Recirculation, stagnation and ventilation: The 2014 legionella episode

NASA Astrophysics Data System (ADS)

Russo, Ana; Soares, Pedro M. M.; Gouveia, Célia M.; Cardoso, Rita M.; Trigo, Ricardo M.

2017-04-01

Legionella transmission through the atmosphere is unusual, but not unprecedented. A scientific paper published in 2006 reports a surge in Pas-de-Calais, France, in which 86 people have been infected by bacteria released by a cooling tower more than 6 km away [3]. Similarly, in Norway, in 2005, there was another case where contamination spread beyond 10 km, although more concentrated within a radius of 1 km from an industrial unit [2]. An unprecedented large Legionella outbreak occurred in November 2014 nearby Lisbon, Portugal. As of 7 November 2014, 375 individuals become hill and 12 died infected by the Legionella pneumophila bacteria, contracted by inhalation of steam droplets of contaminated water (aerosols). These droplets are so small that can carry the bacteria directly to the lungs, depositing it in the alveoli. One way of studying the propagation of legionella episodes is through the use of aerosol dispersion models. However, such approaches often require detailed 3D high resolution wind data over the region, which isn't often available for long periods. The likely impact of wind on legionella transmission can also be understood based on the analysis of special types of flow conditions such as stagnation, recirculation and ventilation [1, 4]. The Allwine and Whiteman (AW) approach constitutes a straightforward method to assess the assimilative and dispersal capacities of different airsheds [1,4], as it only requires hourly wind components. Thus, it has the advantage of not needing surface and upper air meteorological observations and a previous knowledge of the atmospheric transport and dispersion conditions. The objective of this study is to analyze if the legionella outbreak event which took place in November 2014 had extreme potential recirculation and/or stagnation characteristics. In order to accomplish the proposed objective, the AW approach was applied for a hindcast time-series covering the affected area (1989-2007) and then for an independent

The Universal Anaesthesia Machine (UAM): assessment of a new anaesthesia workstation built with global health in mind.

PubMed

de Beer, D A H; Nesbitt, F D; Bell, G T; Rapuleng, A

2017-04-01

The Universal Anaesthesia Machine has been developed as a complete anaesthesia workstation for use in low- and middle-income countries, where the provision of safe general anaesthesia is often compromised by unreliable supply of electricity and anaesthetic gases. We performed a functional and clinical assessment of this anaesthetic machine, with particular reference to novel features and functioning in the intended environment. The Universal Anaesthesia Machine was found to be reliable, safe and consistent across a range of tests during targeted functional testing. © 2016 The Association of Anaesthetists of Great Britain and Ireland.

EIR: enterprise imaging repository, an alternative imaging archiving and communication system.

PubMed

Bian, Jiang; Topaloglu, Umit; Lane, Cheryl

2009-01-01

The enormous number of studies performed at the Nuclear Medicine Department of University of Arkansas for Medical Sciences (UAMS) generates a huge amount PET/CT images daily. A DICOM workstation had been used as "mini-PACS" to route all studies, which is historically proven to be slow due to various reasons. However, replacing the workstation with a commercial PACS server is not only cost inefficient; and more often, the PACS vendors are reluctant to take responsibility for the final integration of these components. Therefore, in this paper, we propose an alternative imaging archiving and communication system called Enterprise Imaging Repository (EIR). EIR consists of two distinguished components: an image processing daemon and a user friendly web interface. EIR not only reduces the overall waiting time of transferring a study from the modalities to radiologists' workstations, but also provides a more preferable presentation.

The prevalence of fluorosis in children is associated with naturally occurring water fluoride concentration in Mexico.

PubMed

Mariño, Rodrigo

2013-09-01

Fluorosis and dental caries in Mexican schoolchildren residing in areas with different water fluoride concentrations and receiving fluoridated salt. Garcia-Perez A, Irigoyen-Carnacho ME, Borges-Yanez A. Caries Res 2013;47(4):299-308. Rodrigo Mariño Is there an association between the presence of dental fluorosis and fluoride concentration in drinking water? and Is there an association between the severity of fluorosis and dental caries experience in schoolchildren residing in two rural towns in Mexico (with water fluoride concentrations of 0.70 and 1.50 ppm) that also receive fluoridated salt? Government: National Council of Science and Technology (Consejo Nacional de Ciencia y Tecnologia, CONACYT) Other: Autonomous University, Xochimilco (Universidad Autonoma Metropolitana, UAM-X) TYPE OF STUDY/DESIGN: Cross-sectional Level 3: Other evidence Not applicable. Copyright © 2013 Elsevier Inc. All rights reserved.

