedures for confirmatory factor analysis that provide estimates of the relations of common and unique factors with external variables that do not undergo factor analysis. We present identification strategies that build upon restrictions of the pattern of correlations between unique factors and external variables. The…

Concentration levels and source apportionment of ultrafine particles in road microenvironments

NASA Astrophysics Data System (ADS)

Argyropoulos, G.; Samara, C.; Voutsa, D.; Kouras, A.; Manoli, E.; Voliotis, A.; Tsakis, A.; Chasapidis, L.; Konstandopoulos, A.; Eleftheriadis, K.

2016-03-01

A mobile laboratory unit (MOBILAB) with on-board instrumentation (Scanning Mobility Particle Sizer, SMPS; Ambient NOx analyzer) was used to measure size-resolved particle number concentrations (PNCs) of quasi-ultrafine particles (UFPs, 9-372 nm), along with NOx, in road microenvironments. On-road measurements were carried out in and around a large Greek urban agglomeration, the Thessaloniki Metropolitan Area (TMA). Two 2-week measurement campaigns were conducted during the warm period of 2011 and the cold period of 2012. During each sampling campaign, MOBILAB was driven through a 5-day inner-city route and a second 5-day external route covering in total a wide range of districts (urban, urban background, industrial and residential), and road types (major and minor urban roads, freeways, arterial and interurban roads). All routes were conducted during working days, in morning and in afternoon hours under real-world traffic conditions. Spatial classification of MOBILAB measurements involved the assignment of measurement points to location bins defined by the aspect ratio of adjacent urban street canyons (USCs). Source apportionment was further carried out, by applying Positive Matrix Factorization (PMF) to particle size distribution data. Apportioned PMF factors were interpreted, by employing a two-step methodology, which involved (a) statistical association of PMF factor contributions with 12 h air-mass back-trajectories ending at the TMA during MOBILAB measurements, and (b) Multiple Linear Regression (MLR) using PMF factor contributions as the dependent variables, while relative humidity, solar radiation flux, and vehicle speed were used as the independent variables. The applied data analysis showed that low-speed cruise and high-load engine operation modes are the two dominant sources of UFPs in most of the road microenvironments in the TMA, with significant contributions from background photochemical processes during the warm period, explaining the reversed

Source apportionment of PM10 by positive matrix factorization in urban area of Mumbai, India.

PubMed

Gupta, Indrani; Salunkhe, Abhaysinh; Kumar, Rakesh

2012-01-01

Particulate Matter (PM(10)) has been one of the main air pollutants exceeding the ambient standards in most of the major cities in India. During last few years, receptor models such as Chemical Mass Balance, Positive Matrix Factorization (PMF), PCA-APCS and UNMIX have been used to provide solutions to the source identification and contributions which are accepted for developing effective and efficient air quality management plans. Each site poses different complexities while resolving PM(10) contributions. This paper reports the variability of four sites within Mumbai city using PMF. Industrial area of Mahul showed sources such as residual oil combustion and paved road dust (27%), traffic (20%), coal fired boiler (17%), nitrate (15%). Residential area of Khar showed sources such as residual oil combustion and construction (25%), motor vehicles (23%), marine aerosol and nitrate (19%), paved road dust (18%) compared to construction and natural dust (27%), motor vehicles and smelting work (25%), nitrate (16%) and biomass burning and paved road dust (15%) in Dharavi, a low income slum residential area. The major contributors of PM(10) at Colaba were marine aerosol, wood burning and ammonium sulphate (24%), motor vehicles and smelting work (22%), Natural soil (19%), nitrate and oil burning (18%).

Source apportionment vs. emission inventories of non-methane hydrocarbons (NMHC) in an urban area of the Middle East: local and global perspectives

NASA Astrophysics Data System (ADS)

Salameh, Thérèse; Sauvage, Stéphane; Afif, Charbel; Borbon, Agnès; Locoge, Nadine

2016-03-01

We applied the positive matrix factorization model to two large data sets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC (non-methane hydrocarbons) sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt %, respectively, in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The PMF analysis finds reasonable differences on emission rates, of 20-39 % higher than the national road transport inventory. However, global inventories (ACCMIP, EDGAR, MACCity) underestimate the emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC (volatile organic compounds) anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector.

Structural insights into the evolution of a sexy protein: novel topology and restricted backbone flexibility in a hypervariable pheromone from the red-legged salamander, Plethodon shermani.

PubMed

Wilburn, Damien B; Bowen, Kathleen E; Doty, Kari A; Arumugam, Sengodagounder; Lane, Andrew N; Feldhoff, Pamela W; Feldhoff, Richard C

2014-01-01

In response to pervasive sexual selection, protein sex pheromones often display rapid mutation and accelerated evolution of corresponding gene sequences. For proteins, the general dogma is that structure is maintained even as sequence or function may rapidly change. This phenomenon is well exemplified by the three-finger protein (TFP) superfamily: a diverse class of vertebrate proteins co-opted for many biological functions - such as components of snake venoms, regulators of the complement system, and coordinators of amphibian limb regeneration. All of the >200 structurally characterized TFPs adopt the namesake "three-finger" topology. In male red-legged salamanders, the TFP pheromone Plethodontid Modulating Factor (PMF) is a hypervariable protein such that, through extensive gene duplication and pervasive sexual selection, individual male salamanders express more than 30 unique isoforms. However, it remained unclear how this accelerated evolution affected the protein structure of PMF. Using LC/MS-MS and multidimensional NMR, we report the 3D structure of the most abundant PMF isoform, PMF-G. The high resolution structural ensemble revealed a highly modified TFP structure, including a unique disulfide bonding pattern and loss of secondary structure, that define a novel protein topology with greater backbone flexibility in the third peptide finger. Sequence comparison, models of molecular evolution, and homology modeling together support that this flexible third finger is the most rapidly evolving segment of PMF. Combined with PMF sequence hypervariability, this structural flexibility may enhance the plasticity of PMF as a chemical signal by permitting potentially thousands of structural conformers. We propose that the flexible third finger plays a critical role in PMF:receptor interactions. As female receptors co-evolve, this flexibility may allow PMF to still bind its receptor(s) without the immediate need for complementary mutations. Consequently, this unique

Limitations to photosynthesis by proton motive force-induced photosystem II photodamage

PubMed Central

Davis, Geoffry A; Kanazawa, Atsuko; Schöttler, Mark Aurel; Kohzuma, Kaori; Froehlich, John E; Rutherford, A William; Satoh-Cruz, Mio; Minhas, Deepika; Tietz, Stefanie; Dhingra, Amit; Kramer, David M

2016-01-01

The thylakoid proton motive force (pmf) generated during photosynthesis is the essential driving force for ATP production; it is also a central regulator of light capture and electron transfer. We investigated the effects of elevated pmf on photosynthesis in a library of Arabidopsis thaliana mutants with altered rates of thylakoid lumen proton efflux, leading to a range of steady-state pmf extents. We observed the expected pmf-dependent alterations in photosynthetic regulation, but also strong effects on the rate of photosystem II (PSII) photodamage. Detailed analyses indicate this effect is related to an elevated electric field (Δψ) component of the pmf, rather than lumen acidification, which in vivo increased PSII charge recombination rates, producing singlet oxygen and subsequent photodamage. The effects are seen even in wild type plants, especially under fluctuating illumination, suggesting that Δψ-induced photodamage represents a previously unrecognized limiting factor for plant productivity under dynamic environmental conditions seen in the field. DOI: http://dx.doi.org/10.7554/eLife.16921.001 PMID:27697149

Can positive matrix factorization help to understand patterns of organic trace gases at the continental Global Atmosphere Watch site Hohenpeissenberg?

NASA Astrophysics Data System (ADS)

Leuchner, M.; Gubo, S.; Schunk, C.; Wastl, C.; Kirchner, M.; Menzel, A.; Plass-Dülmer, C.

2015-02-01

From the rural Global Atmosphere Watch (GAW) site Hohenpeissenberg in the pre-alpine area of southern Germany, a data set of 24 C2-C8 non-methane hydrocarbons over a period of 7 years was analyzed. Receptor modeling was performed by positive matrix factorization (PMF) and the resulting factors were interpreted with respect to source profiles and photochemical aging. Differing from other studies, no direct source attribution was intended because, due to chemistry along transport, mass conservation from source to receptor is not given. However, at remote sites such as Hohenpeissenberg, the observed patterns of non-methane hydrocarbons can be derived from combinations of factors determined by PMF. A six-factor solution showed high stability and the most plausible results. In addition to a biogenic and a background factor of very stable compounds, four additional anthropogenic factors were resolved that could be divided into two short- and two long-lived patterns from evaporative sources/natural gas leakage and incomplete combustion processes. The volume or mass contribution at the site over the entire period was, in decreasing order, from the following factor categories: background, gas leakage and long-lived evaporative, residential heating and long-lived combustion, short-lived evaporative, short-lived combustion, and biogenic. The importance with respect to reactivity contribution was generally in reverse order, with the biogenic and the short-lived combustion factors contributing most. The seasonality of the factors was analyzed and compared to results of a simple box model using constant emissions and the photochemical decay calculated from the measured annual cycles of OH radicals and ozone. Two of the factors, short-lived combustion and gas leakage/long-lived evaporative, showed winter/summer ratios of about 9 and 7, respectively, as expected from constant source estimations. Contrarily, the short-lived evaporative emissions were about 3 times higher in summer

Uncertainty assessment of source attribution of PM(2.5) and its water-soluble organic carbon content using different biomass burning tracers in positive matrix factorization analysis--a case study in Beijing, China.

PubMed

Tao, Jun; Zhang, Leiming; Zhang, Renjian; Wu, Yunfei; Zhang, Zhisheng; Zhang, Xiaoling; Tang, Yixi; Cao, Junji; Zhang, Yuanhang

2016-02-01

Daily PM2.5 samples were collected at an urban site in Beijing during four one-month periods in 2009-2010, with each period in a different season. Samples were subject to chemical analysis for various chemical components including major water-soluble ions, organic carbon (OC) and water-soluble organic carbon (WSOC), element carbon (EC), trace elements, anhydrosugar levoglucosan (LG), and mannosan (MN). Three sets of source profiles of PM2.5 were first identified through positive matrix factorization (PMF) analysis using single or combined biomass tracers - non-sea salt potassium (nss-K(+)), LG, and a combination of nss-K(+) and LG. The six major source factors of PM2.5 included secondary inorganic aerosol, industrial pollution, soil dust, biomass burning, traffic emission, and coal burning, which were estimated to contribute 31±37%, 39±28%, 14±14%, 7±7%, 5±6%, and 4±8%, respectively, to PM2.5 mass if using the nss-K(+) source profiles, 22±19%, 29±17%, 20±20%, 13±13%, 12±10%, and 4±6%, respectively, if using the LG source profiles, and 21±17%, 31±18%, 19±19%, 11±12%, 14±11%, and 4±6%, respectively, if using the combined nss-K(+) and LG source profiles. The uncertainties in the estimation of biomass burning contributions to WSOC due to the different choices of biomass burning tracers were around 3% annually and up to 24% seasonally in terms of absolute percentage contributions, or on a factor of 1.7 annually and up to a factor of 3.3 seasonally in terms of the actual concentrations. The uncertainty from the major source (e.g. industrial pollution) was on a factor of 1.9 annually and up to a factor of 2.5 seasonally in the estimated WSOC concentrations. Copyright © 2015 Elsevier B.V. All rights reserved.

Understanding mineral dusts from the Middle East

NASA Astrophysics Data System (ADS)

Engelbrecht, J. P.; McDonald, E.; Gillies, J. A.; Jayanty, J.; Casuccio, G.; Gertler, A.

2012-12-01

The purpose of the program was to provide scientifically founded information on the chemical and physical properties of airborne mineral dust collected during a period of approximately one year, largely in 2006, at Djibouti, Afghanistan (Bagram, Khowst), Qatar, United Arab Emirates, Iraq (Balad, Baghdad, Tallil, Tikrit, Taji, Al Asad), and Kuwait (Northern, Central, Coastal, and Southern regions). To fully understand mineral dusts, their chemical and physical properties as well as mineralogical interrelationships were accurately established. Three collocated low volume particulate samplers, one each for the total suspended (TSP), less than 10 μm in aerodynamic diameter (PM10), and less than 2.5 μm in aerodynamic diameter (PM2.5) particulate matter were deployed at each of the 15 sites, operating on a "1 in 6 day" sampling schedule. A total of 3,136 filter samples were collected on a 1-in-6 day schedule, along with one-time bulk soil samples, at each of the 15 sites. Sample media included Teflon® membrane and quartz fiber filters for chemical analysis (71 species), and Nuclepore® filters for individual particle analysis by Scanning Electron Microscopy (SEM). The provisional study of the data revealed three broad air pollution sources: geological dust, smoke from burn pits, and until now unidentified lead-zinc smelters and battery-processing facilities. SEM results and secondary electron imagery show that quartz and other silicate minerals and, to a lesser extent, dolomite and calcite particles are coated by a thin Si-Al-Mg layer, probably the clay minerals palygorskite and/or montmorillonite/illite. Positive Matrix Factorization (PMF) was performed on aerosol samples collected at six military sites in Iraq (Balad, Baghdad, Tallil, Tikrit, Taji, and Al Asad). PMF results reflect chemical differences amongst sources impacting at individual sites, further complicated by the regional geomorphology and meteorology. Sampling sites are seldom impacted by one source at

Cloning of three genes involved in the flavonoid metabolic pathway and their expression during insect resistance in Pinus massoniana Lamb.

PubMed

Yang, Z Q; Chen, H; Tan, J H; Xu, H L; Jia, J; Feng, Y H

2016-12-23

Pinus massoniana Lamb. is an important timber and turpentine-producing tree species in China. Dendrolimus punctatus and Dasychira axutha are leaf-eating pests that have harmful effects on P. massoniana production. Few studies have focused on the molecular mechanisms underlying pest resistance in P. massoniana. Based on sequencing analysis of the transcriptomes of insect-resistant P. massoniana, three key genes involved in the flavonoid metabolic pathway were identified in the present study (PmF3H, PmF3'5'H, and PmC4H). Structural domain analysis showed that the PmF3H gene contains typical binding sites for the 2OG-Fe (II) oxygenase superfamily, while PmF3'5'H and PmC4H both contain the cytochrome P450 structural domain, which is specific for P450 enzymes. Phylogenetic analysis showed that each of the three P. massoniana genes, and the homologous genes in gymnosperms, clustered into a group. Expression of these three genes was highest in the stems, and was higher in the insect-resistant P. massoniana varieties than in the controls. The extent of the increased expression in the insect-resistant P. massoniana varieties indicated that these three genes are involved in defense mechanisms against pests in this species. In the insect-resistant varieties, rapid induction of PmF3H increased the levels of PmF3'5'H and PmC4H expression. The enhanced anti-pest capability of the insect-resistant varieties could be related to temperature and humidity. In addition, these results suggest that these three genes maycontribute to the change in flower color during female cone development.

Exploratory Bi-factor Analysis: The Oblique Case.

PubMed

Jennrich, Robert I; Bentler, Peter M

2012-07-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.

A new generic plant growth model framework (PMF): Simulating distributed dynamic interaction of biomass production and its interaction with water and nutrients fluxes

NASA Astrophysics Data System (ADS)

Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz

2010-05-01

Today, crop models have a widespread application in natural sciences, because plant growth interacts and modifies the environment. Transport processes involve water and nutrient uptake from the saturated and unsaturated zone in the pedosphere. Turnover processes include the conversion of dead root biomass into organic matter. Transpiration and the interception of radiation influence the energy exchange between atmosphere and biosphere. But many more feedback mechanisms might be of interest, including erosion, soil compaction or trace gas exchanges. Most of the existing crop models have a closed structure and do not provide interfaces or code design elements for easy data transfer or process exchange with other models during runtime. Changes in the model structure, the inclusion of alternative process descriptions or the implementation of additional functionalities requires a lot of coding. The same is true if models are being upscaled from field to landscape or catchment scale. We therefore conclude that future integrated model developments would benefit from a model structure that has the following requirements: replaceability, expandability and independency. In addition to these requirements we also propose the interactivity of models, which means that models that are being coupled are highly interacting and depending on each other, i.e. the model should be open for influences from other independent models and react on influences directly. Hence, a model which consists of building blocks seems to be reasonable. The aim of the study is the presentation of the new crop model type, the plant growth model framework, PMF. The software concept refers to an object-oriented approach, which is developed with the Unified Modeling Language (UML). The model is implemented with Python, a high level object-oriented programming language. The integration of the models with a setup code enables the data transfer on the computer memory level and direct exchange of information

Long-term chemical analysis and organic aerosol source apportionment at nine sites in central Europe: source identification and uncertainty assessment

NASA Astrophysics Data System (ADS)

Daellenbach, Kaspar R.; Stefenelli, Giulia; Bozzetti, Carlo; Vlachou, Athanasia; Fermo, Paola; Gonzalez, Raquel; Piazzalunga, Andrea; Colombi, Cristina; Canonaco, Francesco; Hueglin, Christoph; Kasper-Giebl, Anne; Jaffrezo, Jean-Luc; Bianchi, Federico; Slowik, Jay G.; Baltensperger, Urs; El-Haddad, Imad; Prévôt, André S. H.

2017-11-01

Long-term monitoring of organic aerosol is important for epidemiological studies, validation of atmospheric models, and air quality management. In this study, we apply a recently developed filter-based offline methodology using an aerosol mass spectrometer (AMS) to investigate the regional and seasonal differences of contributing organic aerosol sources. We present offline AMS measurements for particulate matter smaller than 10 µm at nine stations in central Europe with different exposure characteristics for the entire year of 2013 (819 samples). The focus of this study is a detailed source apportionment analysis (using positive matrix factorization, PMF) including in-depth assessment of the related uncertainties. Primary organic aerosol (POA) is separated in three components: hydrocarbon-like OA related to traffic emissions (HOA), cooking OA (COA), and biomass burning OA (BBOA). We observe enhanced production of secondary organic aerosol (SOA) in summer, following the increase in biogenic emissions with temperature (summer oxygenated OA, SOOA). In addition, a SOA component was extracted that correlated with an anthropogenic secondary inorganic species that is dominant in winter (winter oxygenated OA, WOOA). A factor (sulfur-containing organic, SC-OA) explaining sulfur-containing fragments (CH3SO2+), which has an event-driven temporal behaviour, was also identified. The relative yearly average factor contributions range from 4 to 14 % for HOA, from 3 to 11 % for COA, from 11 to 59 % for BBOA, from 5 to 23 % for SC-OA, from 14 to 27 % for WOOA, and from 15 to 38 % for SOOA. The uncertainty of the relative average factor contribution lies between 2 and 12 % of OA. At the sites north of the alpine crest, the sum of HOA, COA, and BBOA (POA) contributes less to OA (POA / OA = 0.3) than at the southern alpine valley sites (0.6). BBOA is the main contributor to POA with 87 % in alpine valleys and 42 % north of the alpine crest. Furthermore, the influence of primary

ATMOSPHERIC AEROSOL SOURCE-RECEPTOR RELATIONSHIPS: THE ROLE OF COAL-FIRED POWER PLANTS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Allen L. Robinson; Spyros N. Pandis; Cliff I. Davidson

2005-04-01

This report describes the technical progress made on the Pittsburgh Air Quality Study (PAQS) during the period of September 2004 through February 2005. Significant progress was made this project period on the analysis of ambient data, source apportionment, and deterministic modeling activities. The major experimental achievement this project period was the characterization of the mercury and fine particle emissions from two modern, large, commercial pulverized coal boilers. This testing completes the field work component of the Source Characterization Activity. This report highlights results from mercury emission measurements made using a dilution sampler. The measurements clearly indicate that mercury is beingmore » transformed from an oxidized to an elemental state within the dilution. However, wall effects are significant making it difficult to determine whether or not these changes occur in the gas phase or due to some interaction with the sampler walls. This report also presents results from an analysis that uses spherical aluminum silicate (SAS) particles as a marker for primary PM{sub 2.5} emitted from coal combustion. Primary emissions from coal combustion contribute only a small fraction of the PM{sub 2.5} mass (less than 1.5% in the summer and less than 3% in the winter) at the Pittsburgh site. Ambient SAS concentrations also appear to be reasonably spatially homogeneous. Finally, SAS emission factors measured at pilot-scale are consistent with measurements made at full-scale. This report also presents results from applying the Unmix and PMF models to estimate the contribution of different sources to the PM{sub 2.5} mass concentrations in Pittsburgh using aerosol composition information. Comparison of the two models shows similar source composition and contribution for five factors: crustal material, nitrate, an Fe, Mn, and Zn factor, specialty steel production, and a cadmium factor. PMF found several additional factors. Comparison between source

Identification and characterization of fine and coarse particulate matter sources in a middle-European urban environment

NASA Astrophysics Data System (ADS)

Kertész, Zs.; Szoboszlai, Z.; Angyal, A.; Dobos, E.; Borbély-Kiss, I.

2010-06-01

In this work a source apportionment study is presented which aimed to characterize the PM 2.5 and PM 2.5-10 sources in the urban area of Debrecen, East-Hungary by using streaker samples, IBA methods and positive matrix factorization (PMF) analysis. Samples of fine (PM 2.5) and coarse (PM 2.5-10) urban particulate matter were collected with 2 h time resolution in the frame of five sampling campaigns during 2007-2009 in different seasons in the downtown of Debrecen. Elemental concentrations from Al to Pb of over 1000 samples were obtained by particle induced X-ray emission (PIXE); concentrations of black carbon (BC) were determined with a smoke stain reflectometer. On this data base source apportionment was carried out by using the PMF method. Seven factors were identified for both size fractions, including soil dust, traffic, secondary aerosol - sulphates, domestic heating, oil combustion, agriculture and an unknown factor enriched with chlorine. Seasonal and daily variation of the different factors was studied as well as their dependence on meteorological parameters. Besides determining the time patterns characteristic to the city, several emission episodes were identified including a Saharan dust intrusion on 21st-24th May, 2008.

Exploratory Bi-Factor Analysis: The Oblique Case

ERIC Educational Resources Information Center

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

Mass closure and source apportionment of PM2.5 by Positive Matrix Factorization analysis in urban Mediterranean environment

NASA Astrophysics Data System (ADS)

Mantas, E.; Remoundaki, E.; Halari, I.; Kassomenos, P.; Theodosi, C.; Hatzikioseyian, A.; Mihalopoulos, N.

2014-09-01

A systematic monitoring of PM2.5 was carried out during a period of three years (from February 2010 to April 2013) at an urban site, at the National Technical University of Athens campus. Two types of 24-h PM2.5 samples have been collected: 271 samples on PTFE and 116 samples on quartz filters. Daily PM2.5 concentrations were determined for both types of samples. Total sulfur, crustal origin elements and elements of a major crustal component (Al, Si, Fe, Ca, K, Mg, Ti) trace elements (Zn, Pb, Cu, Ni, P, V, Cr, Mn) and water soluble ions (Cl-, NO3-, SO42-, Na+, K+, NH4+, Ca2+, Mg2+) were determined on the PTFE samples. Organic carbon (OC), elemental carbon (EC) and water soluble ions were determined on the quartz samples. For the mass closure six components were considered: Secondary Inorganic Aerosol (SIA), Organic Matter (OM), Elemental Carbon (EC), Dust, Mineral anthropogenic component (MIN) and Sea Salt (SS). SIA and OM contributed in the mass of PM2.5 almost equally: 30-36% and 30% respectively. EC, SS and MIN accounted for 5, 4 and 3% respectively of the total PM2.5 mass. Dust accounted for about 3-5% in absence of dust transport event and reached a much higher percentage in case of dust transport event. These contributions justify at least 80% of the PM2.5 mass. Source apportionment analysis has been performed by Positive Matrix Factorization. The combination of the PMF results obtained by both data sets lead to the definition of six factors: 1. SO42-, NH4+, OC (industrial/regional sources, secondary aerosol) 2. EC, OC, K and trace metals (traffic and heating by biomass burning, locally emitted aerosol). 3. Ca, EC, OC and trace metals (urban-resuspended road dust reflecting exhaust emissions), 4. Secondary nitrates 5. Na, Cl (marine source) 6. Si, Al, Ti, Ca, Fe (Dust transported from Sahara). These factors reflect not only main sources contributions but also underline the key role of atmospheric dynamics and aerosol ageing processes in this Mediterranean

Source Apportionment of Atmospheric Polychlorinated Biphenyls in New Jersey 1997-2011.

PubMed

Praipipat, Pornsawai; Meng, Qingyu; Miskewitz, Robert J; Rodenburg, Lisa A

2017-02-07

Concentrations of polychlorinated biphenyls (PCBs) in the Delaware River currently exceed the Water Quality Criteria of 16 pg/L for the sum of PCBs due in part to atmospheric deposition. The purpose of this work was to use a source apportionment tool called Positive Matrix Factorization (PMF) to identify the sources of PCBs to the atmosphere in this area and determine whether their concentrations are declining over time. The data set was compiled by the Delaware Atmospheric Deposition Network (DADN) from samples taken in Camden, NJ from 1999 to 2011 and New Brunswick, NJ from 1997 to 2011. The PMF analysis revealed four resolved factors at each site. The factors that dominate the PCB burden in the atmosphere at both Camden and New Brunswick resemble Aroclor 1242. These factors declined in concentration during some portions of the monitoring period, but this decline slowed or stopped during 2003-2011. None of the factors displayed consistent declines in concentration throughout the monitoring periods, and some factors actually increased in concentration during some periods. This suggests natural attenuation alone will not control atmospheric PCB concentrations, and additional efforts are needed to control PCB atmospheric emissions as well as the numerous other sources of PCBs to the estuary.

Interpretation of current-voltage relationships for "active" ion transport systems: I. Steady-state reaction-kinetic analysis of class-I mechanisms.

PubMed

Hansen, U P; Gradmann, D; Sanders, D; Slayman, C L

1981-01-01

This paper develops a simple reaction-kinetic model to describe electrogenic pumping and co- (or counter-) transport of ions. It uses the standard steady-state approach for cyclic enzyme- or carrier-mediated transport, but does not assume rate-limitation by any particular reaction step. Voltage-dependence is introduced, after the suggestion of Läuger and Stark (Biochim. Biophys. Acta 211:458-466, 1970), via a symmetric Eyring barrier, in which the charge-transit reaction constants are written as k12 = ko12 exp(zF delta psi/2RT) and k21 = ko21 exp(-zF delta psi/2RT). For interpretation of current-voltage relationships, all voltage-independent reaction steps are lumped together, so the model in its simplest form can be described as a pseudo-2-state model. It is characterized by the two voltage-dependent reaction constants, two lumped voltage-independent reaction constants (k12, k21), and two reserve factors (ri, ro) which formally take account of carrier states that are indistinguishable in the current-voltage (I-V) analysis. The model generates a wide range of I-V relationships, depending on the relative magnitudes of the four reaction constants, sufficient to describe essentially all I-V datas now available on "active" ion-transport systems. Algebraic and numerical analysis of the reserve factors, by means of expanded pseudo-3-, 4-, and 5-state models, shows them to be bounded and not large for most combinations of reaction constants in the lumped pathway. The most important exception to this rule occurs when carrier decharging immediately follows charge transit of the membrane and is very fast relative to other constituent voltage-independent reactions. Such a circumstance generates kinetic equivalence of chemical and electrical gradients, thus providing a consistent definition of ion-motive forces (e.g., proton-motive force, PMF). With appropriate restrictions, it also yields both linear and log-linear relationships between net transport velocity and either

On the link between hygroscopicity, volatility, and oxidation state of ambient and water-soluble aerosol in the Southeastern United States

NASA Astrophysics Data System (ADS)

Cerully, K. M.; Bougiatioti, A.; Hite, J. R., Jr.; Guo, H.; Xu, L.; Ng, N. L.; Weber, R.; Nenes, A.

2014-12-01

The formation of secondary organic aerosol (SOA) combined with the partitioning of semi-volatile organic components can impact numerous aerosol properties including cloud condensation nuclei (CCN) activity, hygroscopicity and volatility. During the summer 2013 Southern Oxidant and Aerosol Study (SOAS) field campaign in a rural site in the Southeastern United States, a suite of instruments including a CCN counter, a thermodenuder (TD) and a high resolution time-of-flight aerosol mass spectrometer (AMS) were used to measure CCN activity, aerosol volatility, composition and oxidation state. Particles were either sampled directly from ambient or through a Particle Into Liquid Sampler (PILS), allowing the investigation of the water-soluble aerosol component. Ambient aerosol exhibited size-dependent composition with larger particles being more hygroscopic. The hygroscopicity of thermally-denuded aerosol was similar between ambient and PILS-generated aerosol and showed limited dependence on volatilization. Results of AMS 3-factor Positive Matrix Factorization (PMF) analysis for the PILS-generated aerosol showed that the most hygroscopic components are most likely the most and the least volatile features of the aerosol. No clear relationship was found between organic hygroscopicity and oxygen-to-carbon ratio; in fact, Isoprene organic aerosol (Isoprene-OA) was found to be the most hygroscopic factor, while at the same time being the least oxidized and likely most volatile of all PMF factors. Considering the diurnal variation of each PMF factor and its associated hygroscopicity, Isoprene-OA and More Oxidized - Oxidized Oxygenated Organic Aerosol (MO-OOA) are the prime contributors to hygroscopicity and covary with Less Oxidized - Oxidized Oxygenated Organic Aerosol (LO-OOA) in a way that induces the observed diurnal invariance in total organic hygroscopicity. Biomass Burning Organic Aerosol (BBOA) contributed little to aerosol hygroscopicity, which is expected since there

Clonal evolution revealed by whole genome sequencing in a case of primary myelofibrosis transformed to secondary acute myeloid leukemia.

PubMed

Engle, E K; Fisher, D A C; Miller, C A; McLellan, M D; Fulton, R S; Moore, D M; Wilson, R K; Ley, T J; Oh, S T

2015-04-01

Clonal architecture in myeloproliferative neoplasms (MPNs) is poorly understood. Here we report genomic analyses of a patient with primary myelofibrosis (PMF) transformed to secondary acute myeloid leukemia (sAML). Whole genome sequencing (WGS) was performed on PMF and sAML diagnosis samples, with skin included as a germline surrogate. Deep sequencing validation was performed on the WGS samples and an additional sample obtained during sAML remission/relapsed PMF. Clustering analysis of 649 validated somatic single-nucleotide variants revealed four distinct clonal groups, each including putative driver mutations. The first group (including JAK2 and U2AF1), representing the founding clone, included mutations with high frequency at all three disease stages. The second clonal group (including MYB) was present only in PMF, suggesting the presence of a clone that was dispensable for transformation. The third group (including ASXL1) contained mutations with low frequency in PMF and high frequency in subsequent samples, indicating evolution of the dominant clone with disease progression. The fourth clonal group (including IDH1 and RUNX1) was acquired at sAML transformation and was predominantly absent at sAML remission/relapsed PMF. Taken together, these findings illustrate the complex clonal dynamics associated with disease evolution in MPNs and sAML.

Argon offline-AMS source apportionment of organic aerosol over yearly cycles for an urban, rural, and marine site in northern Europe

NASA Astrophysics Data System (ADS)

Bozzetti, Carlo; Sosedova, Yuliya; Xiao, Mao; Daellenbach, Kaspar R.; Ulevicius, Vidmantas; Dudoitis, Vadimas; Mordas, Genrik; Byčenkienė, Steigvilė; Plauškaitė, Kristina; Vlachou, Athanasia; Golly, Benjamin; Chazeau, Benjamin; Besombes, Jean-Luc; Baltensperger, Urs; Jaffrezo, Jean-Luc; Slowik, Jay G.; El Haddad, Imad; Prévôt, André S. H.

2017-01-01

The widespread use of Aerodyne aerosol mass spectrometers (AMS) has greatly improved real-time organic aerosol (OA) monitoring, providing mass spectra that contain sufficient information for source apportionment. However, AMS field deployments remain expensive and demanding, limiting the acquisition of long-term datasets at many sampling sites. The offline application of aerosol mass spectrometry entailing the analysis of nebulized water extracted filter samples (offline-AMS) increases the spatial coverage accessible to AMS measurements, being filters routinely collected at many stations worldwide. PM1 (particulate matter with an aerodynamic diameter < 1 µm) filter samples were collected during an entire year in Lithuania at three different locations representative of three typical environments of the southeast Baltic region: Vilnius (urban background), Rūgšteli\\vskis (rural terrestrial), and Preila (rural coastal). Aqueous filter extracts were nebulized in Ar, yielding the first AMS measurements of water-soluble atmospheric organic aerosol (WSOA) without interference from air fragments. This enables direct measurement of the CO+ fragment contribution, whose intensity is typically assumed to be equal to that of CO2+. Offline-AMS spectra reveal that the water-soluble CO2+ : CO+ ratio not only shows values systematically > 1 but is also dependent on season, with lower values in winter than in summer. AMS WSOA spectra were analyzed using positive matrix factorization (PMF), which yielded four factors. These factors included biomass burning OA (BBOA), local OA (LOA) contributing significantly only in Vilnius, and two oxygenated OA (OOA) factors, summer OOA (S-OOA) and background OOA (B-OOA), distinguished by their seasonal variability. The contribution of traffic exhaust OA (TEOA) was not resolved by PMF due to both low concentrations and low water solubility. Therefore, the TEOA concentration was estimated using a chemical mass balance approach, based on the

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

Womack, Sid T.; Hannah, Shellie Louise; Bell, Columbus David

2012-01-01

Four factors in teaching intern effectiveness, as measured by a Praxis III-similar instrument, were found among observational data of teaching interns during the 2010 spring semester. Those factors were lesson planning, teacher/student reflection, fairness & safe environment, and professionalism/efficacy. This factor analysis was as much of a…

Source apportionment of atmospheric bulk deposition in the Belgrade urban area using Positive Matrix factorization

NASA Astrophysics Data System (ADS)

Tasić, M.; Mijić, Z.; Rajšić, S.; Stojić, A.; Radenković, M.; Joksić, J.

2009-04-01

The primary objective of the present study was to assess anthropogenic impacts of heavy metals to the environment by determination of total atmospheric deposition of heavy metals. Atmospheric depositions (wet + dry) were collected monthly, from June 2002 to December 2006, at three urban locations in Belgrade, using bulk deposition samplers. Concentrations of Fe, Al, Pb, Zn, Cu, Ni, Mn, Cr, V, As and Cd were analyzed using atomic absorption spectrometry. Based upon these results, the study attempted to examine elemental associations in atmospheric deposition and to elucidate the potential sources of heavy metal contaminants in the region by the use of multivariate receptor model Positive Matrix Factorization (PMF).

Robust Bayesian Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Yuan, Ke-Hai

2003-01-01

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

Source apportionment of particulate matter and trace gases near a major refinery near the Houston Ship Channel

NASA Astrophysics Data System (ADS)

Wallace, Henry W.; Sanchez, Nancy P.; Flynn, James H.; Erickson, Mathew H.; Lefer, Barry L.; Griffin, Robert J.