The MUMBA campaign: measurements of urban, marine and biogenic air

NASA Astrophysics Data System (ADS)

Paton-Walsh, Clare; Guérette, Élise-Andrée; Kubistin, Dagmar; Humphries, Ruhi; Wilson, Stephen R.; Dominick, Doreena; Galbally, Ian; Buchholz, Rebecca; Bhujel, Mahendra; Chambers, Scott; Cheng, Min; Cope, Martin; Davy, Perry; Emmerson, Kathryn; Griffith, David W. T.; Griffiths, Alan; Keywood, Melita; Lawson, Sarah; Molloy, Suzie; Rea, Géraldine; Selleck, Paul; Shi, Xue; Simmons, Jack; Velazco, Voltaire

2017-06-01

The Measurements of Urban, Marine and Biogenic Air (MUMBA) campaign took place in Wollongong, New South Wales (a small coastal city approximately 80 km south of Sydney, Australia) from 21 December 2012 to 15 February 2013. Like many Australian cities, Wollongong is surrounded by dense eucalyptus forest, so the urban airshed is heavily influenced by biogenic emissions. Instruments were deployed during MUMBA to measure the gaseous and aerosol composition of the atmosphere with the aim of providing a detailed characterisation of the complex environment of the ocean-forest-urban interface that could be used to test the skill of atmospheric models. The gases measured included ozone, oxides of nitrogen, carbon monoxide, carbon dioxide, methane and many of the most abundant volatile organic compounds. The aerosol characterisation included total particle counts above 3 nm, total cloud condensation nuclei counts, mass concentration, number concentration size distribution, aerosol chemical analyses and elemental analysis.The campaign captured varied meteorological conditions, including two extreme heat events, providing a potentially valuable test for models of future air quality in a warmer climate. There was also an episode when the site sampled clean marine air for many hours, providing a useful additional measure of the background concentrations of these trace gases within this poorly sampled region of the globe. In this paper we describe the campaign, the meteorology and the resulting observations of atmospheric composition in general terms in order to equip the reader with a sufficient understanding of the Wollongong regional influences to use the MUMBA datasets as a case study for testing a chemical transport model. The data are available from PANGAEA (http://doi.pangaea.de/10.1594/PANGAEA.871982).

Partitioning phase preference for secondary organic aerosol in an urban atmosphere

NASA Astrophysics Data System (ADS)

Chang, Wayne Li-Wen

Secondary organic aerosol (SOA) comprises a significant portion of atmospheric particular matter (PM). The impact of PM on both human health and global climate has long been recognized. Despite its importance, there are still many unanswered questions regarding the formation and evolution of SOA in the atmosphere. This study uses a modeling approach to understand the preferred partitioning behavior of SOA species into aqueous or organic condensed phases. More specifically, this work uses statistical analyses of approximately 24,000 data values for each variable from a state-of-the-art 3-D airshed model. Spatial and temporal distributions of fractions of SOA residing in the aqueous phase (fAQ) in the South Coast Air Basin of California are presented. Typical values of fAQ within the basin near the surface range from 5 to 80%. Results show that the distribution of fAQ values is inversely proportional to the total SOA loading. Further analysis accounting for various meteorological parameters indicates that large fAQ values are the results of aqueous-phase SOA insensitivity to the ambient conditions; while organic-phase SOA concentrations are dramatically reduced under unfavorable SOA formation conditions, aqueous-phase SOA level remains relatively unchanged, thus increasing fAQ at low SOA loading. Diurnal variations of fAQ near the surface are also observed: it tends to be larger during daytime hours than nighttime hours. When examining the vertical gradient of fAQ, largest values are found at heights above the surface layer. In summary, one must consider SOA in both organic and aqueous phases for proper regional and global SOA budget estimation.

Chlorine activation indoors and outdoors via surface-mediated reactions of nitrogen oxides with hydrogen chloride

PubMed Central

Raff, Jonathan D.; Njegic, Bosiljka; Chang, Wayne L.; Gordon, Mark S.; Dabdub, Donald; Gerber, R. Benny; Finlayson-Pitts, Barbara J.

2009-01-01

Gaseous HCl generated from a variety of sources is ubiquitous in both outdoor and indoor air. Oxides of nitrogen (NOy) are also globally distributed, because NO formed in combustion processes is oxidized to NO2, HNO3, N2O5 and a variety of other nitrogen oxides during transport. Deposition of HCl and NOy onto surfaces is commonly regarded as providing permanent removal mechanisms. However, we show here a new surface-mediated coupling of nitrogen oxide and halogen activation cycles in which uptake of gaseous NO2 or N2O5 on solid substrates generates adsorbed intermediates that react with HCl to generate gaseous nitrosyl chloride (ClNO) and nitryl chloride (ClNO2), respectively. These are potentially harmful gases that photolyze to form highly reactive chlorine atoms. The reactions are shown both experimentally and theoretically to be enhanced by water, a surprising result given the availability of competing hydrolysis reaction pathways. Airshed modeling incorporating HCl generated from sea salt shows that in coastal urban regions, this heterogeneous chemistry increases surface-level ozone, a criteria air pollutant, greenhouse gas and source of atmospheric oxidants. In addition, it may contribute to recently measured high levels of ClNO2 in the polluted coastal marine boundary layer. This work also suggests the potential for chlorine atom chemistry to occur indoors where significant concentrations of oxides of nitrogen and HCl coexist. PMID:19620710

Naphthalene distributions and human exposure in Southern California

NASA Astrophysics Data System (ADS)

Lu, Rong; Wu, Jun; Turco, Richard P.; Winer, Arthur M.; Atkinson, Roger; Arey, Janet; Paulson, Suzanne E.; Lurmann, Fred W.; Miguel, Antonio H.; Eiguren-Fernandez, Arantzazu

The regional distribution of, and human exposure to, naphthalene are investigated for Southern California. A comprehensive approach is taken in which advanced models are linked for the first time to quantify population exposure to the emissions of naphthalene throughout Southern California. Naphthalene is the simplest and most abundant of the polycyclic aromatic hydrocarbons found in polluted urban environments, and has been detected in both outdoor and indoor air samples. Exposure to high concentrations of naphthalene may have adverse health effects, possibly causing cancer in humans. Among the significant emission sources are volatilization from naphthalene-containing products, petroleum refining, and combustion of fossil fuels and wood. Gasoline and diesel engine exhaust, with related vaporization from fuels, are found to contribute roughly half of the daily total naphthalene burden in Southern California. As part of this study, the emission inventory for naphthalene has been verified against new field measurements of the naphthalene-to-benzene ratio in a busy traffic tunnel in Los Angeles, supporting the modeling work carried out here. The Surface Meteorology and Ozone Generation (SMOG) airshed model is used to compute the spatial and temporal distributions of naphthalene and its photooxidation products in Southern California. The present simulations reveal a high degree of spatial variability in the concentrations of naphthalene-related species, with large diurnal and seasonal variations as well. Peak naphthalene concentrations are estimated to occur in the early morning hours in the winter season. The naphthalene concentration estimates obtained from the SMOG model are employed in the Regional Human Exposure (REHEX) model to calculate population exposure statistics. Results show average hourly naphthalene exposures in Southern California under summer and winter conditions of 270 and 430 ng m -3, respectively. Exposure to significantly higher concentrations

Medical Simulation as a Vital Adjunct to Identifying Clinical Life-Threatening Gaps in Austere Environments.

PubMed

Chima, Adaora M; Koka, Rahul; Lee, Benjamin; Tran, Tina; Ogbuagu, Onyebuchi U; Nelson-Williams, Howard; Rosen, Michael; Koroma, Michael; Sampson, John B

2018-04-01

Maternal mortality and morbidity are major causes of death in low-resource countries, especially those in Sub-Saharan Africa. Healthcare workforce scarcities present in these locations result in poor perioperative care access and quality. These scarcities also limit the capacity for progressive development and enhancement of workforce training, and skills through continuing medical education. Newly available low-cost, in-situ simulation systems make it possible for a small cadre of trainers to use simulation to identify areas needing improvement and to rehearse best practice approaches, relevant to the context of target environments. Nurse anesthetists were recruited throughout Sierra Leone to participate in simulation-based obstetric anesthesia scenarios at the country's national referral maternity hospital. All subjects participated in a detailed computer assisted training program to familiarize themselves with the Universal Anesthesia Machine (UAM). An expert panel rated the morbidity/mortality risk of pre-identified critical incidents within the scenario via the Delphi process. Participant responses to critical incidents were observed during these scenarios. Participants had an obstetric anesthesia pretest and post-test as well as debrief sessions focused on reviewing the significance of critical incident responses observed during the scenario. 21 nurse anesthetists, (20% of anesthesia providers nationally) participated. Median age was 41 years and median experience practicing anesthesia was 3.5 years. Most participants (57.1%) were female, two-thirds (66.7%) performed obstetrics anesthesia daily but 57.1% had no experience using the UAM. During the simulation, participants were observed and assessed on critical incident responses for case preparation with a median score of 7 out of 13 points, anesthesia management with a median score of 10 out of 20 points and rapid sequence intubation with a median score of 3 out of 10 points. This study identified

Sonochemical synthesis of highly crystalline photocatalyst for industrial applications.

PubMed

Noman, Muhammad Tayyab; Militky, Jiri; Wiener, Jakub; Saskova, Jana; Ashraf, Muhammad Azeem; Jamshaid, Hafsa; Azeem, Musaddaq

2018-02-01

Highly photo active pure anatase form of TiO 2 nanoparticles with average particle size 4nm have been successfully synthesized by ultrasonic acoustic method (UAM). The effects of process variables i.e. precursors concentration and sonication time were investigated based on central composite design and response surface methodology. The characteristics of the resulting nanoparticles (RNP) were analyzed by scanning electron microscopy, dynamic light scattering, transmission electron microscopy, X-ray diffractometry and Raman spectroscopy. Photocatalytic experiments were performed with methylene blue dye which is considered as model organic pollutant in textile industry. A comparative analysis between the RNP and commercially available Degussa P25 for photocatalytic performance against dye removal efficiency was performed. The rapid removal of methylene blue in case of RNP indicates their higher photocatalytic activity than P25. Maximum dye removal efficiency 98.45% was achieved with optimal conditions i.e. TTIP conc. 10mL, EG conc. 4mL and sonication time 1h. Interestingly, no significant difference was found in the photocatalytic performance of RNP after calcination. Moreover, self-cleaning efficiency of RNP deposited on cotton was evaluated in RGB color space. The obtained results indicate the significant impact of ultrasonic irradiations on the photocatalytic performance of pure anatase form than any other hybrid type of TiO 2 nanoparticles. Copyright © 2017 Elsevier B.V. All rights reserved.