2018-01-01

From February 7 to 27, 2015, a mobile air quality laboratory was deployed to a location proximate to a major refinery, the Port of Houston, and several neighborhoods to conduct measurements of atmospheric trace gases and particulate matter. Two statistical models were utilized to apportion the sources of pollution impacting this site and the denizens of the nearby neighborhoods. Positive matrix factorization (PMF) was performed on the organic signal of the aerosol mass spectra, resulting in five factors totaling an average of 4.1 μg/m3 of the organic aerosol: hydrocarbon-like (0.67 μg/m3), cooking (0.35 μg/m3) biomass burning (1.14 μg/m3), low-volatility oxidized (1.15 μg/m3), and semi-volatile oxidized (0.78 μg/m3). Principal component analysis was performed on daytime and nighttime data, including concentrations from PMF output, of other PM1 components, and of trace gases. This generated five daytime and five nighttime factors that explained 74.5% and 73.0% of the variance, respectively. The most important factors impacting this site were from mobile source exhaust and petrochemical aromatic compound emissions. Together these two factors also constitute most of the observed carcinogens.

Source Identification of Polycyclic Aromatic Hydrocarbons by Diagnostic Ratios and Positive Matrix Factorization

NASA Astrophysics Data System (ADS)

Dvorska, A.; Jarkovsky, J.; Lammel, G.; Klanova, J.

2009-04-01

Although polycyclic aromatic hydrocarbons (PAHs) are also of natural origin, in many regions their environmental concentrations have strongly increased due to human activities. These semivolatile organic compounds are generally formed during incomplete combustion. Other sources include volatilization from unburned petroleum or tire abrasion in road traffic. Among all pollutants PAHs pose the highest human health hazard in Europe (WHO, 2003). A multivariate statistical method, positive matrix factorization (PMF; Paatero, 1997), and diagnostic ratios of individual PAHs (e.g. Yunker et al., 2002) are used for PAH source identification in central Europe. To minimise confounding factors such as differences in volatility, water solubility, adsorption etc., diagnostic ratios should be restricted to PAHs of similar molecular mass (Readman et al., 1987). Furthermore, different reactivities are limiting. Nevertheless, the application of PAH diagnostic ratios is often inconclusive, because substance patterns (profiles) have not been reported for all sources and ranges for various sources overlap. The complete profiles are made use of by statistical methods such as factor analysis, UNMIX and PMF (Tauler et al., 2006). However, these methods can be unreliable, because of incomplete knowledge of source profiles and the analysis' sensitivity to the data distribution. A unique 12-year data set of concentrations of PAHs (16 individual substances, 2 phases, weekly) in air, measured at the regional observatory Košetice, Czech Republic, is examined, together with shorter time series from Leipzig (urban background) and Schwartenberg (subalpine mountain background), Germany. Also, retene and coronene as specific source markers measured in Košetice from 2006 on are included into the analysis. An extensive literature search on PAH emission profiles was conducted. This data set was accomplished by measurements at sites in the Zlínsko region, Czech Republic, which are strongly dominated

Recommendation based on trust diffusion model.

PubMed

Yuan, Jinfeng; Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure.

Recommendation Based on Trust Diffusion Model

PubMed Central

Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure. PMID:25009827

Primary to secondary organic aerosol: evolution of organic emissions from mobile combustion sources

NASA Astrophysics Data System (ADS)

Presto, A. A.; Gordon, T. D.; Robinson, A. L.

2014-05-01

A series of smog chamber experiments were conducted to investigate the transformation of primary organic aerosol (POA) and formation of secondary organic aerosol (SOA) during the photooxidation of dilute exhaust from a fleet of gasoline and diesel motor vehicles and two gas-turbine engines. In experiments where POA was present in the chamber at the onset of photooxidation, positive matrix factorization (PMF) was used to determine separate POA and SOA factors from aerosol mass spectrometer data. A 2-factor solution, with one POA factor and one SOA factor, was sufficient to describe the organic aerosol for gasoline vehicles, diesel vehicles, and one of the gas-turbine engines. Experiments with the second gas-turbine engine required a 3-factor PMF solution with a POA factor and two SOA factors. Results from the PMF analysis were compared to the residual method for determining SOA and POA mass concentrations. The residual method apportioned a larger fraction of the organic aerosol mass as POA because it assumes that all mass at m / z 57 is associated with POA. The POA mass spectrum for the gasoline and diesel vehicles exhibited high abundances of the CnH2n+1 series of ions (m / z 43, 57, etc.) and was similar to the mass spectra of the hydrocarbon-like organic aerosol factor determined from ambient data sets with one exception, a diesel vehicle equipped with a diesel oxidation catalyst. POA mass spectra for the gas-turbine engines are enriched in the CnH2n-1 series of ions (m / z 41, 55, etc.), consistent with the composition of the lubricating oil used in these engines. The SOA formed from the three sources exhibits high abundances of m / z 44 and 43, indicative of mild oxidation. The SOA mass spectra are consistent with less-oxidized ambient SV-OOA (semivolatile oxygenated organic aerosols) and fall within the triangular region of f44 versus f43 defined by ambient measurements. However there is poor absolute agreement between the experimentally derived SOA mass

Fragility Analysis of Concrete Gravity Dams

NASA Astrophysics Data System (ADS)

Tekie, Paulos B.; Ellingwood, Bruce R.

2002-09-01

Concrete gravity dams are an important part ofthe nation's infrastructure. Many dams have been in service for over 50 years, during which time important advances in the methodologies for evaluation of natural phenomena hazards have caused the design-basis events to be revised upwards, in some cases significantly. Many existing dams fail to meet these revised safety criteria and structural rehabilitation to meet newly revised criteria may be costly and difficult. A probabilistic safety analysis (PSA) provides a rational safety assessment and decision-making tool managing the various sources of uncertainty that may impact dam performance. Fragility analysis, which depicts fl%e uncertainty in the safety margin above specified hazard levels, is a fundamental tool in a PSA. This study presents a methodology for developing fragilities of concrete gravity dams to assess their performance against hydrologic and seismic hazards. Models of varying degree of complexity and sophistication were considered and compared. The methodology is illustrated using the Bluestone Dam on the New River in West Virginia, which was designed in the late 1930's. The hydrologic fragilities showed that the Eluestone Dam is unlikely to become unstable at the revised probable maximum flood (PMF), but it is likely that there will be significant cracking at the heel ofthe dam. On the other hand, the seismic fragility analysis indicated that sliding is likely, if the dam were to be subjected to a maximum credible earthquake (MCE). Moreover, there will likely be tensile cracking at the neck of the dam at this level of seismic excitation. Probabilities of relatively severe limit states appear to be only marginally affected by extremely rare events (e.g. the PMF and MCE). Moreover, the risks posed by the extreme floods and earthquakes were not balanced for the Bluestone Dam, with seismic hazard posing a relatively higher risk.

The Infinitesimal Jackknife with Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Advanced receptor models for exploiting highly time-resolved data acquired in the EPA supersite preject

NASA Astrophysics Data System (ADS)

Ke, Haohao

Receptor models have been widely used in air quality studies to identify pollution sources and estimate their contributions. A common problem for most current receptor models is insufficient consideration of realistic constraints such as can be obtained from emission inventories, chemical composition profiles of the sources, and the physics of plume dispersion. In addition, poor resolving of collinear sources was often found. With the high quality time-, composition-, and size-resolved measurements during the EPA Supersite project, efforts towards resolving nearby industrial sources were made by combinative use of Positive Matrix Factorization (PMF) and the Pseudo-Deterministic Receptor Model (PDRM). The PMF modeling of Baltimore data in September 2001 revealed coal-fired and oil-fired power plants (CFPP and OFPP, respectively) with significant cross contamination, as indicated by the high Se/Ni ratio in the OFPP profile. Nevertheless, the PMF results provided a good estimate of background and the PMF-constrained emission rates well seeded the trajectory-driven PDRM modeling. Using NOx as the tracer gas for chi/Q tuning, ultimately resolved emissions from individual stacks exhibited acceptable tracer ratios and the emission rates of metals generally agreed with the TRI estimates. This approach was later applied to two metal pollution episodes in St. Louis during in November 2001 and March 2002 and met a similar success. As NOx measurements were unavailable at those metal-production facilities, highly-specific tracer metals (i.e., Cd, Zn, and Cu) for the corresponding units were used to tune chi/Qs and their contributions were well resolved with the PMF-seeded PDRM. Opportunistically a PM2.5 excursion during a windless morning in November 2002 allowed the extraction of an in-situ profile of vehicular emissions in Baltimore. The profiles obtained by direct peak observation, windless model linear regression (WMA), PMF, and UNMIX were comparable and the WMA profile

Factor Retention in Exploratory Factor Analysis: A Comparison of Alternative Methods.

ERIC Educational Resources Information Center

Mumford, Karen R.; Ferron, John M.; Hines, Constance V.; Hogarty, Kristine Y.; Kromrey, Jeffery D.

This study compared the effectiveness of 10 methods of determining the number of factors to retain in exploratory common factor analysis. The 10 methods included the Kaiser rule and a modified Kaiser criterion, 3 variations of parallel analysis, 4 regression-based variations of the scree procedure, and the minimum average partial procedure. The…

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

Investigation on thermochemical behaviour of low rank Malaysian coal, oil palm biomass and their blends during pyrolysis via thermogravimetric analysis (TGA).

PubMed

Idris, Siti Shawalliah; Abd Rahman, Norazah; Ismail, Khudzir; Alias, Azil Bahari; Abd Rashid, Zulkifli; Aris, Mohd Jindra

2010-06-01

This study aims to investigate the behaviour of Malaysian sub-bituminous coal (Mukah Balingian), oil palm biomass (empty fruit bunches (EFB), kernel shell (PKS) and mesocarp fibre (PMF)) and their respective blends during pyrolysis using thermogravimetric analysis (TGA). The coal/palm biomass blends were prepared at six different weight ratios and experiments were carried out under dynamic conditions using nitrogen as inert gas at various heating rates to ramp the temperature from 25 degrees C to 900 degrees C. The derivative thermogravimetric (DTG) results show that thermal decomposition of EFB, PMF and PKS exhibit one, two and three distinct evolution profiles, respectively. Apparently, the thermal profiles of the coal/oil palm biomass blends appear to correlate with the percentage of biomass added in the blends, thus, suggesting lack of interaction between the coal and palm biomass. First-order reaction model were used to determine the kinetics parameters for the pyrolysis of coal, palm biomass and their respective blends. (c) 2010 Elsevier Ltd. All rights reserved.

Sources of fine particle composition in the northeastern US

NASA Astrophysics Data System (ADS)

Song, Xin-Hua; Polissar, Alexandr V.; Hopke, Philip K.

Fine particle composition data obtained at three sampling sites in the northeastern US were studied using a relatively new type of factor analysis, positive matrix factorization (PMF). The three sites are Washington, DC, Brigantine, NJ and Underhill, VT. The PMF method uses the estimates of the error in the data to provide optimal point-by-point weighting and permits efficient treatment of missing and below detection limit values. It also imposes the non-negativity constraint on the factors. Eight, nine and 11 sources were resolved from the Washington, Brigantine and Underhill data, respectively. The factors were normalized by using aerosol fine mass concentration data through multiple linear regression so that the quantitative source contributions for each resolved factor were obtained. Among the sources resolved at the three sites, six are common. These six sources exhibit not only similar chemical compositions, but also similar seasonal variations at all three sites. They are secondary sulfate with a high concentration of S and strong seasonal variation trend peaking in summer time; coal combustion with the presence of S and Se and its seasonal variation peaking in winter time; oil combustion characterized by Ni and V; soil represented by Al, Ca, Fe, K, Si and Ti; incinerator with the presence of Pb and Zn; sea salt with the high concentrations of Na and S. Among the other sources, nitrate (dominated by NO 3-) and motor vehicle (with high concentrations of organic carbon (OC) and elemental carbon (EC), and with the presence of some soil dust components) were obtained for the Washington data, while the three additional sources for the Brigantine data were nitrate, motor vehicle and wood smoke (OC, EC, K). At the Underhill site, five other sources were resolved. They are wood smoke, Canadian Mn, Canadian Cu smelter, Canadian Ni smelter, and another salt source with high concentrations of Cl and Na. A nitrate source similar to that found at the other sites could

Source apportionment of trace metals in river sediments: A comparison of three methods.

PubMed

Chen, Haiyang; Teng, Yanguo; Li, Jiao; Wu, Jin; Wang, Jinsheng

2016-04-01

Increasing trace metal pollution in river sediment poses a significant threat to watershed ecosystem health. Identifying potential sources of sediment metals and apportioning their contributions are of key importance for proposing prevention and control strategies of river pollution. In this study, three advanced multivariate receptor models, factor analysis with nonnegative constraints (FA-NNC), positive matrix factorization (PMF), and multivariate curve resolution weighted-alternating least-squares (MCR-WALS), were comparatively employed for source apportionment of trace metals in river sediments and applied to the Le'an River, a main tributary of Poyang Lake which is the largest freshwater lake in China. The pollution assessment with contamination factor and geoaccumulation index suggested that the river sediments in Le'an River were contaminated severely by trace metals due to human activities. With the three apportionment tools, similar source profiles of trace metals in sediments were extracted. Especially, the MCR-WALS and PMF models produced essentially the same results. Comparatively speaking, the weighted schemes might give better solutions than the unweighted FA-NNC because the uncertainty information of environmental data was considered by PMF and MCR-WALS. Anthropogenic sources were apportioned as the most important pollution sources influencing the sediment metals in Le'an River with contributions of about 90%. Among them, copper tailings occupied the largest contribution (38.4-42.2%), followed by mining wastewater (29.0-33.5%), and agricultural activities (18.2-18.7%). To protect the ecosystem of Le'an River and Poyang Lake, special attention should be paid to the discharges of mining wastewater and the leachates of copper tailing ponds in that region. Copyright © 2015 Elsevier Ltd. All rights reserved.

Improving source identification of Atlanta aerosol using temperature resolved carbon fractions in positive matrix factorization

NASA Astrophysics Data System (ADS)

Kim, Eugene; Hopke, Philip K.; Edgerton, Eric S.

Daily integrated PM 2.5 (particulate matter ⩽2.5 μm in aerodynamic diameter) composition data including eight individual carbon fractions collected at the Jefferson Street monitoring site in Atlanta were analyzed with positive matrix factorization (PMF). Particulate carbon was analyzed using the thermal optical reflectance method that divides carbon into four organic carbon (OC), pyrolized organic carbon (OP), and three elemental carbon (EC) fractions. A total of 529 samples and 28 variables were measured between August 1998 and August 2000. PMF identified 11 sources in this study: sulfate-rich secondary aerosol I (50%), on-road diesel emissions (11%), nitrate-rich secondary aerosol (9%), wood smoke (7%), gasoline vehicle (6%), sulfate-rich secondary aerosol II (6%), metal processing (3%), airborne soil (3%), railroad traffic (3%), cement kiln/carbon-rich (2%), and bus maintenance facility/highway traffic (2%). Differences from previous studies using only the traditional OC and EC data (J. Air Waste Manag. Assoc. 53(2003a)731; Atmos Environ. (2003b)) include four traffic-related combustion sources (gasoline vehicle, on-road diesel, railroad, and bus maintenance facility) containing carbon fractions whose abundances were different between the various sources. This study indicates that the temperature resolved fractional carbon data can be utilized to enhance source apportionment study, especially with respect to the separation of diesel emissions from gasoline vehicle sources. Conditional probability functions using surface wind data and identified source contributions aid the identifications of local point sources.

JAK2 V617F, MPL W515L and JAK2 Exon 12 Mutations in Chinese Patients with Primary Myelofibrosis.

PubMed

Xia, Jun; Lu, Mi-Ze; Jiang, Yuan-Qiang; Yang, Guo-Hua; Zhuang, Yun; Sun, Hong-Li; Shen, Yun-Feng

2012-03-01

JAK2 V617F, MPL W515L and JAK2 exon 12 mutations are novel acquired mutations that induce constitutive cytokine-independent activation of the JAK-STAT pathway in myeloproliferative disorders (MPD). The discovery of these mutations provides novel mechanism for activation of signal transduction in hematopoietic malignancies. This research was to investigate their prevalence in Chinese patients with primary myelofibrosis (PMF). We introduced allele-specific PCR (AS-PCR) combined with sequence analysis to simultaneously screen JAK2 V617F, MPL W515L and JAK2 exon 12 mutations in 30 patients with PMF. Fifteen PMF patients (50.0%) carried JAK2 V617F mutation, and only two JAK2 V617F-negative patients (6.7%) harbored MPL W515L mutation. None had JAK2 exon 12 mutations. Furthermore, these three mutations were not detected in 50 healthy controls. MPL W515L and JAK2 V617F mutations existed in PMF patients but JAK2 exon 12 mutations not. JAK2 V617F and MPL W515L and mutations might contribute to the primary molecular pathogenesis in patients with PMF.

Evaluation of tumor necrosis factor-alpha (TNF) as an exposure or risk marker in three French coal mining regions.

PubMed

Porcher, J M; Oberson, D; Viseux, N; Sébastien, P; Honnons, S; Auburtin, G

1994-01-01

Several studies have shown the crucial role of the tumor necrosis factor-alpha (TNF) in the fibrosis induced by dusts containing silica and its role in the transition from simple pneumoconiosis (CWSP) to progressive massive fibrosis (PMF). To evaluate the nocivity of dust exposure among coal miners (n = 474) from different mining regions in France (e.g., Nord-Pas de Calais, Lorraine, and Provence), spontaneous and LPS or silica-induced TNF released by peripheral blood monocytes was quantified. The primary aim of this effort was to study the link between the prevalence of coal workers pneumoconiosis (CWP) and TNF release. TNF levels were significantly different between active miners from the three regions. However, after correction for age and region, TNF was found not to be related to dust exposure. Interestingly, a very low, homogeneous expression of TNF was observed in the group from Provence. These results are probably related to the absence of pneumoconiosis in this area. A positive relation between profusion and TNF release was found for all stimulants among retired miners with PMF. Although in retired miners TNF release was consistently higher, the design of the study does not allow this effect to be separated from that of age. Both silica and nonstimulated TNF release were found to increase with increasing radiological symptoms; the opposite was found for LPS-induced release.

Electrostatic Ratchet in the Protective Antigen Channel Promotes Anthrax Toxin Translocation*

PubMed Central

Wynia-Smith, Sarah L.; Brown, Michael J.; Chirichella, Gina; Kemalyan, Gigi; Krantz, Bryan A.

2012-01-01

Central to the power-stroke and Brownian-ratchet mechanisms of protein translocation is the process through which nonequilibrium fluctuations are rectified or ratcheted by the molecular motor to transport substrate proteins along a specific axis. We investigated the ratchet mechanism using anthrax toxin as a model. Anthrax toxin is a tripartite toxin comprised of the protective antigen (PA) component, a homooligomeric transmembrane translocase, which translocates two other enzyme components, lethal factor (LF) and edema factor (EF), into the cytosol of the host cell under the proton motive force (PMF). The PA-binding domains of LF and EF (LFN and EFN) possess identical folds and similar solution stabilities; however, EFN translocates ∼10–200-fold slower than LFN, depending on the electrical potential (Δψ) and chemical potential (ΔpH) compositions of the PMF. From an analysis of LFN/EFN chimera proteins, we identified two 10-residue cassettes comprised of charged sequence that were responsible for the impaired translocation kinetics of EFN. These cassettes have nonspecific electrostatic requirements: one surprisingly prefers acidic residues when driven by either a Δψ or a ΔpH; the second requires basic residues only when driven by a Δψ. Through modeling and experiment, we identified a charged surface in the PA channel responsible for charge selectivity. The charged surface latches the substrate and promotes PMF-driven transport. We propose an electrostatic ratchet in the channel, comprised of opposing rings of charged residues, enforces directionality by interacting with charged cassettes in the substrate, thereby generating forces sufficient to drive unfolding. PMID:23115233

Comparison of receptor models for source apportionment of the PM10 in Zaragoza (Spain).

PubMed

Callén, M S; de la Cruz, M T; López, J M; Navarro, M V; Mastral, A M

2009-08-01

Receptor models are useful to understand the chemical and physical characteristics of air pollutants by identifying their sources and by estimating contributions of each source to receptor concentrations. In this work, three receptor models based on principal component analysis with absolute principal component scores (PCA-APCS), Unmix and positive matrix factorization (PMF) were applied to study for the first time the apportionment of the airborne particulate matter less or equal than 10microm (PM10) in Zaragoza, Spain, during 1year sampling campaign (2003-2004). The PM10 samples were characterized regarding their concentrations in inorganic components: trace elements and ions and also organic components: polycyclic aromatic hydrocarbons (PAH) not only in the solid phase but also in the gas phase. A comparison of the three receptor models was carried out in order to do a more robust characterization of the PM10. The three models predicted that the major sources of PM10 in Zaragoza were related to natural sources (60%, 75% and 47%, respectively, for PCA-APCS, Unmix and PMF) although anthropogenic sources also contributed to PM10 (28%, 25% and 39%). With regard to the anthropogenic sources, while PCA and PMF allowed high discrimination in the sources identification associated with different combustion sources such as traffic and industry, fossil fuel, biomass and fuel-oil combustion, heavy traffic and evaporative emissions, the Unmix model only allowed the identification of industry and traffic emissions, evaporative emissions and heavy-duty vehicles. The three models provided good correlations between the experimental and modelled PM10 concentrations with major precision and the closest agreement between the PMF and PCA models.

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

The Effect of a Receding Saline Lake (The Salton Sea) on Airborne Particulate Matter Composition.

PubMed

Frie, Alexander L; Dingle, Justin H; Ying, Samantha C; Bahreini, Roya

2017-08-01

The composition of ambient particulate matter (PM) and its sources were investigated at the Salton Sea, a shrinking saline lake in California. To investigate the influence of playa exposure on PM composition, PM samples were collected during two seasons and at two sites around the Salton Sea. To characterize source composition, soil samples were collected from local playa and desert surfaces. PM and soil samples were analyzed for 15 elements using mass spectrometry and X-ray diffraction. The contribution of sources to PM mass and composition was investigated using Al-referenced enrichment factors (EFs) and source factors resolved from positive matrix factorization (PMF). Playa soils were found to be significantly enriched in Ca, Na, and Se relative to desert soils. PMF analysis resolved the PM 10 data with four source factors, identified as Playa-like, Desert-like, Ca-rich, and Se. Playa-like and desert-like sources were estimated to contribute to a daily average of 8.9% and 45% of PM 10 mass, respectively. Additionally, playa sources were estimated to contribute to 38-68% of PM 10 Na. PM 10 Se concentrations showed strong seasonal variations, suggesting a seasonal cycle of Se volatilization and recondensation. These results support the importance of playas as a source of PM mass and a controlling factor of PM composition.

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Anthropometric data reduction using confirmatory factor analysis.

PubMed

Rohani, Jafri Mohd; Olusegun, Akanbi Gabriel; Rani, Mat Rebi Abdul

2014-01-01

The unavailability of anthropometric data especially in developing countries has remained a limiting factor towards the design of learning facilities with sufficient ergonomic consideration. Attempts to use anthropometric data from developed countries have led to provision of school facilities unfit for the users. The purpose of this paper is to use factor analysis to investigate the suitability of the collected anthropometric data as a database for school design in Nigerian tertiary institutions. Anthropometric data were collected from 288 male students in a Federal Polytechnic in North-West of Nigeria. Their age is between 18-25 years. Nine vertical anthropometric dimensions related to heights were collected using the conventional traditional equipment. Exploratory factor analysis was used to categorize the variables into a model consisting of two factors. Thereafter, confirmatory factor analysis was used to investigate the fit of the data to the proposed model. A just identified model, made of two factors, each with three variables was developed. The variables within the model accounted for 81% of the total variation of the entire data. The model was found to demonstrate adequate validity and reliability. Various measuring indices were used to verify that the model fits the data properly. The final model reveals that stature height and eye height sitting were the most stable variables for designs that have to do with standing and sitting construct. The study has shown the application of factor analysis in anthropometric data analysis. The study highlighted the relevance of these statistical tools to investigate variability among anthropometric data involving diverse population, which has not been widely used for analyzing previous anthropometric data. The collected data is therefore suitable for use while designing for Nigerian students.

Determinants of spirometric abnormalities among silicotic patients in Hong Kong.

PubMed

Leung, Chi C; Chang, Kwok C; Law, Wing S; Yew, Wing W; Tam, Cheuk M; Chan, Chi K; Wong, Man Y

2005-09-01

Silicosis is the second commonest notified occupational disease in Hong Kong. To characterize the determinants of spirometric abnormalities in silicosis. The spirometric patterns of consecutive silicotic patients on confirmation by the Pneumoconiosis Medical Board from 1991 to 2002 were correlated with demographic characteristics, occupational history, smoking history, tuberculosis (TB) history and radiographic features by univariate and multiple regression analyses. Of 1576 silicotic patients included, 55.6% showed normal spirometry, 28.5% normal forced vital capacity (FVC>or=80% predicted) but reduced forced expiratory ratio (FER<70%), 7.6% reduced FVC but normal FER, and 8.4% reduced both FVC and FER. Age, ever-smoking, cigarette pack-years, industry, job type, history of TB, size of lung nodules and progressive massive fibrosis (PMF) were all significantly associated with airflow limitation on univariate analysis (all P<0.05), while sex and profusion of nodules were not. Only age, cigarette pack-years, history of TB, size of lung nodules and PMF remained as significant independent predictors of airflow obstruction in multiple logistic regression analysis. After controlling for airflow obstruction, only shorter exposure duration, history of TB and profusion of nodules were significant independent predictors of reduced FVC. As well as age, history of TB, cigarette pack-years, PMF and nodule size contributed comparable effects to airflow obstruction in multiple linear regression analyses, while profusion of nodules was the strongest factor for reduced vital capacity. In an occupational compensation setting, disease indices and history of tuberculosis are independent predictors of both airflow obstruction and reduced vital capacity for silicotic patients.

Sources of ambient volatile organic compounds and their contributions to photochemical ozone formation at a site in the Pearl River Delta, southern China.

PubMed

Ling, Z H; Guo, H; Cheng, H R; Yu, Y F

2011-10-01

The Positive Matrix Factorization (PMF) receptor model and the Observation Based Model (OBM) were combined to analyze volatile organic compound (VOC) data collected at a suburban site (WQS) in the PRD region. The purposes are to estimate the VOC source apportionment and investigate the contributions of these sources and species of these sources to the O(3) formation in PRD. Ten VOC sources were identified. We further applied the PMF-extracted concentrations of these 10 sources into the OBM and found "solvent usage 1", "diesel vehicular emissions" and "biomass/biofuel burning" contributed most to the O(3) formation at WQS. Among these three sources, higher Relative Incremental Reactivity (RIR)-weighted values of ethene, toluene and m/p-xylene indicated that they were mainly responsible for local O(3) formation in the region. Sensitivity analysis revealed that the sources of "diesel vehicular emissions", "biomass/biofuel burning" and "solvent usage 1" had low uncertainties whereas "gasoline evaporation" showed the highest uncertainty. Copyright © 2011 Elsevier Ltd. All rights reserved.

Chemical characteristics and source apportionment of indoor and outdoor fine particles observed in an urban environment in Korea

NASA Astrophysics Data System (ADS)

Heo, J.; Yi, S. M.

2016-12-01

Paired indoor-outdoor fine particulate matter (PM2.5) samples were collected at subway stations, underground shopping centers, and schools in Seoul metropolitan over a 4-year period between 2004 and 2007. Relationships between indoor and outdoor PM2.5 chemical species were determined and source contributions to indoor and outdoor PM2.5 mass were estimated using a positive matrix factorization (PMF) model. The PM2.5 samples were analyzed for major chemical components including organic carbon and elemental carbon, ions, and metals, and the results were used in the PMF model. The levels of the PM2.5 mass and its chemical components observed at the indoor sites were higher than those at the outdoor sites. Indoor levels of ions (i.e. sulfate, nitrate, ammonium), elemental carbon, and several metals (i.e. Fe, Zn, and Cu) were found to be significantly affected by outdoor sources. Very high indoor-to-outdoor mass ratio of these chemical components, in particular, were observed, representing the significant impacts of outdoor sources on indoor levels of them. Seven sources (secondary sulfate, secondary nitrate, mobile, biomass burning, roadway emissions, dust, and sea salt) were resolved by the PMF model at both of the indoor and outdoor sites. The secondary inorganic aerosol (i.e. secondary sulfate and nitrate) and the mobile sources were major contributors to the indoor and outdoor PM2.5, accounting for 47% and 27% of the outdoor PM2.5 and 40% and 25% of the indoor PM2.5, respectively. Furthermore, the contributions of the secondary inorganic aerosol and the mobile sources to the indoor PM2.5 were very comparable to its corresponding contributions to the outdoor PM2.5 levels. The spatial and temporal characteristics of each of sources resolved by the PMF model across the sites were examined using summary statistics, correlation analysis, and coefficient of variation and divergence analysis and the detailed results will be discussed in the presentation.

PM2.5 Source Apportionment: Reconciling Receptor Models for U.S. Nonurban and Urban Long-Term Networks.

PubMed

Chen, L-W Antony; Watson, John G; Chow, Judith C; DuBois, Dave W; Herschberger, Lisa

2011-11-01

Chemical mass balance (CMB) and trajectory receptor models were applied to speciated particulate matter with aerodynamic diameter ≤2.5 μm (PM 2.5 ) measurements from Speciation Trends Network (STN; part of the Chemical Speciation Network [CSN]) and Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring network across the state of Minnesota as part of the Minnesota PM 2.5 Source Apportionment Study (MPSAS). CMB equations were solved by the Unmix, positive matrix factorization (PMF), and effective variance (EV) methods, giving collective source contribution and uncertainty estimates. Geological source profiles developed from local dust materials were either incorporated into the EV-CMB model or used to verify factors derived from Unmix and PMF. Common sources include soil dust, calcium (Ca)-rich dust, diesel and gasoline vehicle exhausts, biomass burning, secondary sulfate, and secondary nitrate. Secondary sulfate and nitrate aerosols dominate PM 2.5 mass (50-69%). Mobile sources outweigh area sources at urban sites, and vice versa at rural sites due to traffic emissions. Gasoline and diesel contributions can be separated using data from the STN, despite significant uncertainties. Major differences between MPSAS and earlier studies on similar environments appear to be the type and magnitude of stationary sources, but these sources are generally minor (<7%) in this and other studies. Ensemble back-trajectory analysis shows that the lower Midwestern states are the predominant source region for secondary ammoniated sulfate in Minnesota. It also suggests substantial contributions of biomass burning and soil dust from out-of-state on occasions, although a quantitative separation of local and regional contributions was not achieved in the current study. Supplemental materials are available for this article. Go to the publisher's online edition of the Journal of the Air & Waste Management Association for a summary of input data, Unmix and PMF factor

Comparisons of Exploratory and Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Daniel, Larry G.

Historically, most researchers conducting factor analysis have used exploratory methods. However, more recently, confirmatory factor analytic methods have been developed that can directly test theory either during factor rotation using "best fit" rotation methods or during factor extraction, as with the LISREL computer programs developed…

Bootstrap Standard Error Estimates in Dynamic Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Browne, Michael W.

2010-01-01

Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the…

How Factor Analysis Can Be Used in Classification.

ERIC Educational Resources Information Center

Harman, Harry H.

This is a methodological study that suggests a taxometric technique for objective classification of yeasts. It makes use of the minres method of factor analysis and groups strains of yeast according to their factor profiles. The similarities are judged in the higher-dimensional space determined by the factor analysis, but otherwise rely on the…

Identification and quantification of indoor air pollutant sources within a residential academic campus.

PubMed

Suryawanshi, Shalini; Chauhan, Amit Singh; Verma, Ritika; Gupta, Tarun

2016-11-01

There is a growing concern regarding the adverse health effects due to indoor air pollution in developing countries including India. Hence, it becomes important to study the causes and sources of indoor air pollutants. This study presents the indoor concentrations of PM0.6 (particles with aerodynamic diameter less than 0.6μm) and identifies sources leading to indoor air pollution. Indoor air samples were collected at IIT Kanpur campus. Ninety-eight PM0.6 samples were collected during November 2013 to September 2014. PM0.6 concentration was measured using a single stage impactor type PM0.6 sampler. The average PM0.6 concentration indoor was about 94.44μg/m(3). Samples collected were then analysed for metal concentrations using ICP-OES (Inductively Coupled Plasma - Optical Emission Spectrometer). Eight metals Ba, Ca, Cr, Cu, Fe, Mg, Ni and Pb were quantified from PM samples using ICP-OES. Positive Matrix Factorization (PMF) was used for source apportionment of indoor air pollution. PMF is a factor analysis tool which helps in resolving the profile and contribution of the sources from an unknown mixture. Five possible sources of indoor pollutants were identified by factor analysis - (1) Coal combustion (21.8%) (2) Tobacco smoking (9.8%) (3) Wall dust (25.7%) (4) Soil particles (17.5%) (5) Wooden furniture/paper products (25.2%). Copyright © 2016 Elsevier B.V. All rights reserved.

PM10 source apportionment in Milan (Italy) using time-resolved data.

PubMed

Bernardoni, Vera; Vecchi, Roberta; Valli, Gianluigi; Piazzalunga, Andrea; Fermo, Paola

2011-10-15

In this work Positive Matrix Factorization (PMF) was applied to 4-hour resolved PM10 data collected in Milan (Italy) during summer and winter 2006. PM10 characterisation included elements (Mg-Pb), main inorganic ions (NH(4)(+), NO(3)(-), SO(4)(2-)), levoglucosan and its isomers (mannosan and galactosan), and organic and elemental carbon (OC and EC). PMF resolved seven factors that were assigned to construction works, re-suspended dust, secondary sulphate, traffic, industry, secondary nitrate, and wood burning. Multi Linear Regression was applied to obtain the PM10 source apportionment. The 4-hour temporal resolution allowed the estimation of the factor contributions during peculiar episodes, which would have not been detected with the traditional 24-hour sampling strategy. Copyright © 2011 Elsevier B.V. All rights reserved.