Nuclear data uncertainty propagation by the XSUSA method in the HELIOS2 lattice code

NASA Astrophysics Data System (ADS)

Wemple, Charles; Zwermann, Winfried

2017-09-01

Uncertainty quantification has been extensively applied to nuclear criticality analyses for many years and has recently begun to be applied to depletion calculations. However, regulatory bodies worldwide are trending toward requiring such analyses for reactor fuel cycle calculations, which also requires uncertainty propagation for isotopics and nuclear reaction rates. XSUSA is a proven methodology for cross section uncertainty propagation based on random sampling of the nuclear data according to covariance data in multi-group representation; HELIOS2 is a lattice code widely used for commercial and research reactor fuel cycle calculations. This work describes a technique to automatically propagate the nuclear data uncertainties via the XSUSA approach through fuel lattice calculations in HELIOS2. Application of the XSUSA methodology in HELIOS2 presented some unusual challenges because of the highly-processed multi-group cross section data used in commercial lattice codes. Currently, uncertainties based on the SCALE 6.1 covariance data file are being used, but the implementation can be adapted to other covariance data in multi-group structure. Pin-cell and assembly depletion calculations, based on models described in the UAM-LWR Phase I and II benchmarks, are performed and uncertainties in multiplication factor, reaction rates, isotope concentrations, and delayed-neutron data are calculated. With this extension, it will be possible for HELIOS2 users to propagate nuclear data uncertainties directly from the microscopic cross sections to subsequent core simulations.

Evidence of community structure in biomedical research grant collaborations.

PubMed

Nagarajan, Radhakrishnan; Kalinka, Alex T; Hogan, William R

2013-02-01

Recent studies have clearly demonstrated a shift towards collaborative research and team science approaches across a spectrum of disciplines. Such collaborative efforts have also been acknowledged and nurtured by popular extramurally funded programs including the Clinical Translational Science Award (CTSA) conferred by the National Institutes of Health. Since its inception, the number of CTSA awardees has steadily increased to 60 institutes across 30 states. One of the objectives of CTSA is to accelerate translation of research from bench to bedside to community and train a new genre of researchers under the translational research umbrella. Feasibility of such a translation implicitly demands multi-disciplinary collaboration and mentoring. Networks have proven to be convenient abstractions for studying research collaborations. The present study is a part of the CTSA baseline study and investigates existence of possible community-structure in Biomedical Research Grant Collaboration (BRGC) networks across data sets retrieved from the internally developed grants management system, the Automated Research Information Administrator (ARIA) at the University of Arkansas for Medical Sciences (UAMS). Fastgreedy and link-community community-structure detection algorithms were used to investigate the presence of non-overlapping and overlapping community-structure and their variation across years 2006 and 2009. A surrogate testing approach in conjunction with appropriate discriminant statistics, namely: the modularity index and the maximum partition density is proposed to investigate whether the community-structure of the BRGC networks were different from those generated by certain types of random graphs. Non-overlapping as well as overlapping community-structure detection algorithms indicated the presence of community-structure in the BRGC network. Subsequent, surrogate testing revealed that random graph models considered in the present study may not necessarily be appropriate

Community Health Warriors: Marshallese Community Health Workers' Perceptions and Experiences with CBPR and Community Engagement.

PubMed

Purvis, Rachel S; Bing, Williamina Ioanna; Jacob, Christopher J; Lang, Sharlynn; Mamis, Sammie; Ritok, Mandy; Rubon-Chutaro, Jellesen; McElfish, Pearl Anna

2017-01-01

Our manuscript highlights the viewpoints and reflections of the native Marshallese community health workers (CHWs) engaged in research with the local Marshallese community in Northwest Arkansas. In particular, this paper documents the vital role Marshallese CHWs play in the success of programs and research efforts. The negative health effects of nuclear testing in the Marshall Islands has been passed down through many generations, along with unfavorable attitudes toward the U.S. government and researchers. However, the community-based participatory research (CBPR) approach used by the University of Arkansas for Medical Sciences (UAMS) has allowed the native Marshallese CHWs to become advocates for the Marshallese community. The use of native CHWs has also leveled the power dynamics that can be a barrier to community-based research, and has strengthened trust with community stakeholders. Our paper shows how using Marshallese CHWs can produce positive health outcomes for the Marshallese community.

Materials research at CMAM

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

Zucchiatti, Alessandro

2013-07-18

The Centro de Micro Analisis de Materiales (CMAM) is a research centre of the Universidad Autonoma de Madrid dedicated to the modification and analysis of materials using ion beam techniques. The infrastructure, based on a HVEE 5MV tandem accelerator, provided with a coaxial Cockcroft Walton charging system, is fully open to research groups of the UAM, to other public research institutions and to private enterprises. The CMAM research covers a few important lines such as advanced materials, surface science, biomedical materials, cultural heritage, materials for energy production. The Centre gives as well support to university teaching and technical training. Amore » detail description of the research infrastructures and their use statistics will be given. Some of the main research results will be presented to show the progress of research in the Centre in the past few years and to motivate the strategic plans for the forthcoming.« less

GOFC-GOLD/LCLUC/START Regional Networking: building capacity for science and decision-making.

NASA Astrophysics Data System (ADS)

Justice, C. O.; Vadrevu, K.; Gutman, G.

2016-12-01

Over the past 20 years, the international GOFC-GOLD Program and START, with core funding from the NASA LCLUC program and ESA have been developing regional networks of scientists and data users for scientific capacity building and sharing experience in the use and application of Earth Observation data. Regional networks connect scientists from countries with similar environmental and social issues and often with shared water and airsheds. Through periodic regional workshops, regional and national projects are showcased and national priorities and policy drivers are articulated. The workshops encourage both north-south and south-south exchange and collaboration. The workshops are multi-sponsored and each include a training component, targeting early career scientists and data users from the region. The workshops provide an opportunity for regional scientists to publish in peer-reviewed special editions focused on regional issues. Currently, the NASA LCLUC program funded "South and Southeast Asia Regional Initiative (SARI)" team is working closely with the USAID/NASA SERVIR program to implement some capacity building and training activities jointly in south/southeast Asian countries to achieve maximum benefit.

Breathing easier? The known impacts of biodiesel on air quality

PubMed Central

Traviss, Nora

2013-01-01

Substantial scientific evidence exists on the negative health effects of exposure to petroleum diesel exhaust. Many view biodiesel as a ‘green’, more environmentally friendly alternative fuel, especially with respect to measured reductions of particulate matter in tailpipe emissions. Tailpipe emissions data sets from heavy-duty diesel engines comparing diesel and biodiesel fuels provide important information regarding the composition and potential aggregate contribution of particulate matter and other pollutants to regional airsheds. However, exposure – defined in this instance as human contact with tailpipe emissions – is another key link in the chain between emissions and human health effects. Although numerous biodiesel emissions studies exist, biodiesel exposure studies are nearly absent from the literature. This article summarizes the known impacts of biodiesel on air quality and health effects, comparing emissions and exposure research. In light of rapidly changing engine, fuel and exhaust technologies, both emissions and exposure studies are necessary for developing a fuller understanding of the impact of biodiesel on air quality and human health. PMID:23585814

Challenge theme 7: Information support for management of border security and environmental protection: Chapter 9 in United States-Mexican Borderlands: Facing tomorrow's challenges through USGS science

USGS Publications Warehouse

Parcher, Jean W.; Page, William R.

2013-01-01

Historically, international borders were located far from the major political and economic capitals of their countries and rarely received adequate planning or infrastructure development. Today, as a result of global economics and increased movement of goods between nations, border regions play a much greater role in commerce, tourism, and transportation. For example, Mexico is the second largest destination for United States exports (Woodrow Wilson Center Mexico Institute, 2009). The rapid population and economic growth along the United States–Mexican border, undocumented human border crossings, and the unique natural diversity of resources in the Borderlands present challenges for border security and environmental protection. Assessing risks and implementing sustainable growth policies to protect the environment and quality of life greatly increase in complexity when the issues cross an international border, where social services, environmental regulations, lifestyles, and cultural beliefs are unique for each country. Shared airsheds, water and biological resources, national security issues, and disaster management needs require an integrated binational approach to assess risks and develop binational management strategies.

Environmental behavior and fate of methyl tert-butyl ether (MTBE)

USGS Publications Warehouse

Squillace, Paul J.; Pankow, James F.; Korte, Nic E.; Zogorski, John S.

1996-01-01

When gasoline that has been oxygenated with methyl tert-butyl ether (MTBE) comes in contact with water, large amounts of MTBE can dissolve; at 25 degrees Celsius the water solubility of MTBE is about 5,000 milligrams per liter for a gasoline that is 10 percent MTBE by weight. In contrast, for a nonoxygenated gasoline, the total hydrocarbon solubility in water is typically about 120 milligrams per liter. MTBE sorbs only weakly to soil and aquifer materials; therefore, sorption will not significantly retard MTBE's transport by ground water. In addition, MTBE generally resists degradation in ground water. The half-life of MTBE in the atmosphere can be as short as 3 days in a regional airshed. MTBE in the air tends to partition into atmospheric water, including precipitation. However, washout of gas-phase MTBE by precipitation would not, by itself, greatly alter the gas-phase concentration of the compound in the air. The partitioning of MTBE to precipitation is nevertheless strong enough to allow for up to 3 micrograms per liter or more inputs of MTBE to surface and ground water.