Organic carbon at a remote site of the western Mediterranean Basin: sources and chemistry during the ChArMEx SOP2 field experiment

NASA Astrophysics Data System (ADS)

Michoud, Vincent; Sciare, Jean; Sauvage, Stéphane; Dusanter, Sébastien; Léonardis, Thierry; Gros, Valérie; Kalogridis, Cerise; Zannoni, Nora; Féron, Anaïs; Petit, Jean-Eudes; Crenn, Vincent; Baisnée, Dominique; Sarda-Estève, Roland; Bonnaire, Nicolas; Marchand, Nicolas; Langley DeWitt, H.; Pey, Jorge; Colomb, Aurélie; Gheusi, François; Szidat, Sonke; Stavroulas, Iasonas; Borbon, Agnès; Locoge, Nadine

2017-07-01

The ChArMEx (Chemistry and Aerosols Mediterranean Experiments) SOP2 (special observation period 2) field campaign took place from 15 July to 5 August 2013 in the western Mediterranean Basin at Ersa, a remote site in Cape Corse. During the campaign more than 80 volatile organic compounds (VOCs), including oxygenated species, were measured by different online and offline techniques. At the same time, an exhaustive description of the chemical composition of fine aerosols was performed with an aerosol chemical speciation monitor (ACSM). Low levels of anthropogenic VOCs (typically tens to hundreds of parts per trillion for individual species) and black carbon (0.1-0.9 µg m-3) were observed, while significant levels of biogenic species (peaking at the ppb level) were measured. Furthermore, secondary oxygenated VOCs (OVOCs) largely dominated the VOC speciation during the campaign, while organic matter (OM) dominated the aerosol chemical composition, representing 55 % of the total mass of non-refractory PM1 on average (average of 3.74 ± 1.80 µg m-3), followed by sulfate (27 %, 1.83 ± 1.06 µg m-3), ammonium (13 %, 0.90 ± 0.55 µg m-3) and nitrate (5 %, 0.31 ± 0.18 µg m-3). Positive matrix factorization (PMF) and concentration field (CF) analyses were performed on a database containing 42 VOCs (or grouped VOCs), including OVOCs, to identify the covariation factors of compounds that are representative of primary emissions or chemical transformation processes. A six-factor solution was found for the PMF analysis, including a primary and secondary biogenic factor correlated with temperature and exhibiting a clear diurnal profile. In addition, three anthropogenic factors characterized by compounds with various lifetimes and/or sources have been identified (long-lived, medium-lived and short-lived anthropogenic factors). The anthropogenic nature of these factors was confirmed by the CF analysis, which identified potential source areas known for intense anthropogenic

Assessing the impact of climate and land use changes on extreme floods in a large tropical catchment

NASA Astrophysics Data System (ADS)

Jothityangkoon, Chatchai; Hirunteeyakul, Chow; Boonrawd, Kowit; Sivapalan, Murugesu

2013-05-01

In the wake of the recent catastrophic floods in Thailand, there is considerable concern about the safety of large dams designed and built some 50 years ago. In this paper a distributed rainfall-runoff model appropriate for extreme flood conditions is used to generate revised estimates of the Probable Maximum Flood (PMF) for the Upper Ping River catchment (area 26,386 km2) in northern Thailand, upstream of location of the large Bhumipol Dam. The model has two components: a continuous water balance model based on a configuration of parameters estimated from climate, soil and vegetation data and a distributed flood routing model based on non-linear storage-discharge relationships of the river network under extreme flood conditions. The model is implemented under several alternative scenarios regarding the Probable Maximum Precipitation (PMP) estimates and is also used to estimate the potential effects of both climate change and land use and land cover changes on the extreme floods. These new estimates are compared against estimates using other hydrological models, including the application of the original prediction methods under current conditions. Model simulations and sensitivity analyses indicate that a reasonable Probable Maximum Flood (PMF) at the dam site is 6311 m3/s, which is only slightly higher than the original design flood of 6000 m3/s. As part of an uncertainty assessment, the estimated PMF is sensitive to the design method, input PMP, land use changes and the floodplain inundation effect. The increase of PMP depth by 5% can cause a 7.5% increase in PMF. Deforestation by 10%, 20%, 30% can result in PMF increases of 3.1%, 6.2%, 9.2%, respectively. The modest increase of the estimated PMF (to just 6311 m3/s) in spite of these changes is due to the factoring of the hydraulic effects of trees and buildings on the floodplain as the flood situation changes from normal floods to extreme floods, when over-bank flows may be the dominant flooding process, leading

A Review of CEFA Software: Comprehensive Exploratory Factor Analysis Program

ERIC Educational Resources Information Center

Lee, Soon-Mook

2010-01-01

CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…

Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis

NASA Astrophysics Data System (ADS)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. The college students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. However, the results of the exploratory factor analysis indicated that the questionnaire could be revised to improve its construct validity. The goal of this study was to revise the questionnaire and establish its construct validity through a confirmatory factor analysis. In addition, a Rasch analysis was applied to the data to better understand the psychometric properties of the inventory and to further evaluate the construct validity. Results indicated that the final, revised inventory is a valid, reliable, and efficient tool for assessing student metacognition for physics problem solving.

Oil-soluble and water-soluble BTPhens and their europium complexes in octanol/water solutions: interface crossing studied by MD and PMF simulations.

PubMed

Benay, G; Wipff, G

2013-01-31

Bistriazinyl-phenantroline "BTPhen" ligands L display the remarkable feature to complex trivalent lanthanide and actinide ions, with a marked selectivity for the latter. We report on molecular dynamics studies of tetrasubstituted X(4)BTPhens: L(4+) (X = (+)Et(3)NCH(2)-), L(4-) (X = (-)SO(3)Ph-), and L(0) (X = CyMe(4)) and their complexes with Eu(III) in binary octanol/water solutions. Changes in free energies upon interface crossing are also calculated for typical solutes by potential of mean force PMF simulations. The ligands and their complexes partition, as expected, to either the aqueous or the oil phase, depending on the "solubilizing" group X. Furthermore, most of them are found to be surface active. The water-soluble L(4+) and L(4-) ligands and their (L)Eu(NO(3))(3) complexes adsorb at the aqueous side of the interface, more with L(4-) than with L(4+). The oil soluble ligand L(0) is not surface active in its endo-endo form but adsorbs on the oil side of the interface in its most polar endo-exo form, as well as in its protonated L(0)H(+) and complexed (L(0))Eu(NO(3))(3) states. Furthermore, comparing PMFs of the Eu(III) complexes with and without nitric acid shows that acidifying the aqueous phase has different effects, depending on the ligand charge. In particular, acid promotes the Eu(III) extraction by L(0) via the (L(0))(2)Eu(NO(3))(2+) complex, as observed experimentally. Overall, the results point to the importance of interfacial adsorption for the liquid-liquid extraction of trivalent lanthanide and actinide cations by BTPhens and analogues.

Sources of the PM10 aerosol in Flanders, Belgium, and re-assessment of the contribution from wood burning.

PubMed

Maenhaut, Willy; Vermeylen, Reinhilde; Claeys, Magda; Vercauteren, Jordy; Roekens, Edward

2016-08-15

From 30 June 2011 to 2 July 2012 PM10 aerosol samples were simultaneously taken every 4th day at four urban background sites in Flanders, Belgium. The sites were in Antwerpen, Gent, Brugge, and Oostende. The PM10 mass concentration was determined by weighing; organic and elemental carbon (OC and EC) were measured by thermal-optical analysis, the wood burning tracers levoglucosan, mannosan and galactosan were determined by gas chromatography/mass spectrometry, 8 water-soluble ions were measured by ion chromatography, and 15 elements were determined by a combination of inductively coupled plasma atomic emission spectrometry and mass spectrometry. The multi-species dataset was subjected to receptor modeling by PMF. The 10 retained factors (with their overall average percentage contributions to the experimental PM10 mass) were wood burning (9.5%), secondary nitrate (24%), secondary sulfate (12.6%), sea salt (10.0%), aged sea salt (19.2%), crustal matter (9.7%), non-ferrous metals (1.81%), traffic (10.3%), non-exhaust traffic (0.52%), and heavy oil burning (3.0%). The average contributions of wood smoke for the four sites were quite substantial in winter and ranged from 12.5 to 20% for the PM10 mass and from 47 to 64% for PM10 OC. Wood burning appeared to be also a notable source of As, Cd, and Pb. The contribution from wood burning to the PM10 mass and OC was also assessed by making use of levoglucosan as single marker compound and the conversion factors of Schmidl et al. (2008), as done in our previous study on wood burning in Flanders (Maenhaut et al., 2012). However, the apportionments were much lower than those deduced from PMF. It seems that the conversion factors of Schmidl et al. (2008) may not be applicable to wood burning in Flanders. From scatter plots of the PMF-derived wood smoke OC and PM versus levoglucosan, we arrived at conversion factors of 9.7 and 22.6, respectively. Copyright © 2016 Elsevier B.V. All rights reserved.

A comparison study on detection of key geochemical variables and factors through three different types of factor analysis

NASA Astrophysics Data System (ADS)

Hoseinzade, Zohre; Mokhtari, Ahmad Reza

2017-10-01

Large numbers of variables have been measured to explain different phenomena. Factor analysis has widely been used in order to reduce the dimension of datasets. Additionally, the technique has been employed to highlight underlying factors hidden in a complex system. As geochemical studies benefit from multivariate assays, application of this method is widespread in geochemistry. However, the conventional protocols in implementing factor analysis have some drawbacks in spite of their advantages. In the present study, a geochemical dataset including 804 soil samples collected from a mining area in central Iran in order to search for MVT type Pb-Zn deposits was considered to outline geochemical analysis through various fractal methods. Routine factor analysis, sequential factor analysis, and staged factor analysis were applied to the dataset after opening the data with (additive logratio) alr-transformation to extract mineralization factor in the dataset. A comparison between these methods indicated that sequential factor analysis has more clearly revealed MVT paragenesis elements in surface samples with nearly 50% variation in F1. In addition, staged factor analysis has given acceptable results while it is easy to practice. It could detect mineralization related elements while larger factor loadings are given to these elements resulting in better pronunciation of mineralization.

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

Long term fine aerosol analysis by XRF and PIXE techniques in the city of Rijeka, Croatia

NASA Astrophysics Data System (ADS)

Ivošević, Tatjana; Orlić, Ivica; Radović, Iva Bogdanović

2015-11-01

The results of a long term, multi elemental XRF and PIXE analysis of fine aerosol pollution in the city of Rijeka, Croatia, are reported for the first time. The samples were collected during a seven months period (6th Aug 2013-28th Feb 2014) on thin stretched Teflon filters and analyzed by energy dispersive X-ray fluorescence (EDXRF) at the Laboratory for Elemental Micro-Analysis (LEMA), University of Rijeka and by Particle Induced X-ray Emission (PIXE) using 1.6 MeV protons at the Laboratory for Ion Beam Interactions (LIBI), Ruđer Bošković Institute, Zagreb. The newly developed micro-XRF system at LEMA provided results for 19 elements in the range from Si to Pb. The PIXE at the LIBI provided information for the same elements as well for the light elements such as Na, Mg and Al. Black carbon was determined with the Laser Integrated Plate Method (LIPM). The results were statistically evaluated by means of the positive matrix factorization (PMF). The seven major pollution sources were identified together with their relative contributions, these are: secondary sulfates, road traffic, smoke, road dust, sea spray, ship emissions and soil dust.

Using BMDP and SPSS for a Q factor analysis.

PubMed

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Likelihood-Based Confidence Intervals in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Oort, Frans J.

2011-01-01

In exploratory or unrestricted factor analysis, all factor loadings are free to be estimated. In oblique solutions, the correlations between common factors are free to be estimated as well. The purpose of this article is to show how likelihood-based confidence intervals can be obtained for rotated factor loadings and factor correlations, by…

What School Psychologists Need to Know about Factor Analysis

ERIC Educational Resources Information Center

McGill, Ryan J.; Dombrowski, Stefan C.

2017-01-01

Factor analysis is a versatile class of psychometric techniques used by researchers to provide insight into the psychological dimensions (factors) that may account for the relationships among variables in a given dataset. The primary goal of a factor analysis is to determine a more parsimonious set of variables (i.e., fewer than the number of…

Item Factor Analysis: Current Approaches and Future Directions

ERIC Educational Resources Information Center

Wirth, R. J.; Edwards, Michael C.

2007-01-01

The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA)…

Q-Type Factor Analysis of Healthy Aged Men.

ERIC Educational Resources Information Center

Kleban, Morton H.

Q-type factor analysis was used to re-analyze baseline data collected in 1957, on 47 men aged 65-91. Q-type analysis is the use of factor methods to study persons rather than tests. Although 550 variables were originally studied involving psychiatry, medicine, cerebral metabolism and chemistry, personality, audiometry, dichotic and diotic memory,…

Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Source apportionment of VOCs in the Los Angeles area using positive matrix factorization

NASA Astrophysics Data System (ADS)

Brown, Steven G.; Frankel, Anna; Hafner, Hilary R.

Eight 3-h speciated hydrocarbon measurements were collected daily by the South Coast Air Quality Management District (SCAQMD) as part of the Photochemical Assessment Monitoring Stations (PAMS) program during the summers of 2001-03 at two sites in the Los Angeles air basin, Azusa and Hawthorne. Over 30 hydrocarbons from over 500 samples at Azusa and 600 samples at Hawthorne were subsequently analyzed using the multivariate receptor model positive matrix factorization (PMF). At Azusa and Hawthorne, five and six factors were identified, respectively, with a good comparison between predicted and measured mass. At Azusa, evaporative emissions (a median of 31% of the total mass), motor vehicle exhaust (22%), liquid/unburned gasoline (27%), coatings (17%), and biogenic emissions (3%) factors were identified. Factors identified at Hawthorne were evaporative emissions (a median of 34% of the total mass), motor vehicle exhaust (24%), industrial process losses (15%), natural gas (13%), liquid/unburned gasoline (13%), and biogenic emissions (1%). Together, the median contribution from mobile source-related factors (exhaust, evaporative emissions, and liquid/unburned gasoline) was 80% and 71% at Azusa and Hawthorne, respectively, similar to previous source apportionment results using the chemical mass balance (CMB) model. There is a difference in the distribution among mobile source factors compared to the CMB work, with an increase in the contribution from evaporative emissions, though the cause (changes in emissions or differences between models) is unknown.

Mixture Factor Analysis for Approximating a Nonnormally Distributed Continuous Latent Factor with Continuous and Dichotomous Observed Variables

ERIC Educational Resources Information Center

Wall, Melanie M.; Guo, Jia; Amemiya, Yasuo

2012-01-01

Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus…

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Constrained Source Apportionment of Coarse Particulate Matter and Selected Trace Elements in Three Cities from the Multi-Ethnic Study of Atherosclerosis

PubMed Central

Sturtz, Timothy M.; Adar, Sara D.; Gould, Timothy; Larson, Timothy V.

2016-01-01

PM10-2.5 mass and trace element concentrations were measured in Winston-Salem, Chicago, and St. Paul at up to 60 sites per city during two different seasons in 2010. Positive Matrix Factorization (PMF) was used to explore the underlying sources of variability. Information on previously reported PM10-2.5 tire and brake wear profiles was used to constrain these features in PMF by prior specification of selected species ratios. We also modified PMF to allow for combining the measurements from all three cities into a single model while preserving city-specific soil features. Relatively minor differences were observed between model predictions with and without the prior ratio constraints, increasing confidence in our ability to identify separate brake wear and tire wear features. Brake wear, tire wear, fertilized soil, and re-suspended soil were found to be important sources of copper, zinc, phosphorus, and silicon respectively across all three urban areas. PMID:27468256

Constrained source apportionment of coarse particulate matter and selected trace elements in three cities from the multi-ethnic study of atherosclerosis

NASA Astrophysics Data System (ADS)

Sturtz, Timothy M.; Adar, Sara D.; Gould, Timothy; Larson, Timothy V.

2014-02-01

PM10-2.5 mass and trace element concentrations were measured in Winston-Salem, Chicago, and St. Paul at up to 60 sites per city during two different seasons in 2010. Positive Matrix Factorization (PMF) was used to explore the underlying sources of variability. Information on previously reported PM10-2.5 tire and brake wear profiles was used to constrain these features in PMF by prior specification of selected species ratios. We also modified PMF to allow for combining the measurements from all three cities into a single model while preserving city-specific soil features. Relatively minor differences were observed between model predictions with and without the prior ratio constraints, increasing confidence in our ability to identify separate brake wear and tire wear features. Brake wear, tire wear, fertilized soil, and resuspended soil were found to be important sources of copper, zinc, phosphorus, and silicon, respectively, across all three urban areas.

Derived Basic Ability Factors: A Factor Analysis Replication Study.

ERIC Educational Resources Information Center

Lee, Mickey, M.; Lee, Lynda Newby

The purpose of this study was to replicate the study conducted by Potter, Sagraves, and McDonald to determine whether their recommended analysis could separate criterion variables into similar factors that were stable from year to year and from school to school. The replication samples consisted of all students attending Louisiana State University…

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

PubMed

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors

PubMed Central

Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-01-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection

Generating a Corpus of Mobile Forensic Images for Masquerading user Experimentation.

PubMed

Guido, Mark; Brooks, Marc; Grover, Justin; Katz, Eric; Ondricek, Jared; Rogers, Marcus; Sharpe, Lauren

2016-11-01

The Periodic Mobile Forensics (PMF) system investigates user behavior on mobile devices. It applies forensic techniques to an enterprise mobile infrastructure, utilizing an on-device agent named TractorBeam. The agent collects changed storage locations for later acquisition, reconstruction, and analysis. TractorBeam provides its data to an enterprise infrastructure that consists of a cloud-based queuing service, relational database, and analytical framework for running forensic processes. During a 3-month experiment with Purdue University, TractorBeam was utilized in a simulated operational setting across 34 users to evaluate techniques to identify masquerading users (i.e., users other than the intended device user). The research team surmises that all masqueraders are undesirable to an enterprise, even when a masquerader lacks malicious intent. The PMF system reconstructed 821 forensic images, extracted one million audit events, and accurately detected masqueraders. Evaluation revealed that developed methods reduced storage requirements 50-fold. This paper describes the PMF architecture, performance of TractorBeam throughout the protocol, and results of the masquerading user analysis. © 2016 American Academy of Forensic Sciences.

Different immunophenotypical apoptotic profiles characterise megakaryocytes of essential thrombocythaemia and primary myelofibrosis.

PubMed

Florena, A M; Tripodo, C; Di Bernardo, A; Iannitto, E; Guarnotta, C; Porcasi, R; Ingrao, S; Abbadessa, V; Franco, V

2009-04-01

Essential thrombocythaemia (ET) and primary myelofibrosis (PMF) share some clinical and pathological features, but show different biological behaviour and prognosis. The latest contributions to understanding the nature of these disorders have focused on bone marrow microenvironment remodelling and proliferative stress, recognising megakaryocytes (MKCs) as "key-cells". The aim of this study was to investigate the apoptotic profile of ET and PMF MKCs in order to further characterise the biology of these disorders. Bone marrow biopsy samples from 30 patients with ET, and 30 patients with PMF, were immunophenotypically studied for the expression of pro-apoptotic (Fas, Fas-L, Bax, Bad) and anti-apoptotic (Bcl-2, Bcl-XL, hTERT (human telomerase reverse transcriptase)) molecules and the "executioner" molecule caspase-3. The fraction of MKCs undergoing apoptosis was assessed by deoxynucleotidyl transferase-mediated dUTP nick-end labelling. Only the mitochondrial pathway seemed to be involved in MKC apoptosis. The anti-apoptotic molecule Bcl-XL was predominantly found in ET MKCs (50.5% of ET MKCs versus 35% of PMF MKCs; p = 0.036), while pro-apoptotic molecules Bax and Bad showed a prevalent expression in PMF MKCs (30.5% of ET MKCs versus 55% of PMF MKCs; 41% of ET MKCs versus 52% of PMF MKCs; p = 0.001 and p = 0.068, respectively). A significant fraction of PMF MKCs were committed to apoptosis according to caspase-3 expression and TUNEL, while only few ET cells were committed to apoptosis. hTERT was significantly more expressed in PMF (32% of ET MKCs versus 46% of PMF MKCs; p = 0.022), in agreement with the proliferative nature of this disease. It was found that ET and PMF MKCs, which barely differ in terms of morphology and aggregation, are characterised by markedly different apoptotic profiles. The rather high apoptotic fraction of PMF was able to support the fibrotic nature of this process, while the anti-apoptotic profile of ET cells fits well with their "steady

On the Likelihood Ratio Test for the Number of Factors in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.; Yuan, Ke-Hai

2007-01-01

In the exploratory factor analysis, when the number of factors exceeds the true number of factors, the likelihood ratio test statistic no longer follows the chi-square distribution due to a problem of rank deficiency and nonidentifiability of model parameters. As a result, decisions regarding the number of factors may be incorrect. Several…

A Brief History of the Philosophical Foundations of Exploratory Factor Analysis.

ERIC Educational Resources Information Center

Mulaik, Stanley A.

1987-01-01

Exploratory factor analysis derives its key ideas from many sources, including Aristotle, Francis Bacon, Descartes, Pearson and Yule, and Kant. The conclusions of exploratory factor analysis are never complete without subsequent confirmatory factor analysis. (Author/GDC)

Quantifying sources of black carbon in western North America using observationally based analysis and an emission tagging technique in the Community Atmosphere Model

DOE PAGES

Zhang, Rudong; Wang, Hailong; Hegg, D. A.; ...

2015-11-18

The Community Atmosphere Model (CAM5), equipped with a technique to tag black carbon (BC) emissions by source regions and types, has been employed to establish source–receptor relationships for atmospheric BC and its deposition to snow over western North America. The CAM5 simulation was conducted with meteorological fields constrained by reanalysis for year 2013 when measurements of BC in both near-surface air and snow are available for model evaluation. We find that CAM5 has a significant low bias in predicted mixing ratios of BC in snow but only a small low bias in predicted atmospheric concentrations over northwestern USA and westernmore » Canada. Even with a strong low bias in snow mixing ratios, radiative transfer calculations show that the BC-in-snow darkening effect is substantially larger than the BC dimming effect at the surface by atmospheric BC. Local sources contribute more to near-surface atmospheric BC and to deposition than distant sources, while the latter are more important in the middle and upper troposphere where wet removal is relatively weak. Fossil fuel (FF) is the dominant source type for total column BC burden over the two regions. FF is also the dominant local source type for BC column burden, deposition, and near-surface BC, while for all distant source regions combined the contribution of biomass/biofuel (BB) is larger than FF. An observationally based positive matrix factorization (PMF) analysis of the snow-impurity chemistry is conducted to quantitatively evaluate the CAM5 BC source-type attribution. Furthermore, while CAM5 is qualitatively consistent with the PMF analysis with respect to partitioning of BC originating from BB and FF emissions, it significantly underestimates the relative contribution of BB. In addition to a possible low bias in BB emissions used in the simulation, the model is likely missing a significant source of snow darkening from local soil found in the observations.« less

Monte Carlo-based calibration and uncertainty analysis of a coupled plant growth and hydrological model

NASA Astrophysics Data System (ADS)

Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.

2014-04-01

Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures - for example, by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow for a more detailed analysis of the dynamic behaviour of the soil-plant interface. We coupled two of such high-process-oriented independent models and calibrated both models simultaneously. The catchment modelling framework (CMF) simulated soil hydrology based on the Richards equation and the van Genuchten-Mualem model of the soil hydraulic properties. CMF was coupled with the plant growth modelling framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo-based generalized likelihood uncertainty estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from a uniform distribution. The model was applied to three sites with different management in Müncheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matter of roots, storages, stems and leaves. The shape parameter of the retention curve n was highly constrained, whereas other parameters of the retention curve showed a large equifinality. We attribute this slightly poorer model performance to missing leaf senescence, which is currently not implemented in PMF. The most constrained parameters for the

Hand function evaluation: a factor analysis study.

PubMed

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

Source apportionment vs. emission inventories of non-methane hydrocarbons (NMHC) in an urban area of the Middle East: local and global perspectives

NASA Astrophysics Data System (ADS)

Salameh, T.; Sauvage, S.; Afif, C.; Borbon, A.; Locoge, N.

2015-10-01

We applied the Positive Matrix Factorization model to two large datasets collected during two intensive measurement campaigns (summer 2011 and winter 2012) at a sub-urban site in Beirut, Lebanon, in order to identify NMHC sources and quantify their contribution to ambient levels. Six factors were identified in winter and five factors in summer. PMF-resolved source profiles were consistent with source profiles established by near-field measurements. The major sources were traffic-related emissions (combustion and gasoline evaporation) in winter and in summer accounting for 51 and 74 wt % respectively in agreement with the national emission inventory. The gasoline evaporation related to traffic source had a significant contribution regardless of the season (22 wt % in winter and 30 wt % in summer). The NMHC emissions from road transport are estimated from observations and PMF results, and compared to local and global emission inventories. The national road transport inventory shows lowest emissions than the ones from PMF but with a reasonable difference lower than 50 %. Global inventories show higher discrepancies with lower emissions up to a factor of 10 for the transportation sector. When combining emission inventory to our results, there is a strong evidence that control measures in Lebanon should be targeted on mitigating the NMHC emissions from the traffic-related sources. From a global perspective, an assessment of VOC anthropogenic emission inventories for the Middle East region as a whole seems necessary as these emissions could be much higher than expected at least from the road transport sector. Highlights: - PMF model was applied to identify major NMHC sources and their seasonal variation. - Gasoline evaporation accounts for more than 40 % both in winter and in summer. - NMHC urban emissions are dominated by traffic related sources in both seasons. - Agreement with the emission inventory regarding the relative contribution of the on-road mobile source but

Fine particulate matter associated with monsoonal effect and the responses of biomass fire hotspots in the tropical environment

NASA Astrophysics Data System (ADS)

Khan, M. F.; Latif, M. T.; Saw, W. H.; Amil, N.; Nadzir, M. S. M.; Sahani, M.; Tahir, N. M.; Chung, J. X.

2015-08-01

The health implications of PM2.5 in tropical regions of Southeast Asia are significant as PM2.5 can pose serious health concerns. PM2.5 is strongly influenced by the monsoon. We quantitatively characterize the health risks posed to human populations by selected heavy metals in PM2.5. Monsoonal effects as well as factors influencing the sources of PM2.5 were also determined. Apportionment analysis of PM2.5 was undertaken using US EPA positive matrix factorization (PMF) 5.0 and a mass closure model. Overall, 48 % of the samples exceeded the World Health Organization (WHO) 24 h guideline. The mass closure model identified four sources of PM2.5: (a) mineral matter (MIN) (35 %), (b) secondary inorganic aerosol (SIA) (11 %), (c) sea salt (SS) (7 %), (d) trace elements (TE) (2 %) and (e) undefined (UD) (45 %). PMF 5.0 identified five potential sources and motor vehicle emissions and biomass burning were dominant followed by marine and sulfate aerosol, coal burning, nitrate aerosol, and mineral and road dust. The non-carcinogenic risk level for four selected metals (Pb, As, Cd and Ni) in PM2.5 and in the identified major sources by PMF > 5.0, with respect to inhalation follows the order of PM2.5 > coal burning > motor vehicle emissions/biomass burning > mineral/road dust. The lifetime cancer risk follows the order of As > Ni > Pb > Cd for mineral/road dust, coal burning and overall of PM2.5 concentration and As > Pb > Ni > Cd for motor vehicle/biomass burning. Overall, the associated cancer risk posed by the exposure of toxic metals in PM2.5 is three to four in 1 000 000 people in this location.

Source apportionment of wet-deposited atmospheric mercury in Tampa, Florida

NASA Astrophysics Data System (ADS)

Michael, Ryan; Stuart, Amy L.; Trotz, Maya A.; Akiwumi, Fenda

2016-03-01

In this paper, sources of mercury deposition to the Tampa area (Florida, USA) are investigated by analysis of one year (March 2000-March 2001) of daily wet deposition data. HYSPLIT back-trajectory modeling was performed to assess potential source locations for high versus low concentration events in data stratified by precipitation level. Positive matrix factorization (PMF) was also applied to apportion the elemental compositions from each event and to identify sources. Increased total mercury deposition was observed during summer months, corresponding to increased precipitation. However, mercury concentration in deposited samples was not strongly correlated with precipitation amount. Back-trajectories show air masses passing over Florida land in the short (12 h) and medium (24 h) term prior to deposition for high mercury concentration events. PMF results indicate that eleven factors contribute to the deposited elements in the event data. Diagnosed elemental profiles suggest the sources that contribute to mercury wet deposition at the study site are coal combustion (52% of the deposited mercury mass), municipal waste incineration (23%), medical waste incineration (19%), and crustal dust (6%). Overall, results suggest that sources local to the county and in Florida likely contributed substantially to mercury deposition at the study site, but distant sources may also contribute.

Prognostication in Philadelphia Chromosome Negative Myeloproliferative Neoplasms: a Review of the Recent Literature.

PubMed

Zhou, Amy; Afzal, Amber; Oh, Stephen T

2017-10-01

The prognosis for patients with Philadelphia chromosome (Ph)-negative myeloproliferative neoplasms (MPNs) is highly variable. All Ph-negative MPNs carry an increased risk for thrombotic complications, bleeding, and leukemic transformation. Several clinical, biological, and molecular prognostic factors have been identified in recent years, which provide important information in guiding management of patients with Ph-negative MPNs. In this review, we critically evaluate the recent published literature and discuss important new developments in clinical and molecular factors that impact survival, disease transformation, and thrombosis in patients with polycythemia vera, essential thrombocythemia, and primary myelofibrosis. Recent studies have identified several clinical factors and non-driver mutations to have prognostic impact on Ph-negative MPNs independent of conventional risk stratification and prognostic models. In polycythemia vera (PV), leukocytosis, abnormal karyotype, phlebotomy requirement on hydroxyurea, increased bone marrow fibrosis, and mutations in ASXL1, SRSF2, and IDH2 were identified as additional adverse prognostic factors. In essential thrombocythemia (ET), JAK2 V617F mutation, splenomegaly, and mutations in SH2B3, SF3B1, U2AF1, TP53, IDH2, and EZH2 were found to be additional negative prognostic factors. Bone marrow fibrosis and mutations in ASXL1, SRSF2, EZH2, and IDH1/2 have been found to be additional prognostic factors in primary myelofibrosis (PMF). CALR mutations appear to be a favorable prognostic factor in PMF, which has not been clearly demonstrated in ET. The prognosis for patients with PV, ET, and PMF is dependent upon the presence or absence of several clinical, biological, and molecular risk factors. The significance of additional risk factors identified in these recent studies will need further validation in prospective studies to determine how they may be best utilized in the management of these disorders.

Multivariate analysis of prognostic factors in synovial sarcoma.

PubMed

Koh, Kyoung Hwan; Cho, Eun Yoon; Kim, Dong Wook; Seo, Sung Wook

2009-11-01

Many studies have described the diversity of synovial sarcoma in terms of its biological characteristics and clinical features. Moreover, much effort has been expended on the identification of prognostic factors because of unpredictable behaviors of synovial sarcomas. However, with the exception of tumor size, published results have been inconsistent. We attempted to identify independent risk factors using survival analysis. Forty-one consecutive patients with synovial sarcoma were prospectively followed from January 1997 to March 2008. Overall and progression-free survival for age, sex, tumor size, tumor location, metastasis at presentation, histologic subtype, chemotherapy, radiation therapy, and resection margin were analyzed, and standard multivariate Cox proportional hazard regression analysis was used to evaluate potential prognostic factors. Tumor size (>5 cm), nonlimb-based tumors, metastasis at presentation, and a monophasic subtype were associated with poorer overall survival. Multivariate analysis showed metastasis at presentation and monophasic tumor subtype affected overall survival. For the progression-free survival, monophasic subtype was found to be only 1 prognostic factor. The study confirmed that histologic subtype is the single most important independent prognostic factors of synovial sarcoma regardless of tumor stage.

Spinal atypical protein kinase C activity is necessary to stabilize inactivity-induced phrenic motor facilitation

PubMed Central

Strey, K.A.; Nichols, N.L.; Baertsch, N.A.; Broytman, O.; Baker-Herman, T.L.

2012-01-01

The neural network controlling breathing must establish rhythmic motor output at a level adequate to sustain life. Reduced respiratory neural activity elicits a novel form of plasticity in circuits driving the diaphragm known as inactivity-induced phrenic motor facilitation (iPMF), a rebound increase in phrenic inspiratory output observed once respiratory neural drive is restored. The mechanisms underlying iPMF are unknown. Here, we demonstrate in anesthetized rats that spinal mechanisms give rise to iPMF, and that iPMF consists of at least two mechanistically distinct phases: 1) an early, labile phase that requires atypical PKC (PKCζ and/or PKCΙ/λ) activity to transition to a 2) late, stable phase. Early (but not late) iPMF is associated with increased interactions between PKCζ/Ι and the scaffolding protein ZIP/p62 in spinal regions associated with the phrenic motor pool. Although PKCζ/Ι activity is necessary for iPMF, spinal aPKC activity is not necessary for phrenic long-term facilitation (pLTF) following acute intermittent hypoxia, an activity-independent form of spinal respiratory plasticity. Thus, while iPMF and pLTF both manifest as prolonged increases in phrenic burst amplitude, they arise from distinct spinal cellular pathways. Our data are consistent with the hypotheses that: 1) local mechanisms sense and respond to reduced respiratory-related activity in the phrenic motor pool, and 2) inactivity-induced increases in phrenic inspiratory output require local PKCζ/Ι activity to stabilize into a long-lasting iPMF. Although the physiological role of iPMF is unknown, we suspect that iPMF represents a compensatory mechanism, assuring adequate motor output in a physiological system where prolonged inactivity ends life. PMID:23152633

Correction of the Abnormal Trafficking of Primary Myelofibrosis CD34+ Cells by Treatment with Chromatin Modifying Agents

PubMed Central

Wang, Xiaoli; Zhang, Wei; Ishii, Takefumi; Sozer, Selcuk; Wang, Jiapeng; Xu, Mingjiang; Hoffman, Ronald

2011-01-01

The abnormal trafficking of CD34+ cells is a unique characteristic of primary myelofibrosis (PMF). We have further studied the behavior of PMF CD34+ cells by examining their homing to the marrow and the spleens of NOD/SCID mice. Following the infusion of PMF and normal G-CSF mobilized peripheral blood (mPB) CD34+ cells into NOD/SCID mice, reduced numbers of PMF CD34+ cells and CFU-GM as compared to mPB were detected in the marrow of these mice while similar numbers of PMF and mPB CD34+ cells and CFU-GM homed to their spleens. The abnormal homing of PMF CD34+ cells was associated with reduced expression of CXCR4, but was not related to the presence of JAK2V617F. The sequential treatment of PMF CD34+ cell with the chromatin modifying agents, 5-aza-2'-deoxycytidine (5azaD) and trichostatin A (TSA) but not treatment with small molecule inhibitors of JAK2 resulted in the generation of increased numbers of CD34+CXCR4+ cells which was accompanied by enhanced homing of PMF CD34+ cells to the marrow but not the spleens of NOD/SCID mice. Following 5azaD/TSA treatment JAK2V617F negative PMF hematopoietic progenitor cells preferentially homed to the marrow but not the spleens of recipient mice. Our data suggest that PMF CD34+ cells are characterized by a reduced ability to home to the marrow but not the spleens of NOD/SCID mice and that this homing defect can be corrected by sequential treatment with chromatin modifying agents. PMID:19752087

Citrus peel extracts attenuated obesity and modulated gut microbiota in mice with high-fat diet-induced obesity.