Introduction: Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5)

NASA Astrophysics Data System (ADS)

Martin, S. T.; Artaxo, P.; Machado, L. A. T.; Manzi, A. O.; Souza, R. A. F.; Schumacher, C.; Wang, J.; Andreae, M. O.; Barbosa, H. M. J.; Fan, J.; Fisch, G.; Goldstein, A. H.; Guenther, A.; Jimenez, J. L.; Pöschl, U.; Silva Dias, M. A.; Smith, J. N.; Wendisch, M.

2015-11-01

The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment was carried out in the environs of Manaus, Brazil, in the central region of the Amazon basin during two years from 1 January 2014 through 31 December 2015. The experiment focused on the complex interactions among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other. The objective was to understand and quantify these linked processes, first under natural conditions to obtain a baseline and second when altered by the effects of human activities. To this end, the pollution plume from the Manaus metropolis, superimposed on the background conditions of the central Amazon basin, served as a natural laboratory. The present paper, as the Introduction to the GoAmazon2014/5 Special Issue, presents the context and motivation of the GoAmazon2014/5 Experiment. The nine research sites, including the characteristics and instrumentation of each site, are presented. The sites range from time point zero (T0) upwind of the pollution, to T1 in the midst of the pollution, to T2 just downwind of the pollution, to T3 furthest downwind of the pollution (70 km). In addition to the ground sites, a low-altitude G-159 Gulfstream I (G1) observed the atmospheric boundary layer and low clouds, and a high-altitude Gulfstream G550 (HALO) operated in the free troposphere. During the two-year experiment, two Intensive Operating Periods (IOP1 and IOP2) also took place that included additional specialized research instrumentation at the ground sites as well as flights of the two aircraft. GoAmazon2014/5 IOP1 was carried out from 1 February to 31 March 2014 in the wet season. GoAmazon2014/5 IOP2 was conducted from 15 August to 15 October 2014 in the dry season. The G1 aircraft flew during both IOP1 and IOP2, and the HALO aircraft flew during IOP2. In the context of the Amazon basin, the two IOPs also correspond to the clean

Introduction: Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5)

NASA Astrophysics Data System (ADS)

Martin, S. T.; Artaxo, P.; Machado, L. A. T.; Manzi, A. O.; Souza, R. A. F.; Schumacher, C.; Wang, J.; Andreae, M. O.; Barbosa, H. M. J.; Fan, J.; Fisch, G.; Goldstein, A. H.; Guenther, A.; Jimenez, J. L.; Pöschl, U.; Silva Dias, M. A.; Smith, J. N.; Wendisch, M.

2016-04-01

The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment was carried out in the environs of Manaus, Brazil, in the central region of the Amazon basin for 2 years from 1 January 2014 through 31 December 2015. The experiment focused on the complex interactions among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other. The objective was to understand and quantify these linked processes, first under natural conditions to obtain a baseline and second when altered by the effects of human activities. To this end, the pollution plume from the Manaus metropolis, superimposed on the background conditions of the central Amazon basin, served as a natural laboratory. The present paper, as the introduction to the special issue of GoAmazon2014/5, presents the context and motivation of the GoAmazon2014/5 Experiment. The nine research sites, including the characteristics and instrumentation of each site, are presented. The sites range from time point zero (T0) upwind of the pollution, to T1 in the midst of the pollution, to T2 just downwind of the pollution, to T3 furthest downwind of the pollution (70 km). In addition to the ground sites, a low-altitude G-159 Gulfstream I (G-1) observed the atmospheric boundary layer and low clouds, and a high-altitude Gulfstream G550 (HALO) operated in the free troposphere. During the 2-year experiment, two Intensive Operating Periods (IOP1 and IOP2) also took place that included additional specialized research instrumentation at the ground sites as well as flights of the two aircraft. GoAmazon2014/5 IOP1 was carried out from 1 February to 31 March 2014 in the wet season. GoAmazon2014/5 IOP2 was conducted from 15 August to 15 October 2014 in the dry season. The G-1 aircraft flew during both IOP1 and IOP2, and the HALO aircraft flew during IOP2. In the context of the Amazon basin, the two IOPs also correspond to the clean and

Structure and non-structure of centrosomal proteins.

PubMed

Dos Santos, Helena G; Abia, David; Janowski, Robert; Mortuza, Gulnahar; Bertero, Michela G; Boutin, Maïlys; Guarín, Nayibe; Méndez-Giraldez, Raúl; Nuñez, Alfonso; Pedrero, Juan G; Redondo, Pilar; Sanz, María; Speroni, Silvia; Teichert, Florian; Bruix, Marta; Carazo, José M; Gonzalez, Cayetano; Reina, José; Valpuesta, José M; Vernos, Isabelle; Zabala, Juan C; Montoya, Guillermo; Coll, Miquel; Bastolla, Ugo; Serrano, Luis