PubMed

Tung, Yen-Chen; Chang, Wei-Tien; Li, Shiming; Wu, Jia-Ching; Badmeav, Vladimir; Ho, Chi-Tang; Pan, Min-Hsiung

2018-06-01

Polymethoxyflavones (PMFs) and hydroxyl PMFs (HOPMFs) are mainly found in citrus peel and have shown anti-obesity potential in in vitro and in vivo studies. Herein, we have investigated the anti-obesity effects of two citrus peel extracts obtained via supercritical fluid extraction: PMF A, with a lower content of PMFs and HOPMFs, and PMF B, with a higher content of PMFs and HOPMFs. PMF A and PMF B were administered orally for 16 weeks to mice with high fat diet (HFD)-induced obesity. The results showed that PMF B decreased the lipid content more statistically significantly (p < 0.05) than PMF A in 3T3-L1 preadipocytes, reduced the adipocyte size, decreased the adipose tissue weight and alleviated the total body weight in the HFD mice. Both PMF A and PMF B reduced the adipocyte size in the perigonadal fat by markedly decreasing the levels of lipid droplets (LD) and perilipin 1 protein and Sterol regulatory element binding protein 1 (SREBP-1) expression. Compared to the case of the HFD group, PMF B altered the gut microbiota by increasing Prevotella and decreasing rc4-4 bacteria. The change in the composition of gut microbiota, the community of symbiotic and pathogenic microorganisms, may determine the metabolic health and be responsible for the anti-obesity mechanism. Our results indicate that the citrus peel extracts decrease lipid accumulation both in vivo and in vitro and should be considered for the management of overweight and obesity conditions.

Factor Analysis for Clustered Observations.

ERIC Educational Resources Information Center

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

Merkle, L. A.; Layne, C. S.; Bloomberg, J. J.; Zhang, J. J.

1998-01-01

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

Background PM2.5 source apportionment in the remote Northwestern United States

NASA Astrophysics Data System (ADS)

Hadley, Odelle L.

2017-10-01

This study used the Environmental Protection Agency's positive matrix factorization model (EPA PMF5.0) to identify five primary source factors contributing to the ambient PM2.5 concentrations at Cheeka Peak Atmospheric Observatory (CPO), Neah Bay WA between January 2011 and December 2014. CPO is home to both an IMPROVE (Interagency Monitoring for Protected Visual Environments) and a NCore multi-pollutant monitoring site. Chemically resolved particulate data from the IMPROVE site was the input data to EPA PMF5.0 and the resulting source factors were derived solely from these data. Solutions from the model were analyzed in context with trace gas and meteorological data collected at the NCore site located roughly 10 m away. Seasonal and long-term trends were analyzed for all five factors and provide the first complete source apportionment analysis of PM2.5 at this remote location. The first factor, identified as marine-traffic residual fuel oil (RFO), was the highest contributor to PM2.5 during late summer. Over the 4-year analysis, the RFO percent contribution to total PM2.5 declined. This is consistent with previous studies and may be attributed to regulations restricting the sulfur content of ship fuel. Biomass combustion emissions (BMC) and sea salt were the largest PM2.5 sources observed at CPO in winter, accounting for over 80% of the fine particulate. BMC accounted for a large percent of the fine particulate pollution when winds were easterly, or continental. Sea salt was the dominant winter factor when winds blew from the west. Measured trace carbon monoxide (CO) and reactive nitrogen species (NOy) were most strongly correlated with the BMC factor and continental winds. The fourth factor was identified as aged crustal material, or dust. In all three years, dust peaked in the spring and was associated exclusively with north-easterly winds. The last factor was identified as aged sea salt mixed with nitrate, sulfate, and other components common to RFO and BMC

A Factor Analysis of the BSRI and the PAQ.

ERIC Educational Resources Information Center

Edwards, Teresa A.; And Others

Factor analysis of the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) was undertaken to study the independence of the masculine and feminine scales within each instrument. Both instruments were administered to undergraduate education majors. Analysis of primary first and second order factors of the BSRI indicated…

High-resolution sampling and analysis of ambient particulate matter in the Pearl River Delta region of southern China: source apportionment and health risk implications

NASA Astrophysics Data System (ADS)

Zhou, Shengzhen; Davy, Perry K.; Huang, Minjuan; Duan, Jingbo; Wang, Xuemei; Fan, Qi; Chang, Ming; Liu, Yiming; Chen, Weihua; Xie, Shanju; Ancelet, Travis; Trompetter, William J.

2018-02-01

Hazardous air pollutants, such as trace elements in particulate matter (PM), are known or highly suspected to cause detrimental effects on human health. To understand the sources and associated risks of PM to human health, hourly time-integrated major trace elements in size-segregated coarse (PM2.5-10) and fine (PM2.5) particulate matter were collected at the industrial city of Foshan in the Pearl River Delta region, China. Receptor modeling of the data set by positive matrix factorization (PMF) was used to identify six sources contributing to PM2.5 and PM10 concentrations at the site. Dominant sources included industrial coal combustion, secondary inorganic aerosol, motor vehicles and construction dust along with two intermittent sources (biomass combustion and marine aerosol). The biomass combustion source was found to be a significant contributor to peak PM2.5 episodes along with motor vehicles and industrial coal combustion. Conditional probability function (CPF) analysis was applied to estimate the source locations using the PMF-resolved source contribution coupled with the surface wind direction data. Health exposure risk of hazardous trace elements (Pb, As, Si, Cr, Mn and Ni) and source-specific values were estimated. The total hazard quotient (HQ) of PM2.5 was 2.09, higher than the acceptable limit (HQ = 1). The total carcinogenic risk (CR) was 3.37 × 10-3 for PM2.5, which was 3 times higher than the least stringent limit (1.0 × 10-4). Among the selected trace elements, As and Pb posed the highest non-carcinogenic and carcinogenic risks to human health, respectively. In addition, our results show that the industrial coal combustion source is the dominant non-carcinogenic and carcinogenic risk contributor, highlighting the need for stringent control of this source. This study provides new insight for policy makers to prioritize sources in air quality management and health risk reduction.

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

Factors affecting job satisfaction in nurse faculty: a meta-analysis.

PubMed

Gormley, Denise K

2003-04-01

Evidence in the literature suggests job satisfaction can make a difference in keeping qualified workers on the job, but little research has been conducted focusing specifically on nursing faculty. Several studies have examined nurse faculty satisfaction in relationship to one or two influencing factors. These factors include professional autonomy, leader role expectations, organizational climate, perceived role conflict and role ambiguity, leadership behaviors, and organizational characteristics. This meta-analysis attempts to synthesize the various studies conducted on job satisfaction in nursing faculty and analyze which influencing factors have the greatest effect. The procedure used for this meta-analysis consisted of reviewing studies to identify factors influencing job satisfaction, research questions, sample size reported, instruments used for measurement of job satisfaction and influencing factors, and results of statistical analysis.

The Recoverability of P-Technique Factor Analysis

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…

Influence of pulsed magnetic field on soybean (Glycine max L.) seed germination, seedling growth and soil microbial population.

PubMed

Radhakrishnan, Ramalingam; Kumari, Bollipo Dyana Ranjitha

2013-08-01

The effects of pulsed magnetic field (PMF) treatment of soybean (Glycine max L. cv CO3) seeds were investigated on rate of seed germination, seedling growth, physico-chemical properties of seed leachates and soil microbial population under laboratory conditions. Seeds were exposed to PMF of 1500 nT at 0.1, 1.0 10.0 and 100.0 Hz for 5 h per day for 20 days, induced by enclosure coil systems. Non-treated seeds were considered as controls. All PMF treatments significantly increased the rate of seed germination, while 10 and 100 Hz PMFs showed the most effective response. The 1.0 and 10 Hz PMFs remarkably improved the fresh weight of shoots and roots, leaf area and plant height from seedlings from magnetically-exposed seeds compared to the control, while 10 Hz PMF increased the total soluble sugar, total protein and phenol contents. The leaf chlorophyll a, b and total chlorophyll were higher in PMF (10 and 100 Hz) pretreated plants, as compared to other treatments. In addition, activities of alpha-amylase, acid phosphatase, alkaline phosphatase, nitrate reductase, peroxidase and polyphenoloxidase were increased, while beta-amylase and protease activities were declined in PMF (10 Hz)-exposed soybean plants. Similarly, the capacity of absorbance of water by seeds and electrical conductivity of seed leachates were significantly enhanced by 10 Hz PMF exposure, whereas PMF (10 Hz) pretreated plants did not affect the microbial population in rhizosphere soil. The results suggested the potential of 10 Hz PMF treatment to enhance the germination and seedling growth of soybean.

Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong

2010-01-01

This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…

Donor retention in health care in Iran: a factor analysis

PubMed Central

Aghababa, Sara; Nasiripour, Amir Ashkan; Maleki, Mohammadreza; Gohari, Mahmoodreza

2017-01-01

Background: Long-term financial support is essential for the survival of a charitable organization. Health charities need to identify the effective factors influencing donor retention. Methods: In the present study, the items of a questionnaire were derived from both literature review and semi-structured interviews related to donor retention. Using a purposive sampling, 300 academic and executive practitioners were selected. After the follow- up, a total of 243 usable questionnaires were prepared for factor analysis. The questionnaire was validated based on the face and content validity and reliability through Cronbach’s α-coefficient. Results: The results of exploratory factor analysis extracted 2 factors for retention: donor factor (variance = 33.841%; Cronbach’s α-coefficient = 90.2) and charity factor (variance = 29.038%; Cronbach’s α-coefficient = 82.8), respectively. Subsequently, confirmatory factor analysis was applied to support the overall reasonable fit. Conclusions: In this study, it was found that repeated monetary donations are supplied to the charitable organizations when both aspects of donor factor (retention factor and charity factor) for retention are taken into consideration. This model could provide a perspective for making sustainable donations and charitable giving PMID:28955663

The Factor Structure of the English Language Development Assessment: A Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Kuriakose, Anju

2011-01-01

This study investigated the internal factor structure of the English language development Assessment (ELDA) using confirmatory factor analysis. ELDA is an English language proficiency test developed by a consortium of multiple states and is used to identify and reclassify English language learners in kindergarten to grade 12. Scores on item…

Influential Observations in Principal Factor Analysis.

ERIC Educational Resources Information Center

Tanaka, Yutaka; Odaka, Yoshimasa

1989-01-01

A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)

Protein kinase Cɛ inhibition restores megakaryocytic differentiation of hematopoietic progenitors from primary myelofibrosis patients.

PubMed

Masselli, E; Carubbi, C; Gobbi, G; Mirandola, P; Galli, D; Martini, S; Bonomini, S; Crugnola, M; Craviotto, L; Aversa, F; Vitale, M

2015-11-01

Among the three classic Philadelphia chromosome-negative myeloproliferative neoplasms, primary myelofibrosis (PMF) is the most severe in terms of disease biology, survival and quality of life. Abnormalities in the process of differentiation of PMF megakaryocytes (MKs) are a hallmark of the disease. Nevertheless, the molecular events that lead to aberrant megakaryocytopoiesis have yet to be clarified. Protein kinase Cɛ (PKCɛ) is a novel serine/threonine kinase that is overexpressed in a variety of cancers, promoting aggressive phenotype, invasiveness and drug resistance. Our previous findings on the role of PKCɛ in normal (erythroid and megakaryocytic commitment) and malignant (acute myeloid leukemia) hematopoiesis prompted us to investigate whether it could be involved in the pathogenesis of PMF MK-impaired differentiation. We demonstrate that PMF megakaryocytic cultures express higher levels of PKCɛ than healthy donors, which correlate with higher disease burden but not with JAK2V617F mutation. Inhibition of PKCɛ function (by a negative regulator of PKCɛ translocation) or translation (by target small hairpin RNA) leads to reduction in PMF cell growth, restoration of PMF MK differentiation and inhibition of PKCɛ-related anti-apoptotic signaling (Bcl-xL). Our data suggest that targeting PKCɛ directly affects the PMF neoplastic clone and represent a proof-of-concept for PKCɛ inhibition as a novel therapeutic strategy in PMF.

Biomass burning and biogenic aerosols in northern Australia during the SAFIRED campaign

NASA Astrophysics Data System (ADS)

Milic, Andelija; Mallet, Marc D.; Cravigan, Luke T.; Alroe, Joel; Ristovski, Zoran D.; Selleck, Paul; Lawson, Sarah J.; Ward, Jason; Desservettaz, Maximilien J.; Paton-Walsh, Clare; Williams, Leah R.; Keywood, Melita D.; Miljevic, Branka

2017-03-01

There is a lack of knowledge of how biomass burning aerosols in the tropics age, including those in the fire-prone Northern Territory in Australia. This paper reports chemical characterization of fresh and aged aerosols monitored during the 1-month-long SAFIRED (Savannah Fires in the Early Dry Season) field study, with an emphasis on the chemical signature and aging of organic aerosols. The campaign took place in June 2014 during the early dry season when the surface measurement site, the Australian Tropical Atmospheric Research Station (ATARS), located in the Northern Territory, was heavily influenced by thousands of wild and prescribed bushfires. ATARS was equipped with a wide suite of instrumentation for gaseous and aerosol characterization. A compact time-of-flight aerosol mass spectrometer was deployed to monitor aerosol chemical composition. Approximately 90 % of submicron non-refractory mass was composed of organic material. Ozone enhancement in biomass burning plumes indicated increased air mass photochemistry. The diversity in biomass burning emissions was illustrated through variability in chemical signature (e.g. wide range in f44, from 0.06 to 0.18) for five intense fire events. The background particulate loading was characterized using positive matrix factorization (PMF). A PMF-resolved BBOA (biomass burning organic aerosol) factor comprised 24 % of the submicron non-refractory organic aerosol mass, confirming the significance of fire sources. A dominant PMF factor, OOA (oxygenated organic aerosol), made up 47 % of the sampled aerosol, illustrating the importance of aerosol aging in the Northern Territory. Biogenic isoprene-derived organic aerosol factor was the third significant fraction of the background aerosol (28 %).

Depletion of proton motive force by nisin in Listeria monocytogenes cells.

PubMed

Bruno, M E; Kaiser, A; Montville, T J

1992-07-01

The basal proton motive force (PMF) levels and the influence of the bacteriocin nisin on the PMF were determined in Listeria monocytogenes Scott A. In the absence of nisin, the interconversion of the pH gradient (Z delta pH) and the membrane potential (delta psi) led to the maintenance of a fairly constant PMF at -160 mV over the external pH range 5.5 to 7.0. The addition of nisin at concentrations of greater than or equal to 5 micrograms/ml completely dissipated PMF in cells at external pH values of 5.5 and 7.0. With 1 microgram of nisin per ml, delta pH was completely dissipated but delta psi decreased only slightly. The action of nisin on PMF in L. monocytogenes Scott A was both time and concentration dependent. Valinomycin depleted only delta pH, whereas nigericin and carbonyl cyanide m-chlorophenylhydrazone depleted only delta psi, under conditions in which nisin depleted both. Four other L. monocytogenes strains had basal PMF parameters similar to those of strain Scott A. Nisin (2.5 micrograms/ml) also completely dissipated PMF in these strains.

Pulsed magnetic field: a contemporary approach offers to enhance plant growth and yield of soybean.

PubMed

Radhakrishnan, Ramalingam; Ranjitha Kumari, Bollipo Diana

2012-02-01

The possible involvement of pulsed magnetic field (PMF) pretreatment in development and yield of soybean was investigated. Seeds were subjected to 20 days with 1500 nT at 10.0 Hz of PMF for 5 h per day. PMF pretreatment increased the plant height, fresh and dry weight, and protein content with the changes of protein profile in 8 days old seedlings. In addition, activity of enzymes such as β-amylase, acid phosphatase, polyphenol oxidase and catalase was enhanced while α-amylase, alkaline phosphatase, protease and nitrate reductase activities declined due to PMF exposure. However, a considerable increment of Fe, Cu, Mn, Zn, Mg, K and Na contents with reduced level of Ca was found in PMF treated seedlings. The number of leaves, pods, seeds and length of pods, and weight of seeds were also remarkably higher in PMF treatment in contrast to controls. The results suggest that pretreatment of PMF plays important roles in improvement of crop productivity of soybean through the enhancement of protein, mineral accumulation and enzyme activities which leads to increase the growth and yield. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Potential of mean force between like-charged nanoparticles: Many-body effect

NASA Astrophysics Data System (ADS)

Zhang, Xi; Zhang, Jin-Si; Shi, Ya-Zhou; Zhu, Xiao-Long; Tan, Zhi-Jie

2016-03-01

Ion-mediated interaction is important for the properties of polyelectrolytes such as colloids and nucleic acids. The effective pair interactions between two polyelectrolytes have been investigated extensively, but the many-body effect for multiple polyelectrolytes still remains elusive. In this work, the many-body effect in potential of mean force (PMF) between like-charged nanoparticles in various salt solutions has been comprehensively examined by Monte Carlo simulation and the nonlinear Poisson-Boltzmann theory. Our calculations show that, at high 1:1 salt, the PMF is weakly repulsive and appears additive, while at low 1:1 salt, the additive assumption overestimates the repulsive many-body PMF. At low 2:2 salt, the pair PMF appears weakly repulsive while the many-body PMF can become attractive. In contrast, at high 2:2 salt, the pair PMF is apparently attractive while the many-body effect can cause a weaker attractive PMF than that from the additive assumption. Our microscopic analyses suggest that the elusive many-body effect is attributed to ion-binding which is sensitive to ion concentration, ion valence, number of nanoparticles and charges on nanoparticles.

Application of factor analysis to the water quality in reservoirs

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this work we present a Factor Analysis of chemical and environmental variables of the water column and hydro-morphological features of several Portuguese reservoirs. The objective is to reduce the initial number of variables, keeping their common characteristics. Using the Factor Analysis, the environmental variables measured in the epilimnion and in the hypolimnion, together with the hydromorphological characteristics of the dams were reduced from 63 variables to only 13 factors, which explained a total of 83.348% of the variance in the original data. After performing rotation using the Varimax method, the relations between the factors and the original variables got clearer and more explainable, which provided a Factor Analysis model for these environmental variables using 13 varifactors: Water quality and distance to the source, Hypolimnion chemical composition, Sulfite-reducing bacteria and nutrients, Coliforms and faecal streptococci, Reservoir depth, Temperature, Location, among other factors.

Persistent type II endoleak after EVAR: the predictive value of the AAA thrombus volume.

PubMed

Gallitto, Enrico; Gargiulo, Mauro; Mascoli, Chiara; Freyrie, Antonio; DE Matteis, Massimo; Serra, Carla; Bianchini Massoni, Claudio; Faggioli, Gianluca; Stella, Andrea

2018-02-01

Persistent type II endoleaks (ELIIp, ≥6 months) after an endovascular aneurysm repair (EVAR) can be associated with adverse outcomes. The aims of this study are the evaluation of the incidence of ELIIp, their preoperative morphological predictive features (PMF) and the post-EVAR abdominal aortic aneurysm (AAA) evolution in the presence of ELIIp. Patients underwent EVAR between 2008 and 2010 were prospectively collected. Cases with ELIIp (group A: AG) were identified. A control group without ELIIp (group B: BG), homogeneous for clinical characteristics, follow-up timing and methods (CTA and/or CEUS at 6.12 months and yearly thereafter) was retrospectively selected. The PMF evaluated by computed-tomography-angiography (CTA) were: AAA-diameter, number and diameter of AAA efferent patent vessels (EPV), AAA-total volume (TV), AAA-thrombus volume (THV) and TV/THV rate (%VR). Volumes were calculated by the dedicated vessels analysis software. AG and BG were compared. The primary endpoint was to evaluate the incidence of ELIIp. Secondary endpoints were to analyze the relation between PMF and ELIIp and to assess the post-EVAR AAA-evolution in the presence of ELIIp. Between 2008 and 2010, 200 patients underwent EVAR to treat AAA electively. An ELIIp was detected in 35cases (17.5%) (AG). Twenty-seven patients (13.5%) were included in BG. An overall of 62 patients (GA+GB) were analyzed. The mean pre-operative AAA diameter and EPV were 58±11.6 mm and 5.5±1.8 mm, respectively. The mean TV and THV were 187±111.5 cc and 82±75 cc, respectively. The median %VR was 42.3%. ELIIp was correlated to EPV≥6 (χ2, p=.015) and %VR <40% (logistic regression, P=0.032). The mean follow-up was 22±9 months. Seven (20%) ELIIp spontaneously sealed and 6 (17%) required reinterventions (2 conversions to OR). There were not PMF associated to ELIIp evolution and AAA growth post-EVAR. ELIIp is a not rare complication and it could require re-interventions. Our data suggest that VEP≥6 or %VT<40

Computational active site analysis of molecular pathways to improve functional classification of enzymes.

PubMed

Ozyurt, A Sinem; Selby, Thomas L

2008-07-01

This study describes a method to computationally assess the function of homologous enzymes through small molecule binding interaction energy. Three experimentally determined X-ray structures and four enzyme models from ornithine cyclo-deaminase, alanine dehydrogenase, and mu-crystallin were used in combination with nine small molecules to derive a function score (FS) for each enzyme-model combination. While energy values varied for a single molecule-enzyme combination due to differences in the active sites, we observe that the binding energies for the entire pathway were proportional for each set of small molecules investigated. This proportionality of energies for a reaction pathway appears to be dependent on the amino acids in the active site and their direct interactions with the small molecules, which allows a function score (FS) to be calculated to assess the specificity of each enzyme. Potential of mean force (PMF) calculations were used to obtain the energies, and the resulting FS values demonstrate that a measurement of function may be obtained using differences between these PMF values. Additionally, limitations of this method are discussed based on: (a) larger substrates with significant conformational flexibility; (b) low homology enzymes; and (c) open active sites. This method should be useful in accurately predicting specificity for single enzymes that have multiple steps in their reactions and in high throughput computational methods to accurately annotate uncharacterized proteins based on active site interaction analysis. 2008 Wiley-Liss, Inc.

The role of the extracellular matrix in primary myelofibrosis

PubMed Central

Leiva, O; Ng, S K; Chitalia, S; Balduini, A; Matsuura, S; Ravid, K

2017-01-01

Primary myelofibrosis (PMF) is a myeloproliferative neoplasm that arises from clonal proliferation of hematopoietic stem cells and leads to progressive bone marrow (BM) fibrosis. While cellular mutations involved in the development of PMF have been heavily investigated, noteworthy is the important role the extracellular matrix (ECM) plays in the progression of BM fibrosis. This review surveys ECM proteins contributors of PMF, and highlights how better understanding of the control of the ECM within the BM niche may lead to combined therapeutic options in PMF. PMID:28157219

Progressive massive fibrosis in patients with pneumoconiosis: utility of MRI in differentiating from lung cancer.

PubMed

Ogihara, Yukihiro; Ashizawa, Kazuto; Hayashi, Hideyuki; Nagayasu, Takeshi; Hayashi, Tomayoshi; Honda, Sumihisa; Uetani, Masataka

2018-01-01

Background It is occasionally difficult to distinguish progressive massive fibrosis (PMF) from lung cancer on computed tomography (CT) in patients with pneumoconiosis. Purpose To evaluate the magnetic resonance imaging (MRI) features of PMF and to assess its ability to differentiate PMF from lung cancer. Material and Methods Between 2000 and 2014, 40 pulmonary lesions suspected to be lung cancer on the basis of CT in 28 patients with known pneumoconiosis were evaluated. Twenty-four of the 40 lesions were pathologically or clinically diagnosed as PMF. The signal pattern on T2-weighted (T2W) images, post-contrast enhancement pattern on T1-weighted (T1W) images, and the pattern of the time intensity curve (TIC) on contrast-enhanced dynamic studies were evaluated. All images were analyzed independently by two chest radiologists. Results All 24 PMF lesions showed low signal intensity (SI) on T2W images (sensitivity, 100%), while 15 of 16 lung cancer lesions showed intermediate or high SI on T2W images (specificity, 94%) when PMF was regarded as a positive result. Six of 17 PMF lesions showed a homogeneous enhancement pattern (sensitivity, 35%), and 4/9 lung cancer lesions showed an inhomogeneous or a ring-like enhancement pattern (specificity, 44%). Six of 16 PMF lesions showed a gradually increasing enhancement pattern (sensitivity, 38%), and 7/9 lung cancer lesions showed rapid enhancement pattern (specificity, 78%). Conclusion When differentiation between PMF and lung cancer in patients with pneumoconiosis is difficult on CT, an additional MRI study, particularly the T2W imaging sequence, may help differentiate between the two.

Clinical course and outcome of essential thrombocythemia and prefibrotic myelofibrosis according to the revised WHO 2016 diagnostic criteria

PubMed Central

Rumi, Elisa; Boveri, Emanuela; Bellini, Marta; Pietra, Daniela; Ferretti, Virginia V.; Sant’Antonio, Emanuela; Cavalloni, Chiara; Casetti, Ilaria C.; Roncoroni, Elisa; Ciboddo, Michele; Benvenuti, Pietro; Landini, Benedetta; Fugazza, Elena; Troletti, Daniela; Astori, Cesare; Cazzola, Mario

2017-01-01

The recently revised World Health Organization (WHO) classification of myeloid neoplasms recognizes prefibrotic myelofibrosis (prePMF) as a distinct entity, characterized by well-defined histopathologic features together with minor clinical criteria (leukocytes, anemia, increased LDH, splenomegaly). The aim of the study was to examine the clinical relevance of distinguishing prePMF from essential thrombocythemia (ET). We identified in our database all patients affected with ET, prePMF and primary myelofibrosis (PMF) diagnosed according to 2008 WHO criteria with a bone marrow fibrosis grade 0-1 at diagnosis and one DNA sample to define the mutational status. The bone marrow morphology of all 404 identified patients was reviewed by an expert pathologist and patients were reclassified according to the 2016 WHO criteria. After reclassification, our cohort included 269 ET, 109 prePMF, and 26 myeloproliferative neoplasm unclassificable. In comparison with ET, patients with prePMF had higher leukocyte count, lower hemoglobin level, higher platelet count, higher LDH values, and higher number of circulating CD34-positive cells; they showed more frequently splenomegaly (all P values < ·001). CALR mutations were more frequent in prePMF than in ET (35·8% vs 17·8%, P < ·001). PrePMF patients had shorter overall survival (P < ·001) and a trend to a higher incidence of leukemic evolution (P ·067) compared to ET patients, while they did not differ in terms of thrombotic and bleeding complications. In conclusion, ET and prePMF diagnosed according to 2016 WHO criteria are two entities with a different clinical phenotype at diagnosis and a different clinical outcome. PMID:29254200

A rapid, highly accurate method for quantifying CALR mutant allele burden in persons with myeloproliferative neoplasms.

PubMed

Yao, Qiu-Mei; Zhou, Jiao; Gale, Robert Peter; Li, Jin-Lan; Li, Ling-Di; Li, Ning; Chen, Shan-Shan; Ruan, Guo-Rui

2015-10-01

Calreticulin (CALR) mutations were recently identified in a substantial proportion of persons with essential thrombocythemia (ET) and with primary myelofibrosis (PMF) without JAK2(V617F). Consequently rapid, sensitive, and specific methods to detect and quantify these mutations are needed. We studied samples from 1088 persons with myeloproliferative neoplasms (MPNs) including 421 JAK2(V617F) negative subjects with ET, PMF, polycythemia vera (PV), chronic myeloid leukemia (CML) and hyper-eosinophilic syndrome (HES). Detection of CALR exon 9 mutations was done by PCR amplification followed by fragment length analysis and direct sequencing. Dilution assays were used to determine CALR mutant allele burden. We detected CALR mutations in blood and bone marrow samples from 152 subjects with ET and with PMF but not in samples from normal or persons with PV, CML, or HES. CALR mutant peaks were distinct from wild-type peaks and dilution experiments indicated a sensitivity level of 0.5-5% for a CALR mutant allele in a wild-type background. Diverse types of mutations were detected including deletions, insertions, and complex indels. All mutations were confirmed by direct sequencing. We also used dilution experiments to quantify mutant allele burden. We were able to reproducibly detect mutant allele levels as low 5% (0.5-5%) in a wild-type background. PCR amplification followed by fragment length analysis is a rapid, sensitive, and specific method for screening persons with MPNs for CALR mutations, especially those with ET and PMF and for estimating mutant allele burden.

A replication of a factor analysis of motivations for trapping

USGS Publications Warehouse

Schroeder, Susan; Fulton, David C.

2015-01-01

Using a 2013 sample of Minnesota trappers, we employed confirmatory factor analysis to replicate an exploratory factor analysis of trapping motivations conducted by Daigle, Muth, Zwick, and Glass (1998).  We employed the same 25 items used by Daigle et al. and tested the same five-factor structure using a recent sample of Minnesota trappers. We also compared motivations in our sample to those reported by Daigle et el.

Advanced receptor modelling for the apportionment of road dust resuspension to atmospheric PM

NASA Astrophysics Data System (ADS)

Amato, F.; Pandolfi, M.; Escrig, A.; Querol, X.; Alastuey, A.; Pey, J.; Perez, N.; Hopke, P. K.

2009-04-01

Fugitive emissions from traffic resuspension can often represent an important source of atmospheric particulate matter in urban environments, especially when the scarce precipitations favour the accumulation of road dust. Resuspension of road dust can lead to high exposures to heavy metals, metalloids and mineral matter. Knowing the amount of its contribution to atmospheric PM is a key task for establishing eventual mitigation or preventive measures. Factor analysis techniques are widely used tools for atmospheric aerosol source apportionment, based on the mass conservation principle. Paatero and Tapper (1993) suggested the use of a Weighted Least Squares scheme with the aim of obtaining a minimum variance solution. Additionally they proposed to incorporate the basic physical constraint of non negativity, calling their approach Positive Matrix Factorization (PMF), which can be performed by the program PMF2 released by Paatero (1997). Nevertheless, Positive Matrix Factorization can be either solved with the Multilinear Engine (ME-2), a more flexible program, also developed by Paatero (1999), which can solve any model consisting in sum of products of unknowns. The main difference with PMF2 is that ME-2 does not solve only well-defined tasks, but its actions are defined in a "script file" written in a special-purpose programming language, allowing incorporating additional tasks such as data processing etc. Thus in ME-2 a priori information, e.g. chemical fingerprints can be included as auxiliary terms of the object function to be minimized. This feature of ME-2 make it especially suitable for source apportionment studies where some knowledge (chemical ratios, profiles, mass conservation etc) of involved sources is available. The aim of this study was to quantify the contribution of road dust resuspension in PM10, PM2.5 and PM1 data set from Barcelona (Spain). Given that recently the emission profile of local road dust was characterized (Amato et al., in press

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

DEVELOPMENT AND EVALUATION OF PM 2.5 SOURCE APPORTIONMENT METHODOLOGIES

EPA Science Inventory

The receptor model called Positive Matrix Factorization (PMF) has been extensively used to apportion sources of ambient fine particulate matter (PM_2.5), but the accuracy of source apportionment results currently remains unknown. In addition, air quality forecast model...

Development of chicken embryos in a pulsed magnetic field.

PubMed

Berman, E; Chacon, L; House, D; Koch, B A; Koch, W E; Leal, J; Løvtrup, S; Mantiply, E; Martin, A H; Martucci, G I

1990-01-01

Six independent experiments of common design were performed in laboratories in Canada, Spain, Sweden, and the United States of America. Fertilized eggs of domestic chickens were incubated as controls or in a pulsed magnetic field (PMF); embryos were then examined for developmental anomalies. Identical equipment in each laboratory consisted of two incubators, each containing a Helmholtz coil and electronic devices to develop, control, and monitor the pulsed field and to monitor temperature, relative humidity, and vibrations. A unipolar, pulsed, magnetic field (500-microseconds pulse duration, 100 pulses per s, 1-microT peak density, and 2-microseconds rise and fall time) was applied to experimental eggs during 48 h of incubation. In each laboratory, ten eggs were simultaneously sham exposed in a control incubator (pulse generator not activated) while the PMF was applied to ten eggs in the other incubator. The procedure was repeated ten times in each laboratory, and incubators were alternately used as a control device or as an active source of the PMF. After a 48-h exposure, the eggs were evaluated for fertility. All embryos were then assayed in the blind for development, morphology, and stage of maturity. In five of six laboratories, more exposed embryos exhibited structural anomalies than did controls, although putatively significant differences were observed in only two laboratories (two-tailed Ps of .03 and less than .001), and the significance of the difference in a third laboratory was only marginal (two-tailed P = .08). When the data from all six laboratories are pooled, the difference in incidence of abnormalities in PMF-exposed embryos (approximately 25 percent) and that of controls (approximately 19 percent), although small, is highly significant, as is the interaction between incidence of abnormalities and laboratory site (both Ps less than .001). The factor or factors responsible for the marked variability of inter-laboratory differences are unknown.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

PubMed Central

Sediyama, Cristina Y. N.; Moura, Ricardo; Garcia, Marina S.; da Silva, Antonio G.; Soraggi, Carolina; Neves, Fernando S.; Albuquerque, Maicon R.; Whiteside, Setephen P.; Malloy-Diniz, Leandro F.

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS. PMID:28484414

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale.

PubMed

Sediyama, Cristina Y N; Moura, Ricardo; Garcia, Marina S; da Silva, Antonio G; Soraggi, Carolina; Neves, Fernando S; Albuquerque, Maicon R; Whiteside, Setephen P; Malloy-Diniz, Leandro F

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach's alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

A Factor Analysis of Learning Data and Selected Ability Test Scores

ERIC Educational Resources Information Center

Jones, Dorothy L.

1976-01-01

A verbal concept-learning task permitting the externalizing and quantifying of learning behavior and 16 ability tests were administered to female graduate students. Data were analyzed by alpha factor analysis and incomplete image analysis. Six alpha factors and 12 image factors were extracted and orthogonally rotated. Four areas of cognitive…

Biological risk factors for suicidal behaviors: a meta-analysis

PubMed Central

Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K

2016-01-01

Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09–1.81) and suicide death (wOR=1.28; CI: 1.13–1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias—cytokines (wOR=2.87; CI: 1.40–5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01–1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors. PMID:27622931

[Master files: less paper, more substance. Special rules for special medicines: Plasma Master File and Vaccine Antigen Master File].

PubMed

Seitz, Rainer; Haase, M

2008-07-01

The process of reviewing the European pharmaceutical legislation resulted in a codex, which contains two new instruments related to marketing authorisation of biological medicines: Plasma Master File (PMF) and Vaccine Antigen Master File (VAMF). In the manufacture of plasma derivatives (e. g. coagulation factors, albumin, immunoglobulins), usually the same starting material, i. e. a plasma pool, is used for several products. In the case of vaccines, the same active substance, i.e. vaccine antigen, may be included in several combination vaccine products. The intention behind the introduction of PMF and VAMF was to avoid unnecessary and redundant documentation, and to improve and harmonise assessment by means of procedures for certification of master files on the community level.

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

PubMed

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

Human Factors Vehicle Displacement Analysis: Engineering In Motion

NASA Technical Reports Server (NTRS)

Atencio, Laura Ashley; Reynolds, David; Robertson, Clay

2010-01-01

While positioned on the launch pad at the Kennedy Space Center, tall stacked launch vehicles are exposed to the natural environment. Varying directional winds and vortex shedding causes the vehicle to sway in an oscillating motion. The Human Factors team recognizes that vehicle sway may hinder ground crew operation, impact the ground system designs, and ultimately affect launch availability . The objective of this study is to physically simulate predicted oscillation envelopes identified by analysis. and conduct a Human Factors Analysis to assess the ability to carry out essential Upper Stage (US) ground operator tasks based on predicted vehicle motion.

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

Life cycle assessment of segregating fattening pig urine and feces compared to conventional liquid manure management.

PubMed

De Vries, Jerke W; Aarnink, André J A; Groot Koerkamp, Peter W G; De Boer, Imke J M

2013-02-05

Gaseous emissions from in-house storage of liquid animal manure remain a major contributor to the environmental impact of manure management. Our aim was to assess the life cycle environmental consequences and reduction potential of segregating fattening pig urine and feces with an innovative V-belt system and to compare it to conventional liquid manure management, that is, the reference. Moreover, we aimed at analyzing the uncertainty of the outcomes related to applied emission factors. We compared a reference with two scenarios: segregation with solid, aerobically, stored feces and with liquid, anaerobically, stored feces. Results showed that, compared to the reference, segregation reduced climate change (CC) up to 82%, due to lower methane emission, reduced terrestrial acidification (TA) and particulate matter formation (PMF) up to 49%, through lower ammonia emission, but increased marine eutrophication up to 11% through nitrogen oxide emission from storage and nitrate leaching after field application. Fossil fuel depletion did not change. Segregation with liquid feces revealed lower environmental impact than segregation with solid feces. Uncertainty analysis supported the conclusion that segregating fattening pig urine and feces significantly reduced CC and additionally segregation with liquid feces significantly reduced TA and PMF compared to the reference.

Pharmaceutical manufacturing facility discharges can substantially increase the pharmaceutical load to U.S. wastewaters

USGS Publications Warehouse

Scott, Tia-Marie; Phillips, Patrick J.; Kolpin, Dana W.; Colella, Kaitlyn M.; Furlong, Edward T.; Foreman, William T.; Gray, James L.

2018-01-01

Discharges from pharmaceutical manufacturing facilities (PMFs) previously have been identified as important sources of pharmaceuticals to the environment. Yet few studies are available to establish the influence of PMFs on the pharmaceutical source contribution to wastewater treatment plants (WWTPs) and waterways at the national scale. Consequently, a national network of 13 WWTPs receiving PMF discharges, six WWTPs with no PMF input, and one WWTP that transitioned through a PMF closure were selected from across the United States to assess the influence of PMF inputs on pharmaceutical loading to WWTPs. Effluent samples were analyzed for 120 pharmaceuticals and pharmaceutical degradates. Of these, 33 pharmaceuticals had concentrations substantially higher in PMF-influenced effluent (maximum 555,000 ng/L) compared to effluent from control sites (maximum 175 ng/L). Concentrations in WWTP receiving PMF input are variable, as discharges from PMFs are episodic, indicating that production activities can vary substantially over relatively short (several months) periods and have the potential to rapidly transition to other pharmaceutical products. Results show that PMFs are an important, national-scale source of pharmaceuticals to the environment.

Myeloproliferative Neoplasms in Children.

PubMed

Hofmann, Inga

2015-09-01

Myeloproliferative neoplasms (MPN) are a group of clonal hematopoietic stem cell disorders characterized by aberrant proliferation of one or more myeloid lineages often with increased immature cells in the peripheral blood. The three classical BCR-ABL-negative MPNs are: 1) polycythemia vera (PV), 2) essential thrombocythemia (ET), and 3) primary myelofibrosis (PMF), which are typically disorders of older adults and are exceedingly rare in children. The diagnostic criteria for MPNs remain largely defined by clinical, laboratory and histopathology assessments in adults, but they have been applied to the pediatric population. The discovery of the JAK2 V617F mutation, and more recently, MPL and CALR mutations, are major landmarks in the understanding of MPNs. Nevertheless, they rarely occur in children, posing a significant diagnostic challenge given the lack of an objective, clonal marker. Therefore, in pediatric patients, the diagnosis must rely heavily on clinical and laboratory factors, and exclusion of secondary disorders to make an accurate diagnosis of MPN. This review focuses on the clinical presentation, diagnostic work up, differential diagnosis, treatment and prognosis of the classical BCR-ABL-negative MPNs (PV, ET and PMF) in children and highlights key differences to the adult diseases. Particular attention will be given to pediatric PMF, as it is the only disorder of this group that is observed in infants and young children, and in many ways appears to be a unique entity compared to adult PMF.

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

SOURCE APPORTIONMENT RESULTS, UNCERTAINTIES, AND MODELING TOOLS

EPA Science Inventory

Advanced multivariate receptor modeling tools are available from the U.S. Environmental Protection Agency (EPA) that use only speciated sample data to identify and quantify sources of air pollution. EPA has developed both EPA Unmix and EPA Positive Matrix Factorization (PMF) and ...

NOVEL STATISTICAL APPROACH TO EVALUATE SPATIAL DISTRIBUTION OF PM FROM SPECIFIC SOURCE CATEGORIES

EPA Science Inventory

This task addresses aspects of NRC recommendations 10A and 10B. Positive matrix factorization (PMF) is a new statistical techniques for determining the daily contribution to PM mass of specific source categories (auto exhaust, smelters, suspended soil, secondary sulfate, etc.). I...

Estimates of the organic aerosol volatility in a boreal forest using two independent methods

NASA Astrophysics Data System (ADS)

Hong, Juan; Äijälä, Mikko; Häme, Silja A. K.; Hao, Liqing; Duplissy, Jonathan; Heikkinen, Liine M.; Nie, Wei; Mikkilä, Jyri; Kulmala, Markku; Prisle, Nønne L.; Virtanen, Annele; Ehn, Mikael; Paasonen, Pauli; Worsnop, Douglas R.; Riipinen, Ilona; Petäjä, Tuukka; Kerminen, Veli-Matti

2017-03-01

The volatility distribution of secondary organic aerosols that formed and had undergone aging - i.e., the particle mass fractions of semi-volatile, low-volatility and extremely low volatility organic compounds in the particle phase - was characterized in a boreal forest environment of Hyytiälä, southern Finland. This was done by interpreting field measurements using a volatility tandem differential mobility analyzer (VTDMA) with a kinetic evaporation model. The field measurements were performed during April and May 2014. On average, 40 % of the organics in particles were semi-volatile, 34 % were low-volatility organics and 26 % were extremely low volatility organics. The model was, however, very sensitive to the vaporization enthalpies assumed for the organics (ΔHVAP). The best agreement between the observed and modeled temperature dependence of the evaporation was obtained when effective vaporization enthalpy values of 80 kJ mol-1 were assumed. There are several potential reasons for the low effective enthalpy value, including molecular decomposition or dissociation that might occur in the particle phase upon heating, mixture effects and compound-dependent uncertainties in the mass accommodation coefficient. In addition to the VTDMA-based analysis, semi-volatile and low-volatility organic mass fractions were independently determined by applying positive matrix factorization (PMF) to high-resolution aerosol mass spectrometer (HR-AMS) data. The factor separation was based on the oxygenation levels of organics, specifically the relative abundance of mass ions at m/z 43 (f43) and m/z 44 (f44). The mass fractions of these two organic groups were compared against the VTDMA-based results. In general, the best agreement between the VTDMA results and the PMF-derived mass fractions of organics was obtained when ΔHVAP = 80 kJ mol-1 was set for all organic groups in the model, with a linear correlation coefficient of around 0.4. However, this still indicates that only

Deep Learning with Hierarchical Convolutional Factor Analysis

PubMed Central

Chen, Bo; Polatkan, Gungor; Sapiro, Guillermo; Blei, David; Dunson, David; Carin, Lawrence

2013-01-01

Unsupervised multi-layered (“deep”) models are considered for general data, with a particular focus on imagery. The model is represented using a hierarchical convolutional factor-analysis construction, with sparse factor loadings and scores. The computation of layer-dependent model parameters is implemented within a Bayesian setting, employing a Gibbs sampler and variational Bayesian (VB) analysis, that explicitly exploit the convolutional nature of the expansion. In order to address large-scale and streaming data, an online version of VB is also developed. The number of basis functions or dictionary elements at each layer is inferred from the data, based on a beta-Bernoulli implementation of the Indian buffet process. Example results are presented for several image-processing applications, with comparisons to related models in the literature. PMID:23787342

Factor Analysis by Generalized Least Squares.

ERIC Educational Resources Information Center

Joreskog, Karl G.; Goldberger, Arthur S.

Aitkin's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are scale free and asymptotically efficient. The estimates are computed by a rapidly…

Exploratory Factor Analysis of a Force Concept Inventory Data Set

ERIC Educational Resources Information Center

Scott, Terry F.; Schumayer, Daniel; Gray, Andrew R.

2012-01-01

We perform a factor analysis on a "Force Concept Inventory" (FCI) data set collected from 2109 respondents. We address two questions: the appearance of conceptual coherence in student responses to the FCI and some consequences of this factor analysis on the teaching of Newtonian mechanics. We will highlight the apparent conflation of Newton's…

[Factor Analysis: Principles to Evaluate Measurement Tools for Mental Health].

PubMed

Campo-Arias, Adalberto; Herazo, Edwin; Oviedo, Heidi Celina

2012-09-01

The validation of a measurement tool in mental health is a complex process that usually starts by estimating reliability, to later approach its validity. Factor analysis is a way to know the number of dimensions, domains or factors of a measuring tool, generally related to the construct validity of the scale. The analysis could be exploratory or confirmatory, and helps in the selection of the items with better performance. For an acceptable factor analysis, it is necessary to follow some steps and recommendations, conduct some statistical tests, and rely on a proper sample of participants. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Computational Analysis of KRAS Mutations: Implications for Different Effects on the KRAS p.G12D and p.G13D Mutations

PubMed Central

Liu, Yen-Yi; Hwang, Jenn-Kang; Barrio, Maria Jesus; Rodrigo, Maximiliano; Garcia-Toro, Enrique; Herreros-Villanueva, Marta

2013-01-01

Background The issue of whether patients diagnosed with metastatic colorectal cancer who harbor KRAS codon 13 mutations could benefit from the addition of anti-epidermal growth factor receptor therapy remains under debate. The aim of the current study was to perform computational analysis to investigate the structural implications of the underlying mutations caused by c.38G>A (p.G13D) on protein conformation. Methods Molecular dynamics (MD) simulations were performed to understand the plausible structural and dynamical implications caused by c.35G>A (p.G12D) and c.38G>A (p.G13D). The potential of mean force (PMF) simulations were carried out to determine the free energy profiles of the binding processes of GTP interacting with wild-type (WT) KRAS and its mutants (MT). Results Using MD simulations, we observed that the root mean square deviation (RMSD) increased as a function of time for the MT c.35G>A (p.G12D) and MT c.38G>A (p.G13D) when compared with the WT. We also observed that the GTP-binding pocket in the c.35G>A (p.G12D) mutant is more open than that of the WT and the c.38G>A (p.G13D) proteins. Intriguingly, the analysis of atomic fluctuations and free energy profiles revealed that the mutation of c.35G>A (p.G12D) may induce additional fluctuations in the sensitive sites (P-loop, switch I and II regions). Such fluctuations may promote instability in these protein regions and hamper GTP binding. Conclusions Taken together with the results obtained from MD and PMF simulations, the present findings implicate fluctuations at the sensitive sites (P-loop, switch I and II regions). Our findings revealed that KRAS mutations in codon 13 have similar behavior as KRAS WT. To gain a better insight into why patients with metastatic colorectal cancer (mCRC) and the KRAS c.38G>A (p.G13D) mutation appear to benefit from anti-EGFR therapy, the role of the KRAS c.38G>A (p.G13D) mutation in mCRC needs to be further investigated. PMID:23437064

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

This quantitative research examined factors that affect elementary students' creativity and how those factors correlate. Aiming to identify significant factors that affect creativity and to clarify the relationship between these factors by path analysis, this research was designed to be a stepping stone for creativity enhancement studies. Data…

Generalized five-dimensional dynamic and spectral factor analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Fakhri, Georges; Sitek, Arkadiusz; Zimmerman, Robert E.

2006-04-15

We have generalized the spectral factor analysis and the factor analysis of dynamic sequences (FADS) in SPECT imaging to a five-dimensional general factor analysis model (5D-GFA), where the five dimensions are the three spatial dimensions, photon energy, and time. The generalized model yields a significant advantage in terms of the ratio of the number of equations to that of unknowns in the factor analysis problem in dynamic SPECT studies. We solved the 5D model using a least-squares approach. In addition to the traditional non-negativity constraints, we constrained the solution using a priori knowledge of both time and energy, assuming thatmore » primary factors (spectra) are Gaussian-shaped with full-width at half-maximum equal to gamma camera energy resolution. 5D-GFA was validated in a simultaneous pre-/post-synaptic dual isotope dynamic phantom study where {sup 99m}Tc and {sup 123}I activities were used to model early Parkinson disease studies. 5D-GFA was also applied to simultaneous perfusion/dopamine transporter (DAT) dynamic SPECT in rhesus monkeys. In the striatal phantom, 5D-GFA yielded significantly more accurate and precise estimates of both primary {sup 99m}Tc (bias=6.4%{+-}4.3%) and {sup 123}I (-1.7%{+-}6.9%) time activity curves (TAC) compared to conventional FADS (biases=15.5%{+-}10.6% in {sup 99m}Tc and 8.3%{+-}12.7% in {sup 123}I, p<0.05). Our technique was also validated in two primate dynamic dual isotope perfusion/DAT transporter studies. Biases of {sup 99m}Tc-HMPAO and {sup 123}I-DAT activity estimates with respect to estimates obtained in the presence of only one radionuclide (sequential imaging) were significantly lower with 5D-GFA (9.4%{+-}4.3% for {sup 99m}Tc-HMPAO and 8.7%{+-}4.1% for {sup 123}I-DAT) compared to biases greater than 15% for volumes of interest (VOI) over the reconstructed volumes (p<0.05). 5D-GFA is a novel and promising approach in dynamic SPECT imaging that can also be used in other modalities. It allows accurate and

Review of the Probable Maximum Flood (PMF) Snowmelt Analysis for Success Dam

DTIC Science & Technology

2015-11-01

118.53994 36.11754 7200 1981–2014 CA Dept. of Water Resources EGL Eagle Creek Air Temp. Hourly −118.641 35.983 6700 1995–2009 USACE HSS Hossack Air...is in the form of “tiles” with each tile ap- proximately 1200 × 1200 km in area and containing approximately 2400 × 2400 pixels. Each pixel is...District, U.S. Army Corps of Engineers. REPORT DOCUMENTATION PAGE Form Approved OMB No. 0704-0188 Public reporting burden for this collection of

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Rail Risk Analysis Factors D Appendix D to Part... REQUIREMENTS, AND SECURITY PLANS Pt. 172, App. D Appendix D to Part 172—Rail Risk Analysis Factors A. This... safety and security risk analyses required by § 172.820. The risk analysis to be performed may be...

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Rail Risk Analysis Factors D Appendix D to Part... REQUIREMENTS, AND SECURITY PLANS Pt. 172, App. D Appendix D to Part 172—Rail Risk Analysis Factors A. This... safety and security risk analyses required by § 172.820. The risk analysis to be performed may be...

Sustained Hypoxia Elicits Competing Spinal Mechanisms of Phrenic Motor Facilitation

PubMed Central

Devinney, Michael J.; Nichols, Nicole L.

2016-01-01

Acute intermittent hypoxia (AIH) induces phrenic long-term facilitation (pLTF), a form of spinal motor plasticity. Competing mechanisms give rise to phrenic motor facilitation (pMF; a general term including pLTF) depending on the severity of hypoxia within episodes. In contrast, moderate acute sustained hypoxia (mASH) does not elicit pMF. By varying the severity of ASH and targeting competing mechanisms of pMF, we sought to illustrate why moderate AIH (mAIH) elicits pMF but mASH does not. Although mAIH elicits serotonin-dependent pLTF, mASH does not; thus, mAIH-induced pLTF is pattern sensitive. In contrast, severe AIH (sAIH) elicits pLTF through adenosine-dependent mechanisms, likely from greater extracellular adenosine accumulation. Because serotonin- and adenosine-dependent pMF interact via cross talk inhibition, we hypothesized that pMF is obscured because the competing mechanisms of pMF are balanced and offsetting during mASH. Here, we demonstrate the following: (1) blocking spinal A2A receptors with MSX-3 reveals mASH-induced pMF; and (2) sASH elicits A2A-dependent pMF. In anesthetized rats pretreated with intrathecal A2A receptor antagonist injections before mASH (PaO2 = 40–54 mmHg) or sASH (PaO2 = 25–36 mmHg), (1) mASH induced a serotonin-dependent pMF and (2) sASH induced an adenosine-dependent pMF, which was enhanced by spinal serotonin receptor inhibition. Thus, competing adenosine- and serotonin-dependent mechanisms contribute differentially to pMF depending on the pattern/severity of hypoxia. Understanding interactions between these mechanisms has clinical relevance as we develop therapies to treat severe neuromuscular disorders that compromise somatic motor behaviors, including breathing. Moreover, these results demonstrate how competing mechanisms of plasticity can give rise to pattern sensitivity in pLTF. SIGNIFICANCE STATEMENT Intermittent hypoxia elicits pattern-sensitive spinal plasticity and improves motor function after spinal injury or

Examining evolving performance on the Force Concept Inventory using factor analysis

NASA Astrophysics Data System (ADS)

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W.

2017-06-01

The application of factor analysis to the Force Concept Inventory (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a pre- and post-test, we see factor analysis as a tool by which the changes in conceptual associations made by our students may be gauged given the evolution of their response patterns. This analysis allows us to identify and track conceptual linkages, affording us insight as to how our students have matured due to instruction. We report on our analysis of 427 pre- and post-tests. The factor models for the pre- and post-tests are explored and compared along with the methodology by which these models were fit to the data. The post-test factor pattern is more aligned with an expert's interpretation of the questions' content, as it allows for a more readily identifiable relationship between factors and physical concepts. We discuss this evolution in the context of approaching the characteristics of an expert with force concepts. Also, we find that certain test items do not significantly contribute to the pre- or post-test factor models and attempt explanations as to why this is so. This may suggest that such questions may not be effective in probing the conceptual understanding of our students.

Source Apportionment of PM2.5 Mass and Optical Attenuation Over an Ecologically Sensitive Zone in Central India by Positive Matrix Factorization

NASA Astrophysics Data System (ADS)

Nirmalkar, J.; Raman, R. S.

2016-12-01

Ambient PM2.5 samples (N=366) were collected over an ecologically sensitive zone (Van Vihar National Park) in Bhopal, Central India for two years (01 January, 2012 to 31 December, 2013). Samples were collected using three co-located Mini-Vol® samplers on Teflon, Nylon, and Quartz filter substrates. The aerosol was then chemically characterized for water-soluble inorganic ions, elements, and carbon fractions (elemental carbon and organic carbon) using ion chromatography, ED-XRF, and thermal-optical EC/OC analyzer, respectively. The optical attenuation (at 370 nm and 800 nm) of PM2.5 aerosols was also determined by optical transmissometry (OT-21). The application of Positive matrix factorization (PMF) to a combination of PM2.5 mass, its ions, elements, carbon fractions, and optical attenuation and its outcomes will be discussed.

Confirmatory factor analysis using Microsoft Excel.

PubMed

Miles, Jeremy N V

2005-11-01

This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

A polymethoxyflavone mixture extracted from orange peels, mainly containing nobiletin, 3,3',4',5,6,7,8-heptamethoxyflavone and tangeretin, suppresses melanogenesis through the acidification of cell organelles, including melanosomes.

PubMed

Yoshizaki, Norihiro; Hashizume, Ron; Masaki, Hitoshi

2017-10-01

Skin color is determined by melanin contents and its distribution. Melanin is synthesized in melanosomes of melanocytes, catalyzed by tyrosinase, melanogenic enzymes. Regarding the process of melanin synthesis, melanosomal pH is considered to play an important role, because it has been reported to differ between Caucasian and Black melanocytes. Although polymethoxyflavone (PMF) has many beneficial effects, it has not been reported which PMF suppresses melanogenesis. In this study, we identified the mechanism underlying the effect of PMF on melanogenesis METHODS: We determined the effects of a PMF mixture extracted from orange peels on melanogenesis, on tyrosinase expression, on the localization of tyrosinase and on the acidification of organelles, including melanosomes, in HM3KO human melanoma cells. RESULTS TREATMENT: with the PMF mixture elicited the suppression of melanogenesis, the degradation of tyrosinase in lysosomes and the mislocalization of tyrosinase associated with the acidification of intracellular organelles, including melanosomes. The neutralization of cell organelle pH by ammonium chloride restored melanogenesis and the correct localization of tyrosinase to melanosomes, which had been suppressed by the PMF mixture. These results suggest that the PMF mixture suppresses the localization of tyrosinase to melanosomes and consequently inhibits melanogenesis due to the acidification of cell organelles, including melanosomes. Copyright © 2017 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

Contribution of Cyclic and Pseudo-cyclic Electron Transport to the Formation of Proton Motive Force in Chloroplasts.

PubMed

Shikanai, Toshiharu; Yamamoto, Hiroshi

2017-01-09

Photosynthetic electron transport is coupled to proton translocation across the thylakoid membrane, resulting in the formation of a trans-thylakoid proton gradient (ΔpH) and membrane potential (Δψ). Ion transporters and channels localized to the thylakoid membrane regulate the contribution of each component to the proton motive force (pmf). Although both ΔpH and Δψ contribute to ATP synthesis as pmf, only ΔpH downregulates photosynthetic electron transport via the acidification of the thylakoid lumen by inducing thermal dissipation of excessive absorbed light energy from photosystem II antennae and slowing down of the electron transport through the cytochrome b 6 f complex. To optimize the tradeoff between efficient light energy utilization and protection of both photosystems against photodamage, plants have to regulate the pmf amplitude and its components, ΔpH and Δψ. Cyclic electron transport around photosystem I (PSI) is a major regulator of the pmf amplitude by generating pmf independently of the net production of NADPH by linear electron transport. Chloroplast ATP synthase relaxes pmf for ATP synthesis, and its activity should be finely tuned for maintaining the size of the pmf during steady-state photosynthesis. Pseudo-cyclic electron transport mediated by flavodiiron protein (Flv) forms a large electron sink, which is essential for PSI photoprotection in fluctuating light in cyanobacteria. Flv is conserved from cyanobacteria to gymnosperms but not in angiosperms. The Arabidopsis proton gradient regulation 5 (pgr5) mutant is defective in the main pathway of PSI cyclic electron transport. By introducing Physcomitrella patens genes encoding Flvs, the function of PSI cyclic electron transport was substituted by that of Flv-dependent pseudo-cyclic electron transport. In transgenic plants, the size of the pmf was complemented to the wild-type level but the contribution of ΔpH to the total pmf was lower than that in the wild type. In the pgr5 mutant, the

Source identification and apportionment of halogenated compounds observed at a remote site in East Asia.

PubMed

Li, Shanlan; Kim, Jooil; Park, Sunyoung; Kim, Seung-Kyu; Park, Mi-Kyung; Mühle, Jens; Lee, Gangwoong; Lee, Meehye; Jo, Chun Ok; Kim, Kyung-Ryul

2014-01-01

The sources of halogenated compounds in East Asia associated with stratospheric ozone depletion and climate change are relatively poorly understood. High-precision in situ measurements of 18 halogenated compounds and carbonyl sulfide (COS) made at Gosan, Jeju Island, Korea, from November 2007 to December 2011 were analyzed by a positive matrix factorization (PMF). Seven major industrial sources were identified from the enhanced concentrations of halogenated compounds observed at Gosan and corresponding concentration-based source contributions were also suggested: primary aluminum production explaining 37% of total concentration enhancements, solvent usage of which source apportionment is 25%, fugitive emissions from HCFC/HFC production with 11%, refrigerant replacements (9%), semiconductor/electronics industry (9%), foam blowing agents (6%), and fumigation (3%). Statistical trajectory analysis was applied to specify the potential emission regions for seven sources using back trajectories. Primary aluminum production, solvent usage and fugitive emission sources were mainly contributed by China. Semiconductor/electronics sources were dominantly located in Korea. Refrigerant replacement, fumigation and foam blowing agent sources were spread throughout East Asian countries. The specified potential source regions are consistent with country-based consumptions and emission patterns, verifying the PMF analysis results. The industry-based emission sources of halogenated compounds identified in this study help improve our understanding of the East Asian countries' industrial contributions to halogenated compound emissions.

Testing all six person-oriented principles in dynamic factor analysis.

PubMed

Molenaar, Peter C M

2010-05-01

All six person-oriented principles identified by Sterba and Bauer's Keynote Article can be tested by means of dynamic factor analysis in its current form. In particular, it is shown how complex interactions and interindividual differences/intraindividual change can be tested in this way. In addition, the necessity to use single-subject methods in the analysis of developmental processes is emphasized, and attention is drawn to the possibility to optimally treat developmental psychopathology by means of new computational techniques that can be integrated with dynamic factor analysis.

Exploratory factor analysis of borderline personality disorder criteria in hospitalized adolescents.

PubMed

Becker, Daniel F; McGlashan, Thomas H; Grilo, Carlos M

2006-01-01

The authors examined the factor structure of borderline personality disorder (BPD) in hospitalized adolescents and also sought to add to the theoretical and clinical understanding of any homogeneous components by determining whether they may be related to specific forms of Axis I pathology. Subjects were 123 adolescent inpatients, who were reliably assessed with structured diagnostic interviews for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition Axes I and II disorders. Exploratory factor analysis identified BPD components, and logistic regression analyses tested whether these components were predictive of specific Axis I disorders. Factor analysis revealed a 4-factor solution that accounted for 67.0% of the variance. Factor 1 ("suicidal threats or gestures" and "emptiness or boredom") predicted depressive disorders and alcohol use disorders. Factor 2 ("affective instability," "uncontrolled anger," and "identity disturbance") predicted anxiety disorders and oppositional defiant disorder. Factor 3 ("unstable relationships" and "abandonment fears") predicted only anxiety disorders. Factor 4 ("impulsiveness" and "identity disturbance") predicted conduct disorder and substance use disorders. Exploratory factor analysis of BPD criteria in adolescent inpatients revealed 4 BPD factors that appear to differ from those reported for similar studies of adults. The factors represent components of self-negation, irritability, poorly modulated relationships, and impulsivity--each of which is associated with characteristic Axis I pathology. These findings shed light on the nature of BPD in adolescents and may also have implications for treatment.

Exploratory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Reissmann, D R; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Szabo, G; Rener-Sitar, K

2014-09-01

Although oral health-related quality of life (OHRQoL) as measured by the Oral Health Impact Profile (OHIP) is thought to be multidimensional, the nature of these dimensions is not known. The aim of this report was to explore the dimensionality of the OHIP using the Dimensions of OHRQoL (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Learning Sample (n = 5173), we conducted an exploratory factor analysis on the 46 OHIP items not specifically referring to dentures for 5146 subjects with sufficiently complete data. The first eigenvalue (27·0) of the polychoric correlation matrix was more than ten times larger than the second eigenvalue (2·6), suggesting the presence of a dominant, higher-order general factor. Follow-up analyses with Horn's parallel analysis revealed a viable second-order, four-factor solution. An oblique rotation of this solution revealed four highly correlated factors that we named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact. These four dimensions and the strong general factor are two viable hypotheses for the factor structure of the OHIP. © 2014 John Wiley & Sons Ltd.

Factor analysis of an instrument to measure the impact of disease on daily life.

PubMed

Pedrosa, Rafaela Batista Dos Santos; Rodrigues, Roberta Cunha Matheus; Padilha, Kátia Melissa; Gallani, Maria Cecília Bueno Jayme; Alexandre, Neusa Maria Costa

2016-01-01

to verify the structure of factors of an instrument to measure the Heart Valve Disease Impact on Daily Life (IDCV) when applied to coronary artery disease patients. the study included 153 coronary artery disease patients undergoing outpatient follow-up care. The IDCV structure of factors was initially assessed by means of confirmatory factor analysis and, subsequently, by exploratory factor analysis. The Varimax rotation method was used to estimate the main components of analysis, eigenvalues greater than one for extraction of factors, and factor loading greater than 0.40 for selection of items. Internal consistency was estimated using Cronbach's alpha coefficient. confirmatory factor analysis did not confirm the original structure of factors of the IDCV. Exploratory factor analysis showed three dimensions, which together explained 78% of the measurement variance. future studies with expansion of case selection are necessary to confirm the IDCV new structure of factors.

Calreticulin mutation-specific immunostaining in myeloproliferative neoplasms: pathogenetic insight and diagnostic value

PubMed Central

Vannucchi, A M; Rotunno, G; Bartalucci, N; Raugei, G; Carrai, V; Balliu, M; Mannarelli, C; Pacilli, A; Calabresi, L; Fjerza, R; Pieri, L; Bosi, A; Manfredini, R; Guglielmelli, P

2014-01-01

Mutations in the gene calreticulin (CALR) occur in the majority of JAK2- and MPL-unmutated patients with essential thrombocythemia (ET) and primary myelofibrosis (PMF); identifying CALR mutations contributes to the diagnostic pathway of ET and PMF. CALR mutations are heterogeneous spanning over the exon 9, but all result in a novel common protein C terminus. We developed a polyclonal antibody against a 17-amino-acid peptide derived from mutated calreticulin that was used for immunostaining of bone marrow biopsies. We show that this antibody specifically recognized patients harboring different types of CALR mutation with no staining in healthy controls and JAK2- or MPL-mutated ET and PMF. The labeling was mostly localized in megakaryocytes, whereas myeloid and erythroid cells showed faint staining, suggesting a preferential expression of calreticulin in megakaryocytes. Megakaryocytic-restricted expression of calreticulin was also demonstrated using an antibody against wild-type calreticulin and by measuring the levels of calreticulin RNA by gene expression analysis. Immunostaining using an antibody specific for mutated calreticulin may become a rapid, simple and cost-effective method for identifying CALR-mutated patients complementing molecular analysis; furthermore, the labeling pattern supports the preferential expansion of megakaryocytic cell lineage as a result of CALR mutation in an immature hematopoietic stem cell. PMID:24618731

Impact of a primordial magnetic field on cosmic microwave background B modes with weak lensing

NASA Astrophysics Data System (ADS)

Yamazaki, Dai G.

2018-05-01

We discuss the manner in which the primordial magnetic field (PMF) suppresses the cosmic microwave background (CMB) B mode due to the weak-lensing (WL) effect. The WL effect depends on the lensing potential (LP) caused by matter perturbations, the distribution of which at cosmological scales is given by the matter power spectrum (MPS). Therefore, the WL effect on the CMB B mode is affected by the MPS. Considering the effect of the ensemble average energy density of the PMF, which we call "the background PMF," on the MPS, the amplitude of MPS is suppressed in the wave number range of k >0.01 h Mpc-1 . The MPS affects the LP and the WL effect in the CMB B mode; however, the PMF can damp this effect. Previous studies of the CMB B mode with the PMF have only considered the vector and tensor modes. These modes boost the CMB B mode in the multipole range of ℓ>1000 , whereas the background PMF damps the CMB B mode owing to the WL effect in the entire multipole range. The matter density in the Universe controls the WL effect. Therefore, when we constrain the PMF and the matter density parameters from cosmological observational data sets, including the CMB B mode, we expect degeneracy between these parameters. The CMB B mode also provides important information on the background gravitational waves, inflation theory, matter density fluctuations, and the structure formations at the cosmological scale through the cosmological parameter search. If we study these topics and correctly constrain the cosmological parameters from cosmological observations, including the CMB B mode, we need to correctly consider the background PMF.

Inheritance pattern of platelet membrane fluidity in Alzheimer disease.

PubMed Central

Chakravarti, A; Slaugenhaupt, S A; Zubenko, G S

1989-01-01

The fluorescence anisotropy of 1,6-diphenyl-1,3,5-hexatriene in labeled platelet membranes, an index of membrane fluidity, is a stable, familial trait that is associated with a clinically distinct subtype of Alzheimer disease. Complex segregation analysis of this continuous variable was performed on 95 members of 14 pedigrees identified through probands who had autopsy-confirmed or clinically diagnosed Alzheimer disease. The results suggest that platelet membrane fluidity is controlled by a single genetic locus, PMF, with two alleles that have additive effects. The PMF locus appears to explain approximately 80% of the total variation in platelet membrane fluidity within the families of patients with Alzheimer disease. PMID:2729275

A human factors analysis of EVA time requirements

NASA Technical Reports Server (NTRS)

Pate, D. W.

1996-01-01

Human Factors Engineering (HFE), also known as Ergonomics, is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. A human factors motion and time study was initiated with the goal of developing a database of EVA task times and a method of utilizing the database to predict how long an ExtraVehicular Activity (EVA) should take. Initial development relied on the EVA activities performed during the STS-61 mission (Hubble repair). The first step of the analysis was to become familiar with EVAs and with the previous studies and documents produced on EVAs. After reviewing these documents, an initial set of task primitives and task time modifiers was developed. Videotaped footage of STS-61 EVAs were analyzed using these primitives and task time modifiers. Data for two entire EVA missions and portions of several others, each with two EVA astronauts, was collected for analysis. Feedback from the analysis of the data will be used to further refine the primitives and task time modifiers used. Analysis of variance techniques for categorical data will be used to determine which factors may, individually or by interactions, effect the primitive times and how much of an effect they have.

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rankmore » impacts both overcompleteness and sparsity.« less

Inability of immunomorphometric assessment of angiogenesis to distinguish primary versus secondary myelofibrosis.

PubMed

Sharma, Prashant; Pati, Hara Prasad; Mishra, Pravas Chandra; Dinda, Amit Kumar; Gupta, Ruchika; Sharma, Alok; Jacob, Tony George

2011-08-01

To explore the utility of bone marrow (BM) angiogenesis in differentiating primary myelofibrosis (PMF) from secondary myelofibrosis (MF). CD34 immunostaining was performed on BM biopsies from 21 PMFs, 23 non-PMF myeloproliferative neoplasms (MPN) with associated MF, 20 secondary MF samples, and 10 nonfibrotic controls. Microvessel density (MVD) and microvessel surface area (MSA), along with blood and BM findings were compared between the groups. The post-MPN MF cases included chronic myeloid leukemia-MF and polycythemia vera-MF. Etiologies of secondary MF were metastatic carcinomas, non-MPN hematologic malignancies, tuberculosis, autoimmune MF, and osteopetrosis. Megakaryocytic clustering was the most frequent and intrasinusoidal hematopoiesis the most specific feature of PMF. Higher reticulin grade, collagenization, and osteomyelosclerosis were commoner in PMF. MVD and MSA were significantly increased in fibrotic marrows regardless of etiology. Although mean MVD as well as MSA were highest in PMF, extensive overlaps among groups and marked heterogeneity in the secondary MF group rendered them of limited utility in the differential diagnosis. Enhanced angiogenesis is not entirely specific for PMF. Overlaps with secondary MF limits its differential diagnostic utility. Pathogenetically, our findings suggest that enhanced angiogenesis is a secondary paraneoplastic stromal response shared by various unrelated conditions.