2013-01-01

Here we perform a large-scale study of the structural properties and the expression of proteins that constitute the human Centrosome. Centrosomal proteins tend to be larger than generic human proteins (control set), since their genes contain in average more exons (20.3 versus 14.6). They are rich in predicted disordered regions, which cover 57% of their length, compared to 39% in the general human proteome. They also contain several regions that are dually predicted to be disordered and coiled-coil at the same time: 55 proteins (15%) contain disordered and coiled-coil fragments that cover more than 20% of their length. Helices prevail over strands in regions homologous to known structures (47% predicted helical residues against 17% predicted as strands), and even more in the whole centrosomal proteome (52% against 7%), while for control human proteins 34.5% of the residues are predicted as helical and 12.8% are predicted as strands. This difference is mainly due to residues predicted as disordered and helical (30% in centrosomal and 9.4% in control proteins), which may correspond to alpha-helix forming molecular recognition features (α-MoRFs). We performed expression assays for 120 full-length centrosomal proteins and 72 domain constructs that we have predicted to be globular. These full-length proteins are often insoluble: Only 39 out of 120 expressed proteins (32%) and 19 out of 72 domains (26%) were soluble. We built or retrieved structural models for 277 out of 361 human proteins whose centrosomal localization has been experimentally verified. We could not find any suitable structural template with more than 20% sequence identity for 84 centrosomal proteins (23%), for which around 74% of the residues are predicted to be disordered or coiled-coils. The three-dimensional models that we built are available at http://ub.cbm.uam.es/centrosome/models/index.php.

Source apportionments of ambient fine particulate matter in Israeli, Jordanian, and Palestinian cities.

PubMed

Heo, Jongbae; Wu, Bo; Abdeen, Ziad; Qasrawi, Radwan; Sarnat, Jeremy A; Sharf, Geula; Shpund, Kobby; Schauer, James J

2017-06-01

This manuscript evaluates spatial and temporal variations of source contributions to ambient fine particulate matter (PM 2.5 ) in Israeli, Jordanian, and Palestinian cities. Twenty-four hour integrated PM 2.5 samples were collected every six days over a 1-year period (January to December 2007) in four cities in Israel (West Jerusalem, Eilat, Tel Aviv, and Haifa), four cities in Jordan (Amman, Aqaba, Rahma, and Zarka), and three cities in Palestine (Nablus, East Jerusalem, and Hebron). The PM 2.5 samples were analyzed for major chemical components, including organic carbon and elemental carbon, ions, and metals, and the results were used in a positive matrix factorization (PMF) model to estimate source contributions to PM 2.5 mass. Nine sources, including secondary sulfate, secondary nitrate, mobile, industrial lead sources, dust, construction dust, biomass burning, fuel oil combustion and sea salt, were identified across the sampling sites. Secondary sulfate was the dominant source, contributing 35% of the total PM 2.5 mass, and it showed relatively homogeneous temporal trends of daily source contribution in the study area. Mobile sources were found to be the second greatest contributor to PM 2.5 mass in the large metropolitan cities, such as Tel Aviv, Hebron, and West and East Jerusalem. Other sources (i.e. industrial lead sources, construction dust, and fuel oil combustion) were closely related to local emissions within individual cities. This study demonstrates how international cooperation can facilitate air pollution studies that address regional air pollution issues and the incremental differences across cities in a common airshed. It also provides a model to study air pollution in regions with limited air quality monitoring capacity that have persistent and emerging air quality problems, such as Africa, South Asia and Central America. Copyright © 2017 Elsevier Ltd. All rights reserved.

The future of airborne sulfur-containing particles in the absence of fossil fuel sulfur dioxide emissions

DOE PAGES

Perraud, Véronique; Horne, Jeremy R.; Martinez, Andrew S.; ...

2015-10-19

Sulfuric acid (H2SO4), formed from oxidation of sulfur dioxide (SO2) emitted during fossil fuel combustion, is a major precursor of new airborne particles, which have well-documented detrimental effects on health, air quality, and climate. Another precursor is methanesulfonic acid (MSA), produced simultaneously with SO2 during the atmospheric oxidation of organosulfur compounds (OSCs), such as dimethyl sulfide. In the present paper, a multidisciplinary approach is used to examine how contributions of H2SO4 and MSA to particle formation will change in a large coastal urban area as anthropogenic fossil fuel emissions of SO2 decline. The 3-dimensional University of California Irvine–California Institute ofmore » Technology airshed model is used to compare atmospheric concentrations of gas phase MSA, H2SO4, and SO2 under current emissions of fossil fuel-associated SO2 and a best-case futuristic scenario with zero fossil fuel sulfur emissions. Model additions include results from (i) quantum chemical calculations that clarify the previously uncertain gas phase mechanism of formation of MSA and (ii) a combination of published and experimental estimates of OSC emissions, such as those from marine, agricultural, and urban processes, which include pet waste and human breath. Results show that in the zero anthropogenic SO2 emissions case, particle formation potential from H2SO4 will drop by about two orders of magnitude compared with the current situation. However, particles will continue to be generated from the oxidation of natural and anthropogenic sources of OSCs, with contributions from MSA and H2SO4 of a similar order of magnitude. Finally, this could be particularly important in agricultural areas where there are significant sources of OSCs.« less

The future of airborne sulfur-containing particles in the absence of fossil fuel sulfur dioxide emissions.