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

ERIC Educational Resources Information Center

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-01-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

Confirmatory factor analysis applied to the Force Concept Inventory

NASA Astrophysics Data System (ADS)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

Propellant Mass Fraction Calculation Methodology for Launch Vehicles and Application to Ares Vehicles

NASA Technical Reports Server (NTRS)

Holt, James B.; Monk, Timothy S.

2009-01-01

Propellant Mass Fraction (pmf) calculation methods vary throughout the aerospace industry. While typically used as a means of comparison between candidate launch vehicle designs, the actual pmf calculation method varies slightly from one entity to another. It is the purpose of this paper to present various methods used to calculate the pmf of launch vehicles. This includes fundamental methods of pmf calculation that consider only the total propellant mass and the dry mass of the vehicle; more involved methods that consider the residuals, reserves and any other unusable propellant remaining in the vehicle; and calculations excluding large mass quantities such as the installed engine mass. Finally, a historical comparison is made between launch vehicles on the basis of the differing calculation methodologies, while the unique mission and design requirements of the Ares V Earth Departure Stage (EDS) are examined in terms of impact to pmf.

Toward Reflective Judgment in Exploratory Factor Analysis Decisions: Determining the Extraction Method and Number of Factors To Retain.

ERIC Educational Resources Information Center

Knight, Jennifer L.

This paper considers some decisions that must be made by the researcher conducting an exploratory factor analysis. The primary purpose is to aid the researcher in making informed decisions during the factor analysis instead of relying on defaults in statistical programs or traditions of previous researchers. Three decision areas are addressed.…

Effectiveness of a lumbopelvic monitor and feedback device to change postural behaviour: a protocol for the ELF cluster randomised controlled trial

PubMed Central

Milosavljevic, Stephan

2017-01-01

Introduction Low back pain (LBP) is the most common, costly and disabling musculoskeletal disorder worldwide, and is prevalent in healthcare workers. Posture is a modifiable risk factor for LBP shown to reduce the prevalence of LBP. Our feasibility research suggests that postural feedback might help healthcare workers avoid hazardous postures. The Effectiveness of Lumbopelvic Feedback (ELF) trial will investigate the extent to which postural monitor and feedback (PMF) can reduce exposure to hazardous posture associated with LBP. Methods This is a participant-blinded, randomised controlled trial with blocked cluster random allocation. Participants will include volunteer healthcare workers recruited from aged care institutions and hospitals. A postural monitoring and feedback device will monitor and record lumbopelvic forward bending posture, and provide audio feedback whenever the user sustains a lumbopelvic forward bending posture that exceeds predefined thresholds. The primary outcome measure will be postural behaviour (exceeding thresholds). Secondary outcome measures will be incidence of LBP, participant-reported disability and adherence. Following baseline assessment, we will randomly assign participants to 1 of 2 intervention arms: a feedback group and a no-feedback control group. We will compare between-group differences of changes in postural behaviour by using a repeated measures mixed-effect model analysis of covariance (ANCOVA) at 6 weeks. Postural behaviour baseline scores, work-related psychosocial factors and disability scores will be input as covariates into the statistical models. We will use logistic mixed model analysis and Cox's proportional hazards for assessing the effect of a PMF on LBP incidence between groups. Discussion Posture is a modifiable risk factor for low back disorders. Findings from the ELF trial will inform the design of future clinical trials assessing the effectiveness of wearable technology on minimising hazardous posture

SEPARABLE FACTOR ANALYSIS WITH APPLICATIONS TO MORTALITY DATA

PubMed Central

Fosdick, Bailey K.; Hoff, Peter D.

2014-01-01

Human mortality data sets can be expressed as multiway data arrays, the dimensions of which correspond to categories by which mortality rates are reported, such as age, sex, country and year. Regression models for such data typically assume an independent error distribution or an error model that allows for dependence along at most one or two dimensions of the data array. However, failing to account for other dependencies can lead to inefficient estimates of regression parameters, inaccurate standard errors and poor predictions. An alternative to assuming independent errors is to allow for dependence along each dimension of the array using a separable covariance model. However, the number of parameters in this model increases rapidly with the dimensions of the array and, for many arrays, maximum likelihood estimates of the covariance parameters do not exist. In this paper, we propose a submodel of the separable covariance model that estimates the covariance matrix for each dimension as having factor analytic structure. This model can be viewed as an extension of factor analysis to array-valued data, as it uses a factor model to estimate the covariance along each dimension of the array. We discuss properties of this model as they relate to ordinary factor analysis, describe maximum likelihood and Bayesian estimation methods, and provide a likelihood ratio testing procedure for selecting the factor model ranks. We apply this methodology to the analysis of data from the Human Mortality Database, and show in a cross-validation experiment how it outperforms simpler methods. Additionally, we use this model to impute mortality rates for countries that have no mortality data for several years. Unlike other approaches, our methodology is able to estimate similarities between the mortality rates of countries, time periods and sexes, and use this information to assist with the imputations. PMID:25489353

Source identification of heavy metals in peri-urban agricultural soils of southeast China: An integrated approach.

PubMed

Hu, Wenyou; Wang, Huifeng; Dong, Lurui; Huang, Biao; Borggaard, Ole K; Bruun Hansen, Hans Christian; He, Yue; Holm, Peter E

2018-06-01

Intensive human activities, in particular agricultural and industrial production have led to heavy metal accumulation in the peri-urban agricultural soils of China threatening soil environmental quality and agricultural product security. A combination of spatial analysis (SA), Pb isotope ratio analysis (IRA), input fluxes analysis (IFA), and positive matrix factorization (PMF) model was successfully used to assess the status and sources of heavy metals in typical peri-urban agricultural soils from a rapidly developing region of China. Mean concentrations of Cd, As, Hg, Pb, Cu, Zn and Cr in surface soils (0-20 cm) were 0.31, 11.2, 0.08, 35.6, 44.8, 119.0 and 97.0 mg kg -1 , respectively, exceeding the local background levels except for Hg. Spatial distribution of heavy metals revealed that agricultural activities have significant influence on heavy metal accumulation in the surface soils. Isotope ratio analysis suggested that fertilization along with atmospheric deposition were the major sources of heavy metal accumulation in the soils. Based on the PMF model, the relative contribution rates of the heavy metals due to fertilizer application, atmospheric deposition, industrial emission, and soil parent materials were 30.8%, 33.0%, 25.4% and 10.8%, respectively, demonstrating that anthropogenic activities had significantly higher contribution than natural sources. This study provides a reliable and robust approach for heavy metals source apportionment in this particular peri-urban area with a clear potential for future application in other regions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

NASA Astrophysics Data System (ADS)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

Physics Metacognition Inventory Part Ii: Confirmatory Factor Analysis and Rasch Analysis

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-01-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition,…

SOURCE APPORTIONMENT OF PM2.5 AT AN URBAN IMPROVE SITE IN SEATTLE, WA

EPA Science Inventory

The multivariate receptor models Positive Matrix Factorization (PMF) and Unmix were used along with EPA's Chemical Mass Balance model to deduce the sources of PM2.5 at a centrally located urban site in Seattle, Washington. A total of 289 filter samples were obtained with an IM...

Nitrogen enriched mesoporous organic polymer anchored copper(II) material: an efficient and reusable catalyst for the synthesis of esters and amides from aromatic systems.

PubMed

Molla, Rostam Ali; Iqubal, Md Asif; Ghosh, Kajari; Kamaluddin; Islam, Sk Manirul

2015-04-14

A new copper-grafted mesoporous poly-melamine-formaldehyde (Cu-mPMF) has been synthesized from melamine and paraformaldehyde in DMSO medium, followed by grafting of Cu(ii) at its surface. Cu-mPMF has been characterized by elemental analysis, powder XRD, HR TEM, FE-SEM, N2 adsorption study, FT-IR, UV-vis DRS, TGA-DTA, EPR spectroscopy, Raman spectroscopy and X-ray photoelectron spectroscopy (XPS). The Cu-grafted mesoporous material showed very good catalytic activity in methyl esterification of benzylic alcohols and amidation of nitriles. Moreover, the catalyst is easily recoverable and can be reused seven times without appreciable loss of catalytic activity in the above reactions. The highly dispersed and strongly bound Cu(ii) sites in the Cu-grafted mesoporous polymer could be responsible for the observed high activities of the Cu-mPMF catalyst. Due to strong binding with the functional groups of the polymer, no evidence of leached copper from the catalyst during the course of reaction emerged, suggesting true heterogeneity in the catalytic process.

Comparing solvophobic and multivalent induced collapse in polyelectrolyte brushes

DOE PAGES

Jackson, Nicholas E.; Brettmann, Blair K.; Vishwanath, Venkatram; ...

2017-02-03

Here, coarse-grained molecular dynamics enhanced by free-energy sampling methods is used to examine the roles of solvophobicity and multivalent salts on polyelectrolyte brush collapse. Specifically, we demonstrate that while ostensibly similar, solvophobic collapsed brushes and multivalent-ion collapsed brushes exhibit distinct mechanistic and structural features. Notably, multivalent-induced heterogeneous brush collapse is observed under good solvent polymer backbone conditions, demonstrating that the mechanism of multivalent collapse is not contingent upon a solvophobic backbone. Umbrella sampling of the potential of mean-force (PMF) between two individual brush strands confirms this analysis, revealing starkly different PMFs under solvophobic and multivalent conditions, suggesting the role ofmore » multivalent “bridging” as the discriminating feature in trivalent collapse. Structurally, multivalent ions show a propensity for nucleating order within collapsed brushes, whereas poor-solvent collapsed brushes are more disordered; this difference is traced to the existence of a metastable PMF minimum for poor solvent conditions, and a global PMF minimum for trivalent systems, under experimentally relevant conditions.« less

Comparing solvophobic and multivalent induced collapse in polyelectrolyte brushes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, Nicholas E.; Brettmann, Blair K.; Vishwanath, Venkatram

Here, coarse-grained molecular dynamics enhanced by free-energy sampling methods is used to examine the roles of solvophobicity and multivalent salts on polyelectrolyte brush collapse. Specifically, we demonstrate that while ostensibly similar, solvophobic collapsed brushes and multivalent-ion collapsed brushes exhibit distinct mechanistic and structural features. Notably, multivalent-induced heterogeneous brush collapse is observed under good solvent polymer backbone conditions, demonstrating that the mechanism of multivalent collapse is not contingent upon a solvophobic backbone. Umbrella sampling of the potential of mean-force (PMF) between two individual brush strands confirms this analysis, revealing starkly different PMFs under solvophobic and multivalent conditions, suggesting the role ofmore » multivalent “bridging” as the discriminating feature in trivalent collapse. Structurally, multivalent ions show a propensity for nucleating order within collapsed brushes, whereas poor-solvent collapsed brushes are more disordered; this difference is traced to the existence of a metastable PMF minimum for poor solvent conditions, and a global PMF minimum for trivalent systems, under experimentally relevant conditions.« less

Heavy metals in particulate and colloidal matter from atmospheric deposition of urban Guangzhou, South China.

PubMed

Huang, Wen; Duan, Dandan; Zhang, Yulong; Cheng, Hefa; Ran, Yong

2014-08-30

Suspended particulate matter (SPM) and colloidal matter (COM) in annual dry and wet deposition samples in urban Guangzhou were for the first time collected, and their trace metals were investigated by using inductively coupled plasma mass spectrometry (ICP-MS). The deposition flux of SPM and of metal elements varied largely among the investigated seasons, and reached the maximum in spring. The correlation analysis indicated that significant correlations existed among some of the metal elements in the deposition samples. The enrichment factors (EF) of metals in COM in the deposition ranging from 79.66 to 130,000 were much higher than those of SPM ranging from 1.65 to 286.48, indicating the important role of COM. The factor analysis showed that emissions from street dust, non-ferrous metal production, and heavy fuel oil were major sources of the trace metals. Positive matrix factorization (PMF) model was used to quantitatively estimate anthropogenic source. Copyright © 2013 Elsevier Ltd. All rights reserved.

Connectivism in Postsecondary Online Courses: An Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hogg, Nanette; Lomicky, Carol S.

2012-01-01

This study explores 465 postsecondary students' experiences in online classes through the lens of connectivism. Downes' 4 properties of connectivism (diversity, autonomy, interactivity, and openness) were used as the study design. An exploratory factor analysis was performed. This study found a 4-factor solution. Subjects indicated that autonomy…

Chemical compositions and source identification of PM₂.₅ aerosols for estimation of a diesel source surrogate.

PubMed

Sahu, Manoranjan; Hu, Shaohua; Ryan, Patrick H; Le Masters, Grace; Grinshpun, Sergey A; Chow, Judith C; Biswas, Pratim

2011-06-01

Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Citrus peel polymethoxylated flavones extract modulates liver and heart function parameters in diet induced hypercholesterolemic rats.

PubMed

Green, Curtis O; Wheatley, Andrew O; McGrowder, Donovan A; Dilworth, Lowell L; Asemota, Helen N

2013-01-01

The primary aim of this study was to investigate the effects of Ortanique peel polymethoxylated flavones extract (PMF(ort)) on organ function parameters in the serum of hypercholesterolemic and normal rats. Thirty Sprague-Dawley rats were fed high cholesterol diets supplemented with 1.5% PMF(ort) and niacin respectively for 49days. Hypercholesterolemic rats fed PMF(ort) had significant reductions in the activities of aspartate aminotransferase and alkaline phosphatase (69.12±3.34 and 87.22±8.42U/L respectively) compared to the untreated hypercholesterolemic group (118.61±4.85 and 132.62±10.62U/L respectively, p<0.05). Supplementation of the diet with niacin or PMF(ort) resulted in no significant differences in the serum levels of creatinine or urea in any of the groups. Total bilirubin was highest in the untreated hypercholesterolemic group. Supplementation of the diets of hypercholesterolemic rats with PMF(ort) resulted in significant reductions in the activities of serum creatine kinase and lactate dehydrogenase (119.3±25.3; 222.5±50.3U/L, p<0.05) respectively relative to the untreated hypercholesterolemic group (257.2±48.3; 648.8±103U/L, p<0.05). The results would suggest that PMF(ort) modulates hypercholesterolemia-associated organ injury in rats. PMF(ort) could therefore be a suitable candidate for prophylactic and therapeutic treatment of hypercholesterolemia-associated organ injury. Copyright © 2012 Elsevier Ltd. All rights reserved.

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluating voice characteristics of first-year acting students in Israel: factor analysis.

PubMed

Amir, Ofer; Primov-Fever, Adi; Kushnir, Tami; Kandelshine-Waldman, Osnat; Wolf, Michael

2013-01-01

Acting students require diverse, high-quality, and high-intensity vocal performance from early stages of their training. Demanding vocal activities, before developing the appropriate vocal skills, put them in high risk for developing vocal problems. A retrospective analysis of voice characteristics of first-year acting students using several voice evaluation tools. A total of 79 first-year acting students (55 women and 24 men) were assigned into two study groups: laryngeal findings (LFs) and no laryngeal findings, based on stroboscopic findings. Their voice characteristics were evaluated using acoustic analysis, aerodynamic examination, perceptual scales, and self-report questionnaires. Results obtained from each set of measures were examined using a factor analysis approach. Significant differences between the two groups were found for a single fundamental frequency (F(0))-Regularity factor; a single Grade, Roughness, Breathiness, Asthenia, Strain perceptual factor; and the three self-evaluation factors. Gender differences were found for two acoustic analysis factors, which were based on F(0) and its derivatives, namely an aerodynamic factor that represents expiratory volume measurements and a single self-evaluation factor that represents the tendency to seek therapy. Approximately 50% of the first-year acting students had LFs. These students differed from their peers in the control group in a single acoustic analysis factor, as well as perceptual and self-report factors. No group differences, however, were found for the aerodynamic factors. Early laryngeal examination and voice evaluation of future professional voice users could provide a valuable individual baseline, to which later examinations could be compared, and assist in providing personally tailored treatment. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Correlation between lifetime heterogeneity and kinetics heterogeneity during chlorophyll fluorescence induction in leaves: 2. Multi-frequency phase and modulation analysis evidences a loosely connected PSII pigment-protein complex.

PubMed

Moise, Nicolae; Moya, Ismaël

2004-06-28

We report the first direct decomposition of the fluorescence lifetime heterogeneity during multiphasic fluorescence induction in dark-adapted leaves by multi-frequency phase and modulation fluorometry (PMF). A very fast component, assigned to photosystem I (PSI), was found to be constant in lifetime and yield, whereas the two slow components, which are strongly affected by the closure of the reaction centers by light, were assigned to PSII. Based on a modified "reversible radical pair" kinetic model with three compartments, we showed that a loosely connected pigment complex, which is assumed to be the CP47 complex, plays a specific role with respect to the structure and function of the PSII: (i) it explains the heterogeneity of PSII fluorescence lifetime as a compartmentation of excitation energy in the antenna, (ii) it is the site of a conformational change in the first second of illumination, and (iii) it is involved in the mechanisms of nonphotochemical quenching (NPQ). On the basis of the multi-frequency PMF analysis, we reconciled two apparently antagonistic aspects of chlorophyll a fluorescence in vivo: it is heterogeneous with respect to the kinetic structure (several lifetime components) and homogeneous with respect to average quantities (quasi-linear mean tau-Phi relationship).

Seasonal assessment and apportionment of surface water pollution using multivariate statistical methods: Sinos River, southern Brazil.

PubMed

Alves, Darlan Daniel; Riegel, Roberta Plangg; de Quevedo, Daniela Müller; Osório, Daniela Montanari Migliavacca; da Costa, Gustavo Marques; do Nascimento, Carlos Augusto; Telöken, Franko

2018-06-08

Assessment of surface water quality is an issue of currently high importance, especially in polluted rivers which provide water for treatment and distribution as drinking water, as is the case of the Sinos River, southern Brazil. Multivariate statistical techniques allow a better understanding of the seasonal variations in water quality, as well as the source identification and source apportionment of water pollution. In this study, the multivariate statistical techniques of cluster analysis (CA), principal component analysis (PCA), and positive matrix factorization (PMF) were used, along with the Kruskal-Wallis test and Spearman's correlation analysis in order to interpret a water quality data set resulting from a monitoring program conducted over a period of almost two years (May 2013 to April 2015). The water samples were collected from the raw water inlet of the municipal water treatment plant (WTP) operated by the Water and Sewage Services of Novo Hamburgo (COMUSA). CA allowed the data to be grouped into three periods (autumn and summer (AUT-SUM); winter (WIN); spring (SPR)). Through the PCA, it was possible to identify that the most important parameters in contribution to water quality variations are total coliforms (TCOLI) in SUM-AUT, water level (WL), water temperature (WT), and electrical conductivity (EC) in WIN and color (COLOR) and turbidity (TURB) in SPR. PMF was applied to the complete data set and enabled the source apportionment water pollution through three factors, which are related to anthropogenic sources, such as the discharge of domestic sewage (mostly represented by Escherichia coli (ECOLI)), industrial wastewaters, and agriculture runoff. The results provided by this study demonstrate the contribution provided by the use of integrated statistical techniques in the interpretation and understanding of large data sets of water quality, showing also that this approach can be used as an efficient methodology to optimize indicators for water

Establishing Evidence for Internal Structure Using Exploratory Factor Analysis

ERIC Educational Resources Information Center

Watson, Joshua C.

2017-01-01

Exploratory factor analysis (EFA) is a data reduction technique used to condense data into smaller sets of summary variables by identifying underlying factors potentially accounting for patterns of collinearity among said variables. Using an illustrative example, the 5 general steps of EFA are described with best practices for decision making…

An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

NASA Astrophysics Data System (ADS)

Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

2017-12-01

For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

Targeting megakaryocytic induced fibrosis by AURKA inhibition in the myeloproliferative neoplasms

PubMed Central

Wen, Qiang Jeremy; Yang, Qiong; Goldenson, Benjamin; Malinge, Sébastien; Lasho, Terra; Schneider, Rebekka K.; Breyfogle, Lawrence J.; Schultz, Rachael; Gilles, Laure; Koppikar, Priya; Abdel-Wahab, Omar; Pardanani, Animesh; Stein, Brady; Gurbuxani, Sandeep; Mullally, Ann; Levine, Ross; Tefferi, Ayalew; Crispino, John D.

2015-01-01

Primary myelofibrosis (PMF) is characterized by bone marrow fibrosis, myeloproliferation, extramedullary hematopoiesis, splenomegaly and leukemic progression. Moreover, the bone marrow and spleen of patients are full of atypical megakaryocytes that are postulated to contribute to fibrosis through the release of cytokines including TGF-β. Although the JAK inhibitor ruxolitinib provides symptomatic relief, it does not reduce the mutant allele burden or significantly reverse fibrosis. Here we show through pharmacologic and genetic studies that, apart from JAK2, Aurora kinase A (AURKA) is a novel therapeutic target in PMF. MLN8237, a selective AURKA inhibitor promoted polyploidization and differentiation of PMF megakaryocytes and displayed potent anti-fibrotic and anti-tumor activity in vivo. We also reveal that loss of one allele of AURKA is sufficient to ameliorate fibrosis and other PMF phenotypes in vivo. Our data suggest that megakaryocytes are drivers of fibrosis and that targeting them with AURKA inhibitors will provide therapeutic benefit in PMF. PMID:26569382

Analysis of the influencing factors of global energy interconnection development

NASA Astrophysics Data System (ADS)

Zhang, Yi; He, Yongxiu; Ge, Sifan; Liu, Lin

2018-04-01

Under the background of building global energy interconnection and achieving green and low-carbon development, this paper grasps a new round of energy restructuring and the trend of energy technology change, based on the present situation of global and China's global energy interconnection development, established the index system of the impact of global energy interconnection development factors. A subjective and objective weight analysis of the factors affecting the development of the global energy interconnection was conducted separately by network level analysis and entropy method, and the weights are summed up by the method of additive integration, which gives the comprehensive weight of the influencing factors and the ranking of their influence.

Blended polybenzimidazole and melamine-co-formaldehyde thermosets

DOE PAGES

Klaehn, John R.; Orme, Christopher J.; Peterson, Eric S.

2016-05-11

Polybenzimidazole [PBI; poly-2,2’(m-phenylene)-5,5’-bibenzimidazole] is known to have excellent high temperature stability (up to 450 ºC) and superb H 2/CO 2 selectivity compared to most high performance (HP) polymers. But, PBI has issues in thin-film formation compared to other HP polymers, due to challenging processing techniques. In this work, new blended thermosets were made with PBI and poly(melamine co-formaldehyde) [PMF] to produce stable thin-films after thermal processing at 220-250 ºC. PBI film formation is difficult, and the film tends to fracture and fissure due to loss of processing aids and stabilizers (salt/acid additives) that are found in PBI solutions above10 wtmore » %. The PBI-PMF blended thermosets we report do not have stabilizers, and can be made into dense thin-films. It is remarkable that these thermally processed PBI-PMF films were stable in deionized water for extended periods, whereas many PBI films that contain additives are not. The PBI-PMF films were analyzed using pure and mixed gas permeability measurement techniques. At 250 °C, the data show H 2/CO 2 gas selectivities greater than 13. Also, from the gas permeation data, the energy of activation (Ep) of a mixed gas stream for PBI-PMF shows that hydrogen permeates more easily than the other gases, while the permeabilities for the larger kinetic diameter gases are greatly diminished. The FT-IR spectra show that the PBI-PMF films have changed from parent PBI after thermal processing, and PMF dominates the spectra even in minor percent compositions. Altogether, the reported PBI-PMF thermoset films show good stability which can be used for high temperature gas separation.« less

Blended polybenzimidazole and melamine-co-formaldehyde thermosets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klaehn, John R.; Orme, Christopher J.; Peterson, Eric S.

Polybenzimidazole [PBI; poly-2,2’(m-phenylene)-5,5’-bibenzimidazole] is known to have excellent high temperature stability (up to 450 ºC) and superb H 2/CO 2 selectivity compared to most high performance (HP) polymers. But, PBI has issues in thin-film formation compared to other HP polymers, due to challenging processing techniques. In this work, new blended thermosets were made with PBI and poly(melamine co-formaldehyde) [PMF] to produce stable thin-films after thermal processing at 220-250 ºC. PBI film formation is difficult, and the film tends to fracture and fissure due to loss of processing aids and stabilizers (salt/acid additives) that are found in PBI solutions above10 wtmore » %. The PBI-PMF blended thermosets we report do not have stabilizers, and can be made into dense thin-films. It is remarkable that these thermally processed PBI-PMF films were stable in deionized water for extended periods, whereas many PBI films that contain additives are not. The PBI-PMF films were analyzed using pure and mixed gas permeability measurement techniques. At 250 °C, the data show H 2/CO 2 gas selectivities greater than 13. Also, from the gas permeation data, the energy of activation (Ep) of a mixed gas stream for PBI-PMF shows that hydrogen permeates more easily than the other gases, while the permeabilities for the larger kinetic diameter gases are greatly diminished. The FT-IR spectra show that the PBI-PMF films have changed from parent PBI after thermal processing, and PMF dominates the spectra even in minor percent compositions. Altogether, the reported PBI-PMF thermoset films show good stability which can be used for high temperature gas separation.« less

Examining Evolving Performance on the Force Concept Inventory Using Factor Analysis

ERIC Educational Resources Information Center

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W

2017-01-01

The application of factor analysis to the "Force Concept Inventory" (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a…

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Edwards, Michael C.

2010-01-01

Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR

ERIC Educational Resources Information Center

Baglin, James

2014-01-01

Exploratory factor analysis (EFA) methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many…

Factor analysis of the contextual fine motor questionnaire in children.

PubMed

Lin, Chin-Kai; Meng, Ling-Fu; Yu, Ya-Wen; Chen, Che-Kuo; Li, Kuan-Hua

2014-02-01

Most studies treat fine motor as one subscale in a developmental test, hence, further factor analysis of fine motor has not been conducted. In fact, fine motor has been treated as a multi-dimensional domain from both clinical and theoretical perspectives, and therefore to know its factors would be valuable. The aim of this study is to analyze the internal consistency and factor validity of the Contextual Fine Motor Questionnaire (CFMQ). Based on the ecological observation and literature, the Contextual Fine Motor Questionnaire (CFMQ) was developed and includes 5 subscales: Pen Control, Tool Use During Handicraft Activities, the Use of Dining Utensils, Connecting and Separating during Dressing and Undressing, and Opening Containers. The main purpose of this study is to establish the factorial validity of the CFMQ through conducting this factor analysis study. Among 1208 questionnaires, 904 were successfully completed. Data from the children's CFMQ submitted by primary care providers was analyzed, including 485 females (53.6%) and 419 males (46.4%) from grades 1 to 5, ranging in age from 82 to 167 months (M=113.9, SD=16.3). Cronbach's alpha was used to measure internal consistency and explorative factor analysis was applied to test the five factor structures within the CFMQ. Results showed that Cronbach's alpha coefficient of the CFMQ for 5 subscales ranged from .77 to .92 and all item-total correlations with corresponding subscales were larger than .4 except one item. The factor loading of almost all items classified to their factor was larger than .5 except 3 items. There were five factors, explaining a total of 62.59% variance for the CFMQ. In conclusion, the remaining 24 items in the 5 subscales of the CFMQ had appropriate internal consistency, test-retest reliability and construct validity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Identification of biased sectors in emission data using a combination of chemical transport model and receptor model

NASA Astrophysics Data System (ADS)

Uranishi, Katsushige; Ikemori, Fumikazu; Nakatsubo, Ryohei; Shimadera, Hikari; Kondo, Akira; Kikutani, Yuki; Asano, Katsuyoshi; Sugata, Seiji

2017-10-01

This study presented a comparison approach with multiple source apportionment methods to identify which sectors of emission data have large biases. The source apportionment methods for the comparison approach included both receptor and chemical transport models, which are widely used to quantify the impacts of emission sources on fine particulate matter of less than 2.5 μm in diameter (PM2.5). We used daily chemical component concentration data in the year 2013, including data for water-soluble ions, elements, and carbonaceous species of PM2.5 at 11 sites in the Kinki-Tokai district in Japan in order to apply the Positive Matrix Factorization (PMF) model for the source apportionment. Seven PMF factors of PM2.5 were identified with the temporal and spatial variation patterns and also retained features of the sites. These factors comprised two types of secondary sulfate, road transportation, heavy oil combustion by ships, biomass burning, secondary nitrate, and soil and industrial dust, accounting for 46%, 17%, 7%, 14%, 13%, and 3% of the PM2.5, respectively. The multiple-site data enabled a comprehensive identification of the PM2.5 sources. For the same period, source contributions were estimated by air quality simulations using the Community Multiscale Air Quality model (CMAQ) with the brute-force method (BFM) for four source categories. Both models provided consistent results for the following three of the four source categories: secondary sulfates, road transportation, and heavy oil combustion sources. For these three target categories, the models' agreement was supported by the small differences and high correlations between the CMAQ/BFM- and PMF-estimated source contributions to the concentrations of PM2.5, SO42-, and EC. In contrast, contributions of the biomass burning sources apportioned by CMAQ/BFM were much lower than and little correlated with those captured by the PMF model, indicating large uncertainties in the biomass burning emissions used in the

Assessing suicide risk among callers to crisis hotlines: a confirmatory factor analysis.

PubMed

Witte, Tracy K; Gould, Madelyn S; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E; Kalafat, John

2010-09-01

Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. We conducted an Exploratory Factor Analysis (EFA), an EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and a CFA on independent subsamples derived from a total sample of 1,085. Similar to previous studies, we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations; RPP) and one factor representing milder suicidal ideation (i.e., Suicidal Desire and Ideation; SDI). The RPP factor trended toward being more predictive of suicidal ideation at follow-up than the SDI factor. (c) 2010 Wiley Periodicals, Inc.

Examining the effects of anthropogenic emissions on isoprene-derived secondary organic aerosol formation during the 2013 Southern Oxidant and Aerosol Study (SOAS) at the Look Rock, Tennessee ground site

NASA Astrophysics Data System (ADS)

Budisulistiorini, S. H.; Li, X.; Bairai, S. T.; Renfro, J.; Liu, Y.; Liu, Y. J.; McKinney, K. A.; Martin, S. T.; McNeill, V. F.; Pye, H. O. T.; Nenes, A.; Neff, M. E.; Stone, E. A.; Mueller, S.; Knote, C.; Shaw, S. L.; Zhang, Z.; Gold, A.; Surratt, J. D.

2015-08-01

A suite of offline and real-time gas- and particle-phase measurements was deployed at Look Rock, Tennessee (TN), during the 2013 Southern Oxidant and Aerosol Study (SOAS) to examine the effects of anthropogenic emissions on isoprene-derived secondary organic aerosol (SOA) formation. High- and low-time-resolution PM2.5 samples were collected for analysis of known tracer compounds in isoprene-derived SOA by gas chromatography/electron ionization-mass spectrometry (GC/EI-MS) and ultra performance liquid chromatography/diode array detection-electrospray ionization-high-resolution quadrupole time-of-flight mass spectrometry (UPLC/DAD-ESI-HR-QTOFMS). Source apportionment of the organic aerosol (OA) was determined by positive matrix factorization (PMF) analysis of mass spectrometric data acquired on an Aerodyne Aerosol Chemical Speciation Monitor (ACSM). Campaign average mass concentrations of the sum of quantified isoprene-derived SOA tracers contributed to ~ 9 % (up to 28 %) of the total OA mass, with isoprene-epoxydiol (IEPOX) chemistry accounting for ~ 97 % of the quantified tracers. PMF analysis resolved a factor with a profile similar to the IEPOX-OA factor resolved in an Atlanta study and was therefore designated IEPOX-OA. This factor was strongly correlated (r2 > 0.7) with 2-methyltetrols, C5-alkene triols, IEPOX-derived organosulfates, and dimers of organosulfates, confirming the role of IEPOX chemistry as the source. On average, IEPOX-derived SOA tracer mass was ~ 26 % (up to 49 %) of the IEPOX-OA factor mass, which accounted for 32 % of the total OA. A low-volatility oxygenated organic aerosol (LV-OOA) and an oxidized factor with a profile similar to 91Fac observed in areas where emissions are biogenic-dominated were also resolved by PMF analysis, whereas no primary organic aerosol (POA) sources could be resolved. These findings were consistent with low levels of primary pollutants, such as nitric oxide (NO ~ 0.03 ppb), carbon monoxide (CO ~ 116 ppb), and black

Examining the effects of anthropogenic emissions on isoprene-derived secondary organic aerosol formation during the 2013 Southern Oxidant and Aerosol Study (SOAS) at the Look Rock, Tennessee, ground site

NASA Astrophysics Data System (ADS)

Budisulistiorini, S. H.; Li, X.; Bairai, S. T.; Renfro, J.; Liu, Y.; Liu, Y. J.; McKinney, K. A.; Martin, S. T.; McNeill, V. F.; Pye, H. O. T.; Nenes, A.; Neff, M. E.; Stone, E. A.; Mueller, S.; Knote, C.; Shaw, S. L.; Zhang, Z.; Gold, A.; Surratt, J. D.

2015-03-01

A suite of offline and real-time gas- and particle-phase measurements was deployed at Look Rock, Tennessee (TN), during the 2013 Southern Oxidant and Aerosol Study (SOAS) to examine the effects of anthropogenic emissions on isoprene-derived secondary organic aerosol (SOA) formation. High- and low-time resolution PM2.5 samples were collected for analysis of known tracer compounds in isoprene-derived SOA by gas chromatography/electron ionization-mass spectrometry (GC/EI-MS) and ultra performance liquid chromatography/diode array detection-electrospray ionization-high-resolution quadrupole time-of-flight mass spectrometry (UPLC/DAD-ESI-HR-QTOFMS). Source apportionment of the organic aerosol (OA) was determined by positive matrix factorization (PMF) analysis of mass spectrometric data acquired on an Aerodyne Aerosol Chemical Speciation Monitor (ACSM). Campaign average mass concentrations of the sum of quantified isoprene-derived SOA tracers contributed to ~9% (up to 26%) of the total OA mass, with isoprene-epoxydiol (IEPOX) chemistry accounting for ~97% of the quantified tracers. PMF analysis resolved a factor with a profile similar to the IEPOX-OA factor resolved in an Atlanta study and was therefore designated IEPOX-OA. This factor was strongly correlated (r2>0.7) with 2-methyltetrols, C5-alkene triols, IEPOX-derived organosulfates, and dimers of organosulfates, confirming the role of IEPOX chemistry as the source. On average, IEPOX-derived SOA tracer mass was ~25% (up to 47%) of the IEPOX-OA factor mass, which accounted for 32% of the total OA. A low-volatility oxygenated organic aerosol (LV-OOA) and an oxidized factor with a profile similar to 91Fac observed in areas where emissions are biogenic-dominated were also resolved by PMF analysis, whereas no primary organic aerosol (POA) sources could be resolved. These findings were consistent with low levels of primary pollutants, such as nitric oxide (NO~0.03ppb), carbon monoxide (CO~116 ppb), and black carbon (BC~0

Factor analysis of serogroups botanica and aurisina of Leptospira biflexa.

PubMed

Cinco, M

1977-11-01

Factor analysis is performed on serovars of Botanica and Aurisina serogroup of Leptospira biflexa. The results show the arrangement of main factors serovar and serogroup specific, as well as the antigens common with serovars of heterologous serogroups.

Risk factors for baclofen pump infection in children: a multivariate analysis.

PubMed

Spader, Heather S; Bollo, Robert J; Bowers, Christian A; Riva-Cambrin, Jay

2016-06-01

OBJECTIVE Intrathecal baclofen infusion systems to manage severe spasticity and dystonia are associated with higher infection rates in children than in adults. Factors unique to this population, such as poor nutrition and physical limitations for pump placement, have been hypothesized as the reasons for this disparity. The authors assessed potential risk factors for infection in a multivariate analysis. METHODS Patients who underwent implantation of a programmable pump and intrathecal catheter for baclofen infusion at a single center between January 1, 2000, and March 1, 2012, were identified in this retrospective cohort study. The primary end point was infection. Potential risk factors investigated included preoperative (i.e., demographics, body mass index [BMI], gastrostomy tube, tracheostomy, previous spinal fusion), intraoperative (i.e., surgeon, antibiotics, pump size, catheter location), and postoperative (i.e., wound dehiscence, CSF leak, and number of revisions) factors. Univariate analysis was performed, and a multivariate logistic regression model was created to identify independent risk factors for infection. RESULTS A total of 254 patients were evaluated. The overall infection rate was 9.8%. Univariate analysis identified young age, shorter height, lower weight, dehiscence, CSF leak, and number of revisions within 6 months of pump placement as significantly associated with infection. Multivariate analysis identified young age, dehiscence, and number of revisions as independent risk factors for infection. CONCLUSIONS Young age, wound dehiscence, and number of revisions were independent risk factors for infection in this pediatric cohort. A low BMI and the presence of either a gastrostomy or tracheostomy were not associated with infection and may not be contraindications for this procedure.

Potential of mean force for ion pairs in non-aqueous solvents. Comparison of polarizable and non-polarizable MD simulations

NASA Astrophysics Data System (ADS)

Odinokov, A. V.; Leontyev, I. V.; Basilevsky, M. V.; Petrov, N. Ch.

2011-01-01

Potentials of mean force (PMF) are calculated for two model ion pairs in two non-aqueous solvents. Standard non-polarizable molecular dynamics simulation (NPMD) and approximate polarizable simulation (PMD) are implemented and compared as tools for monitoring PMF profiles. For the polar solvent (dimethylsulfoxide, DMSO) the PMF generated in terms of the NPMD reproduces fairly well the refined PMD-PMF profile. For the non-polar solvent (benzene) the conventional NPMD computation proves to be deficient. The validity of the correction found in terms of the approximate PMD approach is verified by its comparison with the result of the explicit PMD computation in benzene. The shapes of the PMF profiles in DMSO and in benzene are quite different. In DMSO, owing to dielectric screening, the PMF presents a flat plot with a shallow minimum positioned in the vicinity of the van der Waals contact of the ion pair. For the benzene case, the observed minimum proves to be unexpectedly deep, which manifests the formation of a tightly-binded contact ion pair. This remarkable effect arises owing to the strong electrostatic interaction that is incompletely screened by a non-polar medium. The PMFs for the binary benzene/DMSO mixtures display intermediate behaviour depending on the DMSO content.

Identification and determination of the contribution of iron-steel manufacturing industry to sediment-associated polycyclic aromatic hydrocarbons (PAHs) in a large shallow lake of eastern China.

PubMed

Zhang, Liu; Bai, Ya-Shu; Wang, Ji-Zhong; Peng, Shu-Chuan; Chen, Tian-Hu; Yin, Da-Qiang

2016-11-01

Seventeen polycyclic aromatic hydrocarbon (PAH) compounds were determined in surface sediments collected from the Chaohu Lake (a large shallow lake in eastern China) and its tributaries. Both diagnostic ratios and a receptor model (positive matrix factorization, PMF) were applied to identify and determine the contribution of a local iron-steel manufacturing plant located in the Nanfei River (NFR) to the Chaohu Lake basin. The results show that sites located in the downstream of the steel plant contained concentrations of 17 PAH (Σ 17 PAH) approximately two orders of magnitudes higher than those from other sites. Five factors were identified by the PMF model, including industrial waste, wood/biomass burning, diagenetic origin, domestic coal combustion, and industrial combustion. Our findings suggest that sediments in the downstream of the plant and in the western part of the Chaohu Lake were predominantly affected by industrial coal combustion. A mixture of pyrolytic origins impacted urban sediments in the upstream of the plant, whereas diagenetic origins along with coal and biomass burning were suggested to influence the eastern part and rural tributaries of the lake. To assess the potential ecological risk and toxicity caused by the iron-steel plant, sediment toxicity was evaluated by the PMF model, sediment quality guideline, and toxic equivalent factors. All of the three approaches suggested PAH accumulation in the NFR sediments could produce significant adverse ecological effects and half of the sediment toxicity in the NFR may be attributed to the emissions from the iron-steel plant. Some rural locations also exhibited PAH concentrations above probable effects, most likely contributed by wood/biomass burning.

FACTOR 9.2: A Comprehensive Program for Fitting Exploratory and Semiconfirmatory Factor Analysis and IRT Models

ERIC Educational Resources Information Center

Lorenzo-Seva, Urbano; Ferrando, Pere J.

2013-01-01

FACTOR 9.2 was developed for three reasons. First, exploratory factor analysis (FA) is still an active field of research although most recent developments have not been incorporated into available programs. Second, there is now renewed interest in semiconfirmatory (SC) solutions as suitable approaches to the complex structures are commonly found…

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Process factors of enzyme concentration, time, power and frequency were investigated for ultrasound-enhanced bioscouring of greige cotton. A fractional factorial experimental design and subsequent regression analysis of the process factors were employed to determine the significance of each factor a...

Identifying influential factors of business process performance using dependency analysis

NASA Astrophysics Data System (ADS)

Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

2011-02-01

We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

Confirmatory Factor Analysis of the WISC-III with Child Psychiatric Inpatients.

ERIC Educational Resources Information Center

Tupa, David J.; Wright, Margaret O'Dougherty; Fristad, Mary A.

1997-01-01

Factor models of the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) for one, two, three, and four factors were tested using confirmatory factor analysis with a sample of 177 child psychiatric inpatients. The four-factor model proposed in the WISC-III manual provided the best fit to the data. (SLD)

Emotional experiences and motivating factors associated with fingerprint analysis.

PubMed

Charlton, David; Fraser-Mackenzie, Peter A F; Dror, Itiel E

2010-03-01

In this study, we investigated the emotional and motivational factors involved in fingerprint analysis in day-to-day routine case work and in significant and harrowing criminal investigations. Thematic analysis was performed on interviews with 13 experienced fingerprint examiners from a variety of law enforcement agencies. The data revealed factors relating to job satisfaction and the use of skill. Individual satisfaction related to catching criminals was observed; this was most notable in solving high profile, serious, or long-running cases. There were positive emotional effects associated with matching fingerprints and apparent fear of making errors. Finally, we found evidence for a need of cognitive closure in fingerprint examiner decision-making.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

ATP sensitive K+ channel subunits (Kir6.1, Kir6.2) are the candidate mediators regulating ameliorating effects of pulsed magnetic field on aortic contractility in diabetic rats.

PubMed

Ocal, Isil; Yilmaz, Mehmet B; Kocaturk-Sel, Sabriye; Tufan, Turan; Erkoc, Mehmet A; Comertpay, Gamze; Oksuz, Hale; Barc, Esma D

2018-05-01

Diabetes mellitus is a metabolic disease that causes increased morbidity and mortality in developed and developing countries. With recent advancements in technology, alternative treatment methods have begun to be investigated in the world. This study aims to evaluate the effect of pulsed magnetic field (PMF) on vascular complications and contractile activities of aortic rings along with Kir6.1 and Kir6.2 subunit expressions of ATP-sensitive potassium channels (K ATP ) in aortas of controlled-diabetic and non-controlled diabetic rats. Controlled-diabetic and non-controlled diabetic adult male Wistar rats were exposed to PMF for a period of 6 weeks according to the PMF application protocol (1 h/day; intensity: 1.5 mT; consecutive frequency: 1, 10, 20, and 40 Hz). After PMF exposure, body weight and blood glucose levels were measured. Then, thoracic aorta tissue was extracted for relaxation-contraction and Kir6.1 and Kir6.2 expression experiments. Blood plasma glucose levels, body weight, and aortic ring contraction percentage decreased in controlled-diabetic rats but increased in non-controlled diabetic rats. PMF therapy repressed Kir6.1 mRNA expression in non-controlled diabetic rats but not in controlled diabetic rats. Conversely, Kir6.2 mRNA expressions were repressed both in controlled diabetic and non-controlled diabetic rats by PMF. Our findings suggest that the positive therapeutic effects of PMF may act through (K ATP ) subunits and may frequently occur in insulin-free conditions. Bioelectromagnetics. 39:299-311, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

What Is Rotating in Exploratory Factor Analysis?

ERIC Educational Resources Information Center

Osborne, Jason W.

2015-01-01

Exploratory factor analysis (EFA) is one of the most commonly-reported quantitative methodology in the social sciences, yet much of the detail regarding what happens during an EFA remains unclear. The goal of this brief technical note is to explore what "rotation" is, what exactly is rotating, and why we use rotation when performing…

Uncertainty in positive matrix factorization solutions for PAHs in surface sediments of the Yangtze River Estuary in different seasons.

PubMed

Liu, Ruimin; Men, Cong; Yu, Wenwen; Xu, Fei; Wang, Qingrui; Shen, Zhenyao

2018-01-01

To examine the variabilities of source contributions in the Yangtze River Estuary (YRE), the uncertainty based on the positive matrix factorization (PMF) was applied to the source apportionment of the 16 priority PAHs in 120 surface sediment samples from four seasons. Based on the signal-to-noise ratios, the PAHs categorized as "Bad" might drop out of the estimation of bootstrap. Next, the spatial variability of residuals was applied to determine which species with non-normal curves should be excluded. The median values from the bootstrapped solutions were chosen as the best estimate of the true factor contributions, and the intervals from 5th to 95th percentile represent the variability in each sample factor contribution. Based on the results, the median factor contributions of wood grass combustion and coke plant emissions were highly correlated with the variability (R 2  = 0.6797-0.9937) in every season. Meanwhile, the factor of coal and gasoline combustion had large variability with lower R 2 values in every season, especially in summer (0.4784) and winter (0.2785). The coefficient of variation (CV) values based on the Bootstrap (BS) simulations were applied to indicate the uncertainties of PAHs in every factor of each season. Acy, NaP and BgP always showed higher CV values, which suggested higher uncertainties in the BS simulations, and the PAH with the lowest concentration among all PAHs usually became the species with higher uncertainties. Copyright © 2017 Elsevier Ltd. All rights reserved.

Contamination characteristics and source apportionment of trace metals in soils around Miyun Reservoir.

PubMed

Chen, Haiyang; Teng, Yanguo; Chen, Ruihui; Li, Jiao; Wang, Jinsheng

2016-08-01

Due to their toxicity and bioaccumulation, trace metals in soils can result in a wide range of toxic effects on animals, plants, microbes, and even humans. Recognizing the contamination characteristics of soil metals and especially apportioning their potential sources are the necessary preconditions for pollution prevention and control. Over the past decades, several receptor models have been developed for source apportionment. Among them, positive matrix factorization (PMF) has gained popularity and was recommended by the US Environmental Protection Agency as a general modeling tool. In this study, an extended chemometrics model, multivariate curve resolution-alternating least squares based on maximum likelihood principal component analysis (MCR-ALS/MLPCA), was proposed for source apportionment of soil metals and applied to identify the potential sources of trace metals in soils around Miyun Reservoir. Similar to PMF, the MCR-ALS/MLPCA model can incorporate measurement error information and non-negativity constraints in its calculation procedures. Model validation with synthetic dataset suggested that the MCR-ALS/MLPCA could extract acceptable recovered source profiles even considering relatively larger error levels. When applying to identify the sources of trace metals in soils around Miyun Reservoir, the MCR-ALS/MLPCA model obtained the highly similar profiles with PMF. On the other hand, the assessment results of contamination status showed that the soils around reservoir were polluted by trace metals in slightly moderate degree but potentially posed acceptable risks to the public. Mining activities, fertilizers and agrochemicals, and atmospheric deposition were identified as the potential anthropogenic sources with contributions of 24.8, 14.6, and 13.3 %, respectively. In order to protect the drinking water source of Beijing, special attention should be paid to the metal inputs to soils from mining and agricultural activities.

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

NASA Astrophysics Data System (ADS)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

Spatial and temporal variability of fine particle composition and source types in five cities of Connecticut and Massachusetts

PubMed Central

Lee, Hyung Joo; Gent, Janneane F.; Leaderer, Brian P.; Koutrakis, Petros

2011-01-01

To protect public health from PM2.5 air pollution, it is critical to identify the source types of PM2.5 mass and chemical components associated with higher risks of adverse health outcomes. Source apportionment modeling using Positive Matrix Factorization (PMF), was used to identify PM2.5 source types and quantify the source contributions to PM2.5 in five cities of Connecticut and Massachusetts. Spatial and temporal variability of PM2.5 mass, components and source contributions were investigated. PMF analysis identified five source types: regional pollution as traced by sulfur, motor vehicle, road dust, oil combustion and sea salt. The sulfur-related regional pollution and traffic source type were major contributors to PM2.5. Due to sparse ground-level PM2.5 monitoring sites, current epidemiological studies are susceptible to exposure measurement errors. The higher correlations in concentrations and source contributions between different locations suggest less spatial variability, resulting in less exposure measurement errors. When concentrations and/or contributions were compared to regional averages, correlations were generally higher than between-site correlations. This suggests that for assigning exposures for health effects studies, using regional average concentrations or contributions from several PM2.5 monitors is more reliable than using data from the nearest central monitor. PMID:21429560

Comparison of source apportionment of PM2.5 using receptor models in the main hub port city of East Asia: Busan

NASA Astrophysics Data System (ADS)

Jeong, Ju-Hee; Shon, Zang-Ho; Kang, Minsung; Song, Sang-Keun; Kim, Yoo-Keun; Park, Jinsoo; Kim, Hyunjae

2017-01-01

The contributions of various PM2.5 emission sources to ambient PM2.5 levels during 2013 in the main hub port city (Busan, South Korea) of East Asia was quantified using several receptor modeling techniques. Three receptor models of principal component analysis/absolute principal component score (PCA/APCS), positive matrix factorization (PMF), and chemical mass balance (CMB) were used to apportion the source of PM2.5 obtained from the target city. The results of the receptor models indicated that the secondary formation of PM2.5 was the dominant (45-60%) contributor to PM2.5 levels in the port city of Busan. The PMF and PCA/APCS suggested that ship emission was a non-negligible contributor of PM2.5 (up to about 10%) in the study area, whereas it was a negligible contributor based on CMB. The magnitude of source contribution estimates to PM2.5 levels differed significantly among these three models due to their limitations (e.g., PM2.5 emission source profiles and restrictions of the models). Potential source contribution function and concentration-weighted trajectory analyses indicated that long-range transport from sources in the eastern China and Yellow Sea contributed significantly to the level of PM2.5 in Busan.

Confirmatory Factor Analysis of the Delirium Rating Scale Revised-98 (DRS-R98).

PubMed

Thurber, Steven; Kishi, Yasuhiro; Trzepacz, Paula T; Franco, Jose G; Meagher, David J; Lee, Yanghyun; Kim, Jeong-Lan; Furlanetto, Leticia M; Negreiros, Daniel; Huang, Ming-Chyi; Chen, Chun-Hsin; Kean, Jacob; Leonard, Maeve

2015-01-01

Principal components analysis applied to the Delirium Rating Scale-Revised-98 contributes to understanding the delirium construct. Using a multisite pooled international delirium database, the authors applied confirmatory factor analysis to Delirium Rating Scale-Revised-98 scores from 859 adult patients evaluated by delirium experts (delirium, N=516; nondelirium, N=343). Confirmatory factor analysis found all diagnostic features and core symptoms (cognitive, language, thought process, sleep-wake cycle, motor retardation), except motor agitation, loaded onto factor 1. Motor agitation loaded onto factor 2 with noncore symptoms (delusions, affective lability, and perceptual disturbances). Factor 1 loading supports delirium as a single construct, but when accompanied by psychosis, motor agitation's role may not be solely as a circadian activity indicator.

Factor Analysis of the Aberrant Behavior Checklist in Individuals with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Brinkley, Jason; Nations, Laura; Abramson, Ruth K.; Hall, Alicia; Wright, Harry H.; Gabriels, Robin; Gilbert, John R.; Pericak-Vance, Margaret A. O.; Cuccaro, Michael L.

2007-01-01

Exploratory factor analysis (varimax and promax rotations) of the aberrant behavior checklist-community version (ABC) in 275 individuals with Autism spectrum disorder (ASD) identified four- and five-factor solutions which accounted for greater than 70% of the variance. Confirmatory factor analysis (Lisrel 8.7) revealed indices of moderate fit for…

A factor analysis of landscape pattern and structure metrics

Treesearch

Kurt H. Riitters; R.V. O' Neill; C.T. Hunsaker; James D. Wickham; D.H. Yankee; S.P. Timmins; K.B. Jones; B.L. Jackson

1995-01-01

Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These...

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

PubMed

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

Bayes factor design analysis: Planning for compelling evidence.

PubMed

Schönbrodt, Felix D; Wagenmakers, Eric-Jan

2018-02-01

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis significance testing (NHST) paradigm to facilitate the design of informative experiments. In contrast, there is almost no literature that discusses the design of experiments when Bayes factors (BFs) are used as a measure of evidence. Here we explore Bayes Factor Design Analysis (BFDA) as a useful tool to design studies for maximum efficiency and informativeness. We elaborate on three possible BF designs, (a) a fixed-n design, (b) an open-ended Sequential Bayes Factor (SBF) design, where researchers can test after each participant and can stop data collection whenever there is strong evidence for either [Formula: see text] or [Formula: see text], and (c) a modified SBF design that defines a maximal sample size where data collection is stopped regardless of the current state of evidence. We demonstrate how the properties of each design (i.e., expected strength of evidence, expected sample size, expected probability of misleading evidence, expected probability of weak evidence) can be evaluated using Monte Carlo simulations and equip researchers with the necessary information to compute their own Bayesian design analyses.

Application of the Bootstrap Methods in Factor Analysis.

ERIC Educational Resources Information Center

Ichikawa, Masanori; Konishi, Sadanori

1995-01-01

A Monte Carlo experiment was conducted to investigate the performance of bootstrap methods in normal theory maximum likelihood factor analysis when the distributional assumption was satisfied or unsatisfied. Problems arising with the use of bootstrap methods are highlighted. (SLD)

Propellant Mass Fraction Calculation Methodology for Launch Vehicles

NASA Technical Reports Server (NTRS)

Holt, James B.; Monk, Timothy S.

2009-01-01

Propellant Mass Fraction (pmf) calculation methods vary throughout the aerospace industry. While typically used as a means of comparison between competing launch vehicle designs, the actual pmf calculation method varies slightly from one entity to another. It is the purpose of this paper to present various methods used to calculate the pmf of a generic launch vehicle. This includes fundamental methods of pmf calculation which consider only the loaded propellant and the inert mass of the vehicle, more involved methods which consider the residuals and any other unusable propellant remaining in the vehicle, and other calculations which exclude large mass quantities such as the installed engine mass. Finally, a historic comparison is made between launch vehicles on the basis of the differing calculation methodologies.

Exploratory Factor Analysis with Small Sample Sizes

ERIC Educational Resources Information Center

de Winter, J. C. F.; Dodou, D.; Wieringa, P. A.

2009-01-01

Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…

Space Human Factors Engineering Gap Analysis Project Final Report

NASA Technical Reports Server (NTRS)

Hudy, Cynthia; Woolford, Barbara

2006-01-01

Humans perform critical functions throughout each phase of every space mission, beginning with the mission concept and continuing to post-mission analysis (Life Sciences Division, 1996). Space missions present humans with many challenges - the microgravity environment, relative isolation, and inherent dangers of the mission all present unique issues. As mission duration and distance from Earth increases, in-flight crew autonomy will increase along with increased complexity. As efforts for exploring the moon and Mars advance, there is a need for space human factors research and technology development to play a significant role in both on-orbit human-system interaction, as well as the development of mission requirements and needs before and after the mission. As part of the Space Human Factors Engineering (SHFE) Project within the Human Research Program (HRP), a six-month Gap Analysis Project (GAP) was funded to identify any human factors research gaps or knowledge needs. The overall aim of the project was to review the current state of human factors topic areas and requirements to determine what data, processes, or tools are needed to aid in the planning and development of future exploration missions, and also to prioritize proposals for future research and technology development.

Assessing Suicide Risk Among Callers to Crisis Hotlines: A Confirmatory Factor Analysis

PubMed Central

Witte, Tracy K.; Gould, Madelyn S.; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E.; Kalafat, John

2012-01-01

Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. 1,085 suicidal callers to crisis hotlines were divided into three sub-samples, which allowed us to conduct an independent Exploratory Factor Analysis (EFA), EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and CFA. Similar to previous factor analytic studies (Beck et al., 1997; Holden & DeLisle, 2005; Joiner, Rudd, & Rajab, 1997; Witte et al., 2006), we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations) and one factor representing more mild suicidal ideation (i.e., Suicidal Desire and Ideation). Using structural equation modeling techniques, we found preliminary evidence that the Resolved Plans and Preparations factor trended toward being more predictive of suicidal ideation than the Suicidal Desire and Ideation factor. This factor analytic study is the first longitudinal study of the obtained factors. PMID:20578186

Factor analysis of some socio-economic and demographic variables for Bangladesh.

PubMed

Islam, S M

1986-01-01

The author carries out an exploratory factor analysis of some socioeconomic and demographic variables for Bangladesh using the classical or common factor approach with the varimax rotation method. The socioeconomic and demographic indicators used in this study include literacy, rate of growth, female employment, economic development, urbanization, population density, childlessness, sex ratio, proportion of women ever married, and fertility. The 18 administrative districts of Bangladesh constitute the unit of analysis. 3 common factors--modernization, fertility, and social progress--are identified in this study to explain the correlations among the set of selected socioeconomic and demographic variables.

Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

PubMed

Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-09-01

Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. �

Bayesian Factor Analysis as a Variable Selection Problem: Alternative Priors and Consequences

PubMed Central

Lu, Zhao-Hua; Chow, Sy-Miin; Loken, Eric

2016-01-01

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, a Bayesian structural equation modeling (BSEM) approach (Muthén & Asparouhov, 2012) has been proposed as a way to explore the presence of cross-loadings in CFA models. We show that the issue of determining factor loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov’s approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike and slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set (Byrne, 2012; Pettegrew & Wolf, 1982) is used to demonstrate our approach. PMID:27314566

Confirmatory Factor Analysis of the Cancer Locus of Control Scale.

ERIC Educational Resources Information Center

Henderson, Jessica W.; Donatelle, Rebecca J.; Acock, Alan C.

2002-01-01

Conducted a confirmatory factor analysis of the Cancer Locus of Control scale (M. Watson and others, 1990), administered to 543 women with a history of breast cancer. Results support a three-factor model of the scale and support use of the scale to assess control dimensions. (SLD)

Analysis of Social Cohesion in Health Data by Factor Analysis Method: The Ghanaian Perspective

ERIC Educational Resources Information Center

Saeed, Bashiru I. I.; Xicang, Zhao; Musah, A. A. I.; Abdul-Aziz, A. R.; Yawson, Alfred; Karim, Azumah

2013-01-01

We investigated the study of the overall social cohesion of Ghanaians. In this study, we considered the paramount interest of the involvement of Ghanaians in their communities, their views of other people and institutions, and their level of interest in both local and national politics. The factor analysis method was employed for analysis using R…

Evidence Regarding the Internal Structure: Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Lewis, Todd F.

2017-01-01

American Educational Research Association (AERA) standards stipulate that researchers show evidence of the internal structure of instruments. Confirmatory factor analysis (CFA) is one structural equation modeling procedure designed to assess construct validity of assessments that has broad applicability for counselors interested in instrument…

Accelerating potential of mean force calculations for lipid membrane permeation: System size, reaction coordinate, solute-solute distance, and cutoffs

NASA Astrophysics Data System (ADS)

Nitschke, Naomi; Atkovska, Kalina; Hub, Jochen S.

2016-09-01

Molecular dynamics simulations are capable of predicting the permeability of lipid membranes for drug-like solutes, but the calculations have remained prohibitively expensive for high-throughput studies. Here, we analyze simple measures for accelerating potential of mean force (PMF) calculations of membrane permeation, namely, (i) using smaller simulation systems, (ii) simulating multiple solutes per system, and (iii) using shorter cutoffs for the Lennard-Jones interactions. We find that PMFs for membrane permeation are remarkably robust against alterations of such parameters, suggesting that accurate PMF calculations are possible at strongly reduced computational cost. In addition, we evaluated the influence of the definition of the membrane center of mass (COM), used to define the transmembrane reaction coordinate. Membrane-COM definitions based on all lipid atoms lead to artifacts due to undulations and, consequently, to PMFs dependent on membrane size. In contrast, COM definitions based on a cylinder around the solute lead to size-independent PMFs, down to systems of only 16 lipids per monolayer. In summary, compared to popular setups that simulate a single solute in a membrane of 128 lipids with a Lennard-Jones cutoff of 1.2 nm, the measures applied here yield a speedup in sampling by factor of ˜40, without reducing the accuracy of the calculated PMF.

The Role of Interfacial Water in Protein-Ligand Binding: Insights from the Indirect Solvent Mediated Potential of Mean Force.

PubMed

Cui, Di; Zhang, Bin W; Matubayasi, Nobuyuki; Levy, Ronald M

2018-02-13

Classical density functional theory (DFT) can be used to relate the thermodynamic properties of solutions to the indirect solvent mediated part of the solute-solvent potential of mean force (PMF). Standard, but powerful numerical methods can be used to estimate the solute-solvent PMF from which the indirect part can be extracted. In this work we show how knowledge of the direct and indirect parts of the solute-solvent PMF for water at the interface of a protein receptor can be used to gain insights about how to design tighter binding ligands. As we show, the indirect part of the solute-solvent PMF is equal to the sum of the 1-body (energy + entropy) terms in the inhomogeneous solvation theory (IST) expansion of the solvation free energy. To illustrate the effect of displacing interfacial water molecules with particular direct/indirect PMF signatures on the binding of ligands, we carry out simulations of protein binding with several pairs of congeneric ligands. We show that interfacial water locations that contribute favorably or unfavorably at the 1-body level (energy + entropy) to the solvation free energy of the solute can be targeted as part of the ligand design process. Water locations where the indirect PMF is larger in magnitude provide better targets for displacement when adding a functional group to a ligand core.

Pulsed magnetic field enhances therapeutic efficiency of mesenchymal stem cells in chronic neuropathic pain model.

PubMed

Mert, Tufan; Kurt, Akif Hakan; Altun, İdiris; Celik, Ahmet; Baran, Furkan; Gunay, Ismail

2017-05-01

Cell-based or magnetic field therapies as alternative approaches to pain management have been tested in several experimental pain models. The aim of this study therefore was to investigate the actions of the cell-based therapy (adipose tissue derived mesenchymal stem cells; ADMSC) or pulsed magnetic field (PMF) therapy and magneto-cell therapy (combination of ADMSC and PMF) in chronic constriction nerve injury model (CCI). The actions of individual ADMSC (route dependent [systemic or local], time-dependent [a day or a week after surgery]), or PMF and their combination (magneto-cell) therapies on hyperalgesia and allodynia were investigated by using thermal plantar test and a dynamic plantar aesthesiometer, respectively. In addition, various cytokine levels (IL-1β, IL-6, and IL-10) of rat sciatic nerve after CCI were analyzed. Following the CCI, both latency and threshold significantly decreased. ADMSC or PMF significantly increased latencies and thresholds. The combination of ADMSC with PMF even more significantly increased latency and threshold when compared with ADMSC alone. However, ADMSC-induced decrease in pro-inflammatory or increase in anti-inflammatory cytokines levels were partially prevented by PMF treatments. Present findings may suggest that both cell-based and magnetic therapies can effectively attenuate chronic neuropathic pain symptoms. Combined magneto-cell therapy may also efficiently reverse neuropathic signs. Bioelectromagnetics. 38:255-264, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Improved source apportionment of PAHs and Pb by integrating Pb stable isotopes and positive matrix factorization application (PAHs): A historical record case study from the northern South China Sea.

PubMed

Cai, Minggang; Lin, Yan; Chen, Meng; Yang, Weifeng; Du, Huihong; Xu, Ye; Cheng, Shayen; Xu, Fangjian; Hong, Jiajun; Chen, Mian; Ke, Hongwei

2017-12-31

To obtain the historical changes of pyrogenic sources, integrated source apportionment methods, which include PAH compositions, diagnostic ratios (DRs), Pb isotopic ratios, and positive matrix factorization (PMF) model, were developed and applied in sediments of the northern South China Sea. These methods provided a gradually clear picture of energy structural change. Spatially, Σ 15 PAH (11.3 to 95.5ng/g) and Pb (10.2 to 74.6μg/g) generally exhibited decreasing concentration gradient offshore; while the highest levels of PAHs and Pb were observed near the southern Taiwan Strait, which may be induced by accumulation of different fluvial input. Historical records of pollutants followed closely with the economic development of China, with fast growth of Σ 15 PAH and Pb occurring since the 1980s and 1990s, respectively. The phasing-out of leaded gasoline in China was captured with a sharp decrease of Pb after the mid-1990s. PAHs and Pb correlated well with TOC and clay content for core sediments, which was not observed for surface sediments. There was an up-core increase of high molecular PAH proportions. Coal and biomass burning were then qualitatively identified as the major sources of PAHs with DRs. Furthermore, shift toward less radiogenic signatures of Pb isotopic ratios after 1900 revealed the start and growing importance of industrial sources. Finally, a greater separation and quantification of various input was achieved by a three-factor PMF model, which made it clear that biomass burning, coal combustion, and vehicle emissions accounted for 40±20%, 41±13%, and 19±12% of PAHs through the core. Biomass and coal combustion acted as major sources before 2000, while contributions from vehicle emission soared thereafter. The integrated multi-methodologies here improved the source apportionment by reducing biases with a step-down and cross-validation perspective, which could be similarly applied to other aquatic systems. Copyright © 2017 Elsevier B.V. All

Factor Structure of the Student-Teacher Relationship Scale for Norwegian School-Age Children Explored with Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Drugli, May Britt; Hjemdal, Odin

2013-01-01

The validity of the Student-Teacher Relationship Scale (STRS) was examined in a national sample of 863 Norwegian schoolchildren in grades 1-7 (aged 6-13). The original factor structure of the STRS was tested by confirmatory factor analysis (CFA). The CFA results did not support the original three-factor structure of the STRS. Subsequent CFA of the…

The School Counselor Leadership Survey: Instrument Development and Exploratory Factor Analysis

ERIC Educational Resources Information Center

Young, Anita; Bryan, Julia

2015-01-01

This study examined the factor structure of the School Counselor Leadership Survey (SCLS). Survey development was a threefold process that resulted in a 39-item survey of 801 school counselors and school counselor supervisors. The exploratory factor analysis indicated a five-factor structure that revealed five key dimensions of school counselor…

Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Cheng, Ying; Zhang, Wei

2010-01-01

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found.…

A Primer on Bootstrap Factor Analysis as Applied to Health Studies Research

ERIC Educational Resources Information Center

Lu, Wenhua; Miao, Jingang; McKyer, E. Lisako J.

2014-01-01

Objectives: To demonstrate how the bootstrap method could be conducted in exploratory factor analysis (EFA) with a syntax written in SPSS. Methods: The data obtained from the Texas Childhood Obesity Prevention Policy Evaluation project (T-COPPE project) were used for illustration. A 5-step procedure to conduct bootstrap factor analysis (BFA) was…

Sequential treatment of CD34+ cells from patients with primary myelofibrosis with chromatin-modifying agents eliminate JAK2V617F-positive NOD/SCID marrow repopulating cells

PubMed Central

Wang, Xiaoli; Zhang, Wei; Tripodi, Joseph; Lu, Min; Xu, Mingjiang; Najfeld, Vesna; Li, Yan

2010-01-01

Because primary myelofibrosis (PMF) originates at the level of the pluripotent hematopoietic stem cell (HSC), we examined the effects of various therapeutic agents on the in vitro and in vivo behavior of PMF CD34+ cells. Treatment of PMF CD34+ cells with chromatin-modifying agents (CMAs) but not hydroxyurea, Janus kinase 2 (JAK2) inhibitors, or low doses of interferon-α led to the generation of greater numbers of CD34+ chemokine (C-X-C motif) receptor (CXCR)4+ cells, which were capable of migrating in response to chemokine (C-X-C motif) ligand (CXCL)12 and resulted in a reduction in the proportion of hematopoietic progenitor cells (HPCs) that were JAK2V617F+. Furthermore, sequential treatment of PMF CD34+ cells but not normal CD34+ cells with decitabine (5-aza-2′-deoxycytidine [5azaD]), followed by suberoylanilide hydroxamic acid (SAHA; 5azaD/SAHA), or trichostatin A (5azaD/TSA) resulted in a higher degree of apoptosis. Two to 6 months after the transplantation of CMAs treated JAK2V617F+ PMF CD34+ cells into nonobese diabetic/severe combined immunodeficient (SCID)/IL-2Rγnull mice, the percentage of JAK2V617F/JAK2total in human CD45+ marrow cells was dramatically reduced. These findings suggest that both PMF HPCs, short-term and long-term SCID repopulating cells (SRCs), are JAK2V617F+ and that JAK2V617F+ HPCs and SRCs can be eliminated by sequential treatment with CMAs. Sequential treatment with CMAs, therefore, represents a possible effective means of treating PMF at the level of the malignant SRC. PMID:20858855

Understanding Older Adults' Perceptions of Internet Use: An Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zheng, Robert; Spears, Jeffrey; Luptak, Marilyn; Wilby, Frances

2015-01-01

The current study examined factors related to older adults' perceptions of Internet use. Three hundred ninety five older adults participated in the study. The factor analysis revealed four factors perceived by older adults as critical to their Internet use: social connection, self-efficacy, the need to seek financial information, and the need to…

Myeloproliferative neoplasms: Current molecular biology and genetics.

PubMed

Saeidi, Kolsoum

2016-02-01

Myeloproliferative neoplasms (MPNs) are clonal disorders characterized by increased production of mature blood cells. Philadelphia chromosome-negative MPNs (Ph-MPNs) consist of polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF). A number of stem cell derived mutations have been identified in the past 10 years. These findings showed that JAK2V617F, as a diagnostic marker involving JAK2 exon 14 with a high frequency, is the best molecular characterization of Ph-MPNs. Somatic mutations in an endoplasmic reticulum chaperone, named calreticulin (CALR), is the second most common mutation in patients with ET and PMF after JAK2 V617F mutation. Discovery of CALR mutations led to the increased molecular diagnostic of ET and PMF up to 90%. It has been shown that JAK2V617F is not the unique event in disease pathogenesis. Some other genes' location such as TET oncogene family member 2 (TET2), additional sex combs-like 1 (ASXL1), casitas B-lineage lymphoma proto-oncogene (CBL), isocitrate dehydrogenase 1/2 (IDH1/IDH2), IKAROS family zinc finger 1 (IKZF1), DNA methyltransferase 3A (DNMT3A), suppressor of cytokine signaling (SOCS), enhancer of zeste homolog 2 (EZH2), tumor protein p53 (TP53), runt-related transcription factor 1 (RUNX1) and high mobility group AT-hook 2 (HMGA2) have also identified to be involved in MPNs phenotypes. Here, current molecular biology and genetic mechanisms involved in MNPs with a focus on the aforementioned factors is presented. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Polychlorinated biphenyl congener patterns in fish near the Hanford Site (Washington State, USA).

PubMed

Rodenburg, Lisa A; Delistraty, Damon; Meng, Qingyu

2015-03-03

It is well-known that absorption, distribution, metabolism, and excretion (ADME) processes in fish can alter polychlorinated biphenyl (PCB) congener patterns in fish, but these patterns have never been investigated using an advanced source-apportionment tool. In this work, PCB congener patterns in freshwater fish were examined with positive matrix factorization (PMF). PCB congeners were quantified via EPA Method 1668 in fillet and carcass of six species in four study areas in the Columbia River near the Hanford Site. Six factors were resolved with PMF2 software. Depletion and enhancement of PCB congeners in factors, relative to Aroclor 1254, suggested biotransformation (via cytochrome P450) and bioaccumulation in fish, respectively. Notable differences were observed among species and across study locations. For example, sturgeon and whitefish exhibited congener patterns consistent with Aroclor weathering, suggesting potential PCB metabolism in these species. In terms of location, average concentration of total PCBs for all species combined was significantly higher (P < 0.05) at Hanford 100 and 300 areas, relative to upriver and downriver study sites. Furthermore, a distinct PCB signature in sturgeon and whitefish, collected at Hanford study areas, suggests that Hanford is a unique PCB source.

Confirmatory factor analysis of the Child Oral Health Impact Profile (Korean version).

PubMed

Cho, Young Il; Lee, Soonmook; Patton, Lauren L; Kim, Hae-Young

2016-04-01

Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score. © 2016 Eur J Oral Sci.

Risk analysis of the thermal sterilization process. Analysis of factors affecting the thermal resistance of microorganisms.

PubMed

Akterian, S G; Fernandez, P S; Hendrickx, M E; Tobback, P P; Periago, P M; Martinez, A

1999-03-01

A risk analysis was applied to experimental heat resistance data. This analysis is an approach for processing experimental thermobacteriological data in order to study the variability of D and z values of target microorganisms depending on the deviations range of environmental factors, to determine the critical factors and to specify their critical tolerance. This analysis is based on sets of sensitivity functions applied to a specific case of experimental data related to the thermoresistance of Clostridium sporogenes and Bacillus stearothermophilus spores. The effect of the following factors was analyzed: the type of target microorganism; nature of the heating substrate; pH, temperature; type of acid employed and NaCl concentration. The type of target microorganism to be inactivated, the nature of the substrate (reference or real food) and the heating temperature were identified as critical factors, determining about 90% of the alteration of the microbiological risk. The effect of the type of acid used for the acidification of products and the concentration of NaCl can be assumed to be negligible factors for the purposes of engineering calculations. The critical non-uniformity in temperature during thermobacteriological studies was set as 0.5% and the critical tolerances of pH value and NaCl concentration were 5%. These results are related to a specific case study, for that reason their direct generalization is not correct.

Chemical factor analysis of skin cancer FTIR-FEW spectroscopic data

NASA Astrophysics Data System (ADS)

Bruch, Reinhard F.; Sukuta, Sydney

2002-03-01

Chemical Factor Analysis (CFA) algorithms were applied to transform complex Fourier transform infrared fiberoptical evanescent wave (FTIR-FEW) normal and malignant skin tissue spectra into factor spaces for analysis and classification. The factor space approach classified melanoma beyond prior pathological classifications related to specific biochemical alterations to health states in cluster diagrams allowing diagnosis with more biochemical specificity, resolving biochemical component spectra and employing health state eigenvector angular configurations as disease state sensors. This study demonstrated a wealth of new information from in vivo FTIR-FEW spectral tissue data, without extensive a priori information or clinically invasive procedures. In particular, we employed a variety of methods used in CFA to select the rank of spectroscopic data sets of normal benign and cancerous skin tissue. We used the Malinowski indicator function (IND), significance level and F-Tests to rank our data matrices. Normal skin tissue, melanoma and benign tumors were modeled by four, two and seven principal abstract factors, respectively. We also showed that the spectrum of the first eigenvalue was equivalent to the mean spectrum. The graphical depiction of angular disparities between the first abstract factors can be adopted as a new way to characterize and diagnose melanoma cancer.

Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

PubMed Central

Flora, David B.; LaBrish, Cathy; Chalmers, R. Philip

2011-01-01

We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables. PMID:22403561

PM₁₀ and PM₂.₅ sources at an insular location in the western Mediterranean by using source apportionment techniques.

PubMed

Pey, Jorge; Alastuey, Andrés; Querol, Xavier

2013-07-01

PM₁₀ and PM₂.₅ chemical composition has been determined at a suburban insular site in the Balearic Islands (Spain) during almost one and a half year. As a result, 200 samples with more than 50 chemical parameters analyzed have been obtained. The whole database has been analyzed by two receptor modelling techniques (Principal Component Analysis and Positive Matrix Factorisation) in order to identify the main PM sources. After that, regression analyses with respect to the PM mass concentrations were conducted to quantify the daily contributions of each source. Four common sources were identified by both receptor models: secondary nitrate coupled with vehicular emissions, secondary sulphate influenced by fuel-oil combustion, aged marine aerosols and mineral dust. In addition, PCA isolated harbour emissions and a mixed anthropogenic factor containing industrial emissions; whereas PMF isolated an additional mineral factor interpreted as road dust+harbour emissions, and a vehicular abrasion products factor. The use of both methodologies appeared complementary. Nevertheless, PMF sources by themselves were better differentiated. Besides these receptor models, a specific methodology to quantify African dust was also applied. The combination of these three source apportionment tools allowed the identification of 8 sources, being 4 of them mineral (African, regional, urban and harbour dusts). As a summary, 29% of PM₁₀ was attributed to natural sources (African dust, regional dust and sea spray), whereas the proportion diminished to 11% in PM₂.₅. Furthermore, the secondary sulphate source, which accounted for about 22 and 32% of PM₁₀ and PM₂.₅, is strongly linked to the aged polluted air masses residing over the western Mediterranean in the warm period. Copyright © 2013 Elsevier B.V. All rights reserved.

Seasonal variations and source estimation of saccharides in atmospheric particulate matter in Beijing, China.

PubMed

Liang, Linlin; Engling, Guenter; Du, Zhenyu; Cheng, Yuan; Duan, Fengkui; Liu, Xuyan; He, Kebin

2016-05-01

Saccharides are important constituents of atmospheric particulate matter (PM). In order to better understand the sources and seasonal variations of saccharides in aerosols in Beijing, China, saccharide composition was measured in ambient PM samples collected at an urban site in Beijing. The highest concentrations of total saccharides in Beijing were observed in autumn, while an episode with abnormal high total saccharide levels was observed from 15 to 23 June, 2011, due to extensive agricultural residue burning in northern China during the wheat harvest season. Compared to the other two categories of saccharides, sugars and sugar alcohols, anhydrosugars were the predominant saccharide group, indicating that biomass burning contributions to Beijing urban aerosol were significant. Ambient sugar and sugar alcohol levels in summer and autumn were higher than those in spring and winter, while they were more abundant in PM2.5 during winter time. Levoglucosan was the most abundant saccharide compound in both PM2.5 and PM10, the annual contributions of which to total measured saccharides in PM2.5 and PM10 were 61.5% and 54.1%, respectively. To further investigate the sources of the saccharides in ambient aerosols in Beijing, the PM10 datasets were subjected to positive matrix factorization (PMF) analysis. Based on the objective function to be minimized and the interpretable factors identified by PMF, six factors appeared to be optimal as to the probable origin of saccharides in the atmosphere in Beijing, including biomass burning, soil or dust, isoprene SOA and the direct release of airborne fungal spores and pollen. Copyright © 2016 Elsevier Ltd. All rights reserved.

Determinants of job stress in chemical process industry: A factor analysis approach.

PubMed

Menon, Balagopal G; Praveensal, C J; Madhu, G

2015-01-01

Job stress is one of the active research domains in industrial safety research. The job stress can result in accidents and health related issues in workers in chemical process industries. Hence it is important to measure the level of job stress in workers so as to mitigate the same to avoid the worker's safety related problems in the industries. The objective of this study is to determine the job stress factors in the chemical process industry in Kerala state, India. This study also aims to propose a comprehensive model and an instrument framework for measuring job stress levels in the chemical process industries in Kerala, India. The data is collected through a questionnaire survey conducted in chemical process industries in Kerala. The collected data out of 1197 surveys is subjected to principal component and confirmatory factor analysis to develop the job stress factor structure. The factor analysis revealed 8 factors that influence the job stress in process industries. It is also found that the job stress in employees is most influenced by role ambiguity and the least by work environment. The study has developed an instrument framework towards measuring job stress utilizing exploratory factor analysis and structural equation modeling.

An Empirical Analysis of Factors Affecting Honors Program Completion Rates

ERIC Educational Resources Information Center

Savage, Hallie; Raehsler, Rod D.; Fiedor, Joseph

2014-01-01

One of the most important issues in any educational environment is identifying factors that promote academic success. A plethora of research on such factors exists across most academic fields, involving a wide range of student demographics, and the definition of student success varies across the range of studies published. The analysis in this…

Factors of Spatial Visualization: An Analysis of the PSVT:R

ERIC Educational Resources Information Center

Ernst, Jeremy V.; Willams, Thomas O.; Clark, Aaron C.; Kelly, Daniel P.

2017-01-01

The Purdue Spatial Visualization Test: Visualization of Rotations (PVST:R) is among the most commonly used measurement instruments to assess spatial ability among engineering students. Previous analysis that explores the factor structure of the PSVT:R indicates a single-factor measure of the instrument. With this as a basis, this research seeks to…

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

PubMed

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

The risk factors for avian influenza on poultry farms: a meta-analysis.

PubMed

Wang, Youming; Li, Peng; Wu, Yangli; Sun, Xiangdong; Yu, Kangzhen; Yu, Chuanhua; Qin, Aijian

2014-11-01

Avian influenza is a severe threat both to humans and poultry, but so far, no systematic review on the identification and evaluation of the risk factors of avian influenza infection has been published. The objective of this meta-analysis is to provide evidence for decision-making and further research on AI prevention through identifying the risk factors associated with AI infection on poultry farms. The results from 15 selected studies on risk factors for AI infections on poultry farms were analyzed quantitatively by meta-analysis. Open water source (OR=2.89), infections on nearby farms (OR=4.54), other livestock (OR=1.90) and disinfection of farm (OR=0.54) have significant association with AI infection on poultry farms. The subgroup analysis results indicate that there exist different risk factors for AI infections in different types of farms. The main risk factors for AI infection in poultry farms are environmental conditions (open water source, infections on nearby farms), keeping other livestock on the same farm and no disinfection of the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

PubMed Central

Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-01-01

Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor

[Introduction to Exploratory Factor Analysis (EFA)].

PubMed

Martínez, Carolina Méndez; Sepúlveda, Martín Alonso Rondón

2012-03-01

Exploratory Factor Analysis (EFA) has become one of the most frequently used statistical techniques, especially in the medical and social sciences. Given its popularity, it is essential to understand the basic concepts necessary for its proper application and to take into consideration the main strengths and weaknesses of this technique. To present in a clear and concise manner the main applications of this technique, to determine the basic requirements for its use providing a description step by step of its methodology, and to establish the elements that must be taken into account during its preparation in order to not incur in erroneous results and interpretations. Narrative review. This review identifies the basic concepts and briefly describes the objectives, design, assumptions, and methodology to achieve factor derivation, global adjustment evaluation, and adequate interpretation of results. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Investigation on Constrained Matrix Factorization for Hyperspectral Image Analysis

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for

Confirmatory Factor Analysis of the Minnesota Nicotine Withdrawal Scale

PubMed Central

Toll, Benjamin A.; O’Malley, Stephanie S.; McKee, Sherry A.; Salovey, Peter; Krishnan-Sarin, Suchitra

2008-01-01

The authors examined the factor structure of the Minnesota Nicotine Withdrawal Scale (MNWS) using confirmatory factor analysis in clinical research samples of smokers trying to quit (n = 723). Three confirmatory factor analytic models, based on previous research, were tested with each of the 3 study samples at multiple points in time. A unidimensional model including all 8 MNWS items was found to be the best explanation of the data. This model produced fair to good internal consistency estimates. Additionally, these data revealed that craving should be included in the total score of the MNWS. Factor scores derived from this single-factor, 8-item model showed that increases in withdrawal were associated with poor smoking outcome for 2 of the clinical studies. Confirmatory factor analyses of change scores showed that the MNWS symptoms cohere as a syndrome over time. Future investigators should report a total score using all of the items from the MNWS. PMID:17563141

Meta-analysis of the Brief Psychiatric Rating Scale Factor Structure

ERIC Educational Resources Information Center

Shafer, Alan

2005-01-01

A meta-analysis (N=17,620; k=26) of factor analyses of the Brief Psychiatric Rating Scale (BPRS) was conducted. Analysis of the 12 items from Overall et al.'s (J. E. Overall, L. E. Hollister, & P. Pichot, 1974) 4 subscales found support for his 4 subscales. Analysis of all 18 BPRS items found 4 components similar to those of Overall et al. In a…

D-Shaped Polarization Maintaining Fiber Sensor for Strain and Temperature Monitoring.

PubMed

Qazi, Hummad Habib; Mohammad, Abu Bakar; Ahmad, Harith; Zulkifli, Mohd Zamani

2016-09-15

A D-shaped polarization-maintaining fiber (PMF) as fiber optic sensor for the simultaneous monitoring of strain and the surrounding temperature is presented. A mechanical end and edge polishing system with aluminum oxide polishing film is utilized to perform sequential polishing on one side (lengthwise) of the PMF in order to fabricate a D-shaped cross-section. Experimental results show that the proposed sensor has high sensitivity of 46 pm/µε and 130 pm/°C for strain and temperature, respectively, which is significantly higher than other recently reported work (mainly from 2013) related to fiber optic sensors. The easy fabrication method, high sensitivity, and good linearity make this sensing device applicable in various applications such as health monitoring and spatial analysis of engineering structures.

Particulate Matter Sources and Composition near a Shrinking Saline Lake (Salton Sea)

NASA Astrophysics Data System (ADS)

Frie, A. L.; Dingle, J. H.; Garrison, A.; Ying, S.; Bahreini, R.

2017-12-01

Dried lake beds (playas) are large dust sources in arid regions, and with increased global water demand many large lakes are shrinking. The Salton Sea is an example of one such lake in the early stages of desiccation, with about 15,000 acres of exposed playa. To quantify the impacts of the shrinking lake on airborne particulate matter(PM) composition, PM samples were collected in August of 2015 and February of 2016 near the Salton Sea, CA. These samples were analyzed for total elemental concentration of 15 elements. For these elements, enrichment factors relative to aluminum were calculated and PMF modeling was applied to deconvolve source factors. From these data, desert-like and playa-like sources were estimated to accounted for 45% and 9% of PM10 mass during these sampling periods. PMF results also revealed that playa sources account for 70% of PM10 Na, evidencing playa-driven PM compositional changes. Additionally, PM Se displayed strong seasonal variation, which is thought to be driven by Se volatilization within Salton Sea sediments, playas, or waters.

A Human Factors Analysis of EVA Time Requirements

NASA Technical Reports Server (NTRS)

Pate, Dennis W.

1997-01-01

Human Factors Engineering (HFE) is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. During the summer of 1995, a human factors motion and time study was initiated with the goals of developing a database of EVA task times and developing a method of utilizing the database to predict how long an EVA should take. Initial development relied on the EVA activities performed during the STS-61 (Hubble) mission. The first step of the study was to become familiar with EVA's, the previous task-time studies, and documents produced on EVA's. After reviewing these documents, an initial set of task primitives and task-time modifiers was developed. Data was collected from videotaped footage of two entire STS-61 EVA missions and portions of several others, each with two EVA astronauts. Feedback from the analysis of the data was used to further refine the primitives and modifiers used. The project was continued during the summer of 1996, during which data on human errors was also collected and analyzed. Additional data from the STS-71 mission was also collected. Analysis of variance techniques for categorical data was used to determine which factors may affect the primitive times and how much of an effect they have. Probability distributions for the various task were also generated. Further analysis of the modifiers and interactions is planned.

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

The mutation profile of JAK2 and CALR in Chinese Han patients with Philadelphia chromosome-negative myeloproliferative neoplasms

PubMed Central

2014-01-01

Mutations in JAK2, MPL and CALR are highly relevant to the Philadelphia chromosome (Ph)-negative myeloproliferative neoplasms (MPNs). We performed high resolution melting analysis and Sanger sequencing together with T-A cloning to elucidate the unique mutation profile of these genes, in Chinese patients with MPNs. Peripheral blood DNA samples were obtained from 80 patients with polycythemia vera (PV), 80 patients with essential thrombocytosis (ET) and 50 patients with primary myelofibrosis (PMF). Ten PV patients were identified with diverse JAK2 exon 12 mutations. Five novel JAK2 Exon 12 mutation patterns (M532V/E543G, N533D, M535I/H538Y/K549I, E543G and D544N) were described. JAK2 V617F was detected in 140 samples (66 PV, 45 ET and 29 PMF). JAK2 Exon 12 mutations were prevalent (13%) and variable in the Chinese patients. Compared with PV patients with JAK2 V617F mutations, PV patients with JAK2 exon 12 mutations had an earlier median onset of disease (P = 0.0013). MPL W515L/K mutations were discerned in 4 ET and 3 PMF patients. Two kinds of CALR mutation, c. 1179_1230del and c. 1234_1235insTTGTC were detected in 20 ET and 16 PMF patients. A novel CALR mutation pattern (c. 1173_1223del/c. 1179_1230del) was identified in 2 PMF samples. In addition, 17 scattered point mutations in CALR c.1153 to c.1255 were also detected in 13 cases with CALR frame-shifting variations and 2 cases without CALR frame-shifting variations. Female patients showed a predisposition to CALR mutations (P = 0.0035). Chinese Ph-negative MPN patients have a unique mutation landscape in the common molecular markers of MPN diagnosis. Validation of the molecular diagnostic pipeline should be emphasized since there is a considerable ethnical diversity in the molecular profiles of Ph-negative MPNs. PMID:25023898

Relationship between Solvation Thermodynamics from IST and DFT Perspectives.

PubMed

Levy, Ronald M; Cui, Di; Zhang, Bin W; Matubayasi, Nobuyuki

2017-04-20

Inhomogeneous solvation theory (IST) and classical density functional theory (DFT) each provide a framework for relating distribution functions of solutions to their thermodynamic properties. As reviewed in this work, both IST and DFT can be formulated in a way that use two "end point" simulations, one of the pure solvent and the other of the solution, to determine the solute chemical potential and other thermodynamic properties of the solution and of subvolumes in regions local to the solute containing hydrating waters. In contrast to IST, where expressions for the excess energy and entropy of solution are the object of analysis, in the DFT end point formulation of the problem, the solute-solvent potential of mean force (PMF) plays a central role. The indirect part of the PMF corresponds to the lowest order (1-body) truncation of the IST expression. Because the PMF is a free energy function, powerful numerical methods can be used to estimate it. We show that the DFT expressions for the solute excess chemical potential can be written in a form which is local, involving integrals only over regions proximate to the solute. The DFT end point route to estimating solvation free energies provides an alternative path to that of IST for analyzing solvation effects on molecular recognition and conformational changes in solution, which can lead to new insights. In order to illustrate the kind of information that is contained in the solute-solvent PMF, we have carried out simulations of β-cyclodextrin in water. This solute is a well studied "host" molecule to which "guest" molecules bind; host-guest systems serve as models for molecular recognition. We illustrate the range of values the direct and indirect parts of the solute-solvent PMF can have as a water molecule is brought to the interface of β-cyclodextrin from the bulk; we discuss the "competition" between these two terms, and the role it plays in molecular recognition.

Quantitative Analysis of Guanine Nucleotide Exchange Factors (GEFs) as Enzymes

PubMed Central

Randazzo, Paul A; Jian, Xiaoying; Chen, Pei-Wen; Zhai, Peng; Soubias, Olivier; Northup, John K

2014-01-01

The proteins that possess guanine nucleotide exchange factor (GEF) activity, which include about ~800 G protein coupled receptors (GPCRs),1 15 Arf GEFs,2 81 Rho GEFs,3 8 Ras GEFs,4 and others for other families of GTPases,5 catalyze the exchange of GTP for GDP on all regulatory guanine nucleotide binding proteins. Despite their importance as catalysts, relatively few exchange factors (we are aware of only eight for ras superfamily members) have been rigorously characterized kinetically.5–13 In some cases, kinetic analysis has been simplistic leading to erroneous conclusions about mechanism (as discussed in a recent review14). In this paper, we compare two approaches for determining the kinetic properties of exchange factors: (i) examining individual equilibria, and; (ii) analyzing the exchange factors as enzymes. Each approach, when thoughtfully used,14,15 provides important mechanistic information about the exchange factors. The analysis as enzymes is described in further detail. With the focus on the production of the biologically relevant guanine nucleotide binding protein complexed with GTP (G•GTP), we believe it is conceptually simpler to connect the kinetic properties to cellular effects. Further, the experiments are often more tractable than those used to analyze the equilibrium system and, therefore, more widely accessible to scientists interested in the function of exchange factors. PMID:25332840

Students' motivation to study dentistry in Malaysia: an analysis using confirmatory factor analysis.

PubMed

Musa, Muhd Firdaus Che; Bernabé, Eduardo; Gallagher, Jennifer E

2015-06-12

Malaysia has experienced a significant expansion of dental schools over the past decade. Research into students' motivation may inform recruitment and retention of the future dental workforce. The objectives of this study were to explore students' motivation to study dentistry and whether that motivation varied by students' and school characteristics. All 530 final-year students in 11 dental schools (6 public and 5 private) in Malaysia were invited to participate at the end of 2013. The self-administered questionnaire, developed at King's College London, collected information on students' motivation to study dentistry and demographic background. Responses on students' motivation were collected using five-point ordinal scales. Confirmatory factor analysis (CFA) was used to evaluate the underlying structure of students' motivation to study dentistry. Multivariate analysis of variance (MANOVA) was used to compare factor scores for overall motivation and sub-domains by students' and school characteristics. Three hundred and fifty-six final-year students in eight schools (all public and two private) participated in the survey, representing an 83% response rate for these schools and 67% of all final-year students nationally. The majority of participants were 24 years old (47%), female (70%), Malay (56%) and from middle-income families (41%) and public schools (78%). CFA supported a model with five first-order factors (professional job, healthcare and people, academic, careers advising and family and friends) which were linked to a single second-order factor representing overall students' motivation. Academic factors and healthcare and people had the highest standardized factor loadings (0.90 and 0.71, respectively), suggesting they were the main motivation to study dentistry. MANOVA showed that students from private schools had higher scores for healthcare and people than those in public schools whereas Malay students had lower scores for family and friends than those

An Analysis of Selected Factors Influencing Enrollment Patterns.

ERIC Educational Resources Information Center

Heck, James

This report presents an analysis of factors influencing enrollment patterns at Lake City Community College (LCCC; Florida) and recommends ways to increase enrollments at the college. Section I reviews the methods of collecting data for the report, which included interviews with key college personnel, an examination of social indicators such as…

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

2011-01-01

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

Tie2 Expressing Monocytes in the Spleen of Patients with Primary Myelofibrosis

PubMed Central

Campanelli, Rita; Fois, Gabriela; Catarsi, Paolo; Poletto, Valentina; Villani, Laura; Erba, Benedetta Gaia; Maddaluno, Luigi; Jemos, Basilio; Salmoiraghi, Silvia; Guglielmelli, Paola; Abbonante, Vittorio; Di Buduo, Christian Andrea; Balduini, Alessandra; Iurlo, Alessandra; Barosi, Giovanni; Rosti, Vittorio; Massa, Margherita

2016-01-01

Primary myelofibrosis (PMF) is a Philadelphia-negative (Ph−) myeloproliferative disorder, showing abnormal CD34+ progenitor cell trafficking, splenomegaly, marrow fibrosis leading to extensive extramedullary haematopoiesis, and abnormal neoangiogenesis in either the bone marrow or the spleen. Monocytes expressing the angiopoietin-2 receptor (Tie2) have been shown to support abnormal angiogenic processes in solid tumors through a paracrine action that takes place in proximity to the vessels. In this study we investigated the frequency of Tie2 expressing monocytes in the spleen tissue samples of patients with PMF, and healthy subjects (CTRLs), and evaluated their possible role in favouring spleen angiogenesis. We show by confocal microscopy that in the spleen tissue of patients with PMF, but not of CTRLs, the most of the CD14+ cells are Tie2+ and are close to vessels; by flow cytometry, we found that Tie2 expressing monocytes were Tie2+CD14lowCD16brightCDL62−CCR2− (TEMs) and their frequency was higher (p = 0.008) in spleen tissue-derived mononuclear cells (MNCs) of patients with PMF than in spleen tissue-derived MNCs from CTRLs undergoing splenectomy for abdominal trauma. By in vitro angiogenesis assay we evidenced that conditioned medium of immunomagnetically selected spleen tissue derived CD14+ cells of patients with PMF induced a denser tube like net than that of CTRLs; in addition, CD14+Tie2+ cells sorted from spleen tissue derived single cell suspension of patients with PMF show a higher expression of genes involved in angiogenesis than that found in CTRLs. Our results document the enrichment of Tie2+ monocytes expressing angiogenic genes in the spleen of patients with PMF, suggesting a role for these cells in starting/maintaining the pathological angiogenesis in this organ. PMID:27281335

Recovery of Weak Factor Loadings When Adding the Mean Structure in Confirmatory Factor Analysis: A Simulation Study

PubMed Central

Ximénez, Carmen

2016-01-01

This article extends previous research on the recovery of weak factor loadings in confirmatory factor analysis (CFA) by exploring the effects of adding the mean structure. This issue has not been examined in previous research. This study is based on the framework of Yung and Bentler (1999) and aims to examine the conditions that affect the recovery of weak factor loadings when the model includes the mean structure, compared to analyzing the covariance structure alone. A simulation study was conducted in which several constraints were defined for one-, two-, and three-factor models. Results show that adding the mean structure improves the recovery of weak factor loadings and reduces the asymptotic variances for the factor loadings, particularly for the models with a smaller number of factors and a small sample size. Therefore, under certain circumstances, modeling the means should be seriously considered for covariance models containing weak factor loadings. PMID:26779071

Differentiation between electron transport sensing and proton motive force sensing by the Aer and Tsr receptors for aerotaxis

PubMed Central

Edwards, Jessica C.; Johnson, Mark S.; Taylor, Barry L.

2007-01-01

SUMMARY Aerotaxis (oxygen-seeking) behavior in Escherichia coli is a response to changes in the electron transport system and not oxygen per se. Because changes in proton motive force (PMF) are coupled to respiratory electron transport, it is difficult to differentiate between PMF, electron transport or redox, all primary candidates for the signal sensed by the aerotaxis receptors, Aer and Tsr. We constructed electron transport mutants that produced different respiratory H+/e- stoichiometries. These strains expressed binary combinations of one NADH dehydrogenase and one quinol oxidase. We then introduced either an aer or tsr mutation into each mutant to create two sets of electron transport mutants. In vivo H+/e- ratios for strains grown in glycerol medium ranged from 1.46 ± 0.18 to 3.04 ± 0.47, but rates of respiration and growth were similar. The PMF jump in response to oxygen was proportional to the H+/e- ratio in each set of mutants (r2 = 0.986 to 0.996). The length of Tsr-mediated aerotaxis responses increased with the PMF jump (r2 = 0.988), but Aer-mediated responses did not correlate with either PMF changes (r2 = 0.297) or the rate of electron transport (r2 = 0.066). Aer-mediated responses were linked to NADH dehydrogenase I, although there was no absolute requirement. The data indicate that Tsr responds to changes in PMF, but strong Aer responses to oxygen are associated with redox changes in NADH dehydrogenase I PMID:16995896

Potential-of-mean-force description of ionic interactions and structural hydration in biomolecular systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hummer, G.; Garcia, A.E.; Soumpasis, D.M.

1994-10-01

To understand the functioning of living organisms on a molecular level, it is crucial to dissect the intricate interplay of the immense number of biological molecules. Most of the biochemical processes in cells occur in a liquid environment formed mainly by water and ions. This solvent environment plays an important role in biological systems. The potential-of-mean-force (PMF) formalism attempts to describe quantitatively the interactions of the solvent with biological macromolecules on the basis of an approximate statistical-mechanical representation. At its current status of development, it deals with ionic effects on the biomolecular structure and with the structural hydration of biomolecules.more » The underlying idea of the PMF formalism is to identify the dominant sources of interactions and incorporate these interactions into the theoretical formalism using PMF`s (or particle correlation functions) extracted from bulk-liquid systems. In the following, the authors shall briefly outline the statistical-mechanical foundation of the PMF formalism and introduce the PMF expansion formalism, which is intimately linked to superposition approximations for higher-order particle correlation functions. The authors shall then sketch applications, which describe the effects of the ionic environment on nucleic-acid structure. Finally, the authors shall present the more recent extension of the PMF idea to describe quantitatively the structural hydration of biomolecules. Results for the interface of ice and water and for the hydration of deoxyribonucleic acid (DNA) will be discussed.« less

Affective Outcomes of Schooling: Full-Information Item Factor Analysis of a Student Questionnaire.

ERIC Educational Resources Information Center

Muraki, Eiji; Engelhard, George, Jr.

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise joint…

Insights into the chemical characterization and sources of PM(2.5) in Beijing at a 1-h time resolution.

PubMed

Gao, Jian; Peng, Xing; Chen, Gang; Xu, Jiao; Shi, Guo-Liang; Zhang, Yue-Chong; Feng, Yin-Chang

2016-01-15

As the widespread application of online instruments penetrates the environmental fields, it is interesting to investigate the sources of fine particulate matter (PM2.5) based on the data monitored by online instruments. In this study, online analyzers with 1-h time resolution were employed to observe PM2.5 composition data, including carbon components, inorganic ions, heavy metals and gas pollutants, during a summer in Beijing. Chemical characteristics, temporal patterns and sources of PM2.5 are discussed. On the basis of hourly data, the mean concentration value of PM2.5 was 62.16±39.37 μg m(-3) (ranging from 6.69 to 183.67 μg m(-3)). The average concentrations of NO3(-), SO4(2-), NH4(+), OC and EC, the major chemical species, were 15.18±13.12, 14.80±14.53, 8.90±9.51, 9.32±4.16 and 3.08±1.43 μg m(-3), respectively. The concentration of PM2.5 varied during the online-sampling period, initially increasing and then subsequently decreasing. Three factor analysis models, including principal component analysis (PCA), positive matrix factorization (PMF) and Multilinear Engine 2 (ME2), were applied to apportion the PM2.5 sources. Source apportionment results obtained by the three different models were in agreement. Four sources were identified in Beijing during the sampling campaign, including secondary sources (38-39%), crustal dust (17-22%), vehicle exhaust (25-28%) and coal combustion (15-16%). Similar source profiles and contributions of PM2.5 were derived from ME2 and PMF, indicating the results of the two models are reasonable. The finding provides information that could be exploited for regular air control strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

MPLW515L mutation in acute megakaryoblastic leukaemia.

PubMed

Hussein, K; Bock, O; Theophile, K; Schulz-Bischof, K; Porwit, A; Schlue, J; Jonigk, D; Kreipe, H

2009-05-01

The thrombopoietin receptor gene (MPL) is expressed in megakaryocytes and exhibits the gain of function point mutation W515K/L in approximately 5% of patients with primary myelofibrosis/idiopathic myelofibrosis (PMF) representing one subtype of the chronic myeloproliferative disorders (myeloproliferative neoplasm). A series of primary and secondary acute myeloid leukaemias (AML) with megakaryoblastic phenotype and myelofibrosis unrelated to PMF (n=12) was analysed for the MPL(W515K/L) mutation by pyrosequencing. In three cases (25%), MPL(W515L) was found and in two of these a combination with trisomy 21 or the Philadelphia chromosome occurred. None of the secondary AML cases evolving from pre-existing PMF showed MPL(W515K/L) (n=4). We conclude that MPL(W515L) occurs in a considerable proportion of acute megakaryoblastic leukaemias with myelofibrosis unrelated to PMF.

A Study of Algorithms for Covariance Structure Analysis with Specific Comparisons Using Factor Analysis.

ERIC Educational Resources Information Center

Lee, S. Y.; Jennrich, R. I.

1979-01-01

A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)

An Analysis of Factors that Influence Enlistment Decisions in the U.S. Army

DTIC Science & Technology

1998-03-01

NAVAL POSTGRADUATE SCHOOL Monterey, California CM THESIS AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY by Young...TITLE AND SUBTITLE : AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY 6. AUTHOR(S) Oh, Young Yeol 7...200 words) The purpose of this thesis is to analyze factors that influence decisions to enlist in the U.S. Army. This thesis uses 1997 New Recruit

Risky Business: Factor Analysis of Survey Data – Assessing the Probability of Incorrect Dimensionalisation

PubMed Central

van der Eijk, Cees; Rose, Jonathan

2015-01-01

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered-categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations. We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of over-dimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems. PMID:25789992