PubMed

Perraud, Véronique; Horne, Jeremy R; Martinez, Andrew S; Kalinowski, Jaroslaw; Meinardi, Simone; Dawson, Matthew L; Wingen, Lisa M; Dabdub, Donald; Blake, Donald R; Gerber, R Benny; Finlayson-Pitts, Barbara J

2015-11-03

Sulfuric acid (H2SO4), formed from oxidation of sulfur dioxide (SO2) emitted during fossil fuel combustion, is a major precursor of new airborne particles, which have well-documented detrimental effects on health, air quality, and climate. Another precursor is methanesulfonic acid (MSA), produced simultaneously with SO2 during the atmospheric oxidation of organosulfur compounds (OSCs), such as dimethyl sulfide. In the present work, a multidisciplinary approach is used to examine how contributions of H2SO4 and MSA to particle formation will change in a large coastal urban area as anthropogenic fossil fuel emissions of SO2 decline. The 3-dimensional University of California Irvine-California Institute of Technology airshed model is used to compare atmospheric concentrations of gas phase MSA, H2SO4, and SO2 under current emissions of fossil fuel-associated SO2 and a best-case futuristic scenario with zero fossil fuel sulfur emissions. Model additions include results from (i) quantum chemical calculations that clarify the previously uncertain gas phase mechanism of formation of MSA and (ii) a combination of published and experimental estimates of OSC emissions, such as those from marine, agricultural, and urban processes, which include pet waste and human breath. Results show that in the zero anthropogenic SO2 emissions case, particle formation potential from H2SO4 will drop by about two orders of magnitude compared with the current situation. However, particles will continue to be generated from the oxidation of natural and anthropogenic sources of OSCs, with contributions from MSA and H2SO4 of a similar order of magnitude. This could be particularly important in agricultural areas where there are significant sources of OSCs.

The future of airborne sulfur-containing particles in the absence of fossil fuel sulfur dioxide emissions

PubMed Central

Perraud, Véronique; Horne, Jeremy R.; Martinez, Andrew S.; Kalinowski, Jaroslaw; Meinardi, Simone; Dawson, Matthew L.; Wingen, Lisa M.; Dabdub, Donald; Blake, Donald R.; Gerber, R. Benny; Finlayson-Pitts, Barbara J.

2015-01-01

Sulfuric acid (H2SO4), formed from oxidation of sulfur dioxide (SO2) emitted during fossil fuel combustion, is a major precursor of new airborne particles, which have well-documented detrimental effects on health, air quality, and climate. Another precursor is methanesulfonic acid (MSA), produced simultaneously with SO2 during the atmospheric oxidation of organosulfur compounds (OSCs), such as dimethyl sulfide. In the present work, a multidisciplinary approach is used to examine how contributions of H2SO4 and MSA to particle formation will change in a large coastal urban area as anthropogenic fossil fuel emissions of SO2 decline. The 3-dimensional University of California Irvine–California Institute of Technology airshed model is used to compare atmospheric concentrations of gas phase MSA, H2SO4, and SO2 under current emissions of fossil fuel-associated SO2 and a best-case futuristic scenario with zero fossil fuel sulfur emissions. Model additions include results from (i) quantum chemical calculations that clarify the previously uncertain gas phase mechanism of formation of MSA and (ii) a combination of published and experimental estimates of OSC emissions, such as those from marine, agricultural, and urban processes, which include pet waste and human breath. Results show that in the zero anthropogenic SO2 emissions case, particle formation potential from H2SO4 will drop by about two orders of magnitude compared with the current situation. However, particles will continue to be generated from the oxidation of natural and anthropogenic sources of OSCs, with contributions from MSA and H2SO4 of a similar order of magnitude. This could be particularly important in agricultural areas where there are significant sources of OSCs. PMID:26483454

The future of airborne sulfur-containing particles in the absence of fossil fuel sulfur dioxide emissions

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

Perraud, Véronique; Horne, Jeremy R.; Martinez, Andrew S.

Sulfuric acid (H2SO4), formed from oxidation of sulfur dioxide (SO2) emitted during fossil fuel combustion, is a major precursor of new airborne particles, which have well-documented detrimental effects on health, air quality, and climate. Another precursor is methanesulfonic acid (MSA), produced simultaneously with SO2 during the atmospheric oxidation of organosulfur compounds (OSCs), such as dimethyl sulfide. In the present paper, a multidisciplinary approach is used to examine how contributions of H2SO4 and MSA to particle formation will change in a large coastal urban area as anthropogenic fossil fuel emissions of SO2 decline. The 3-dimensional University of California Irvine–California Institute ofmore » Technology airshed model is used to compare atmospheric concentrations of gas phase MSA, H2SO4, and SO2 under current emissions of fossil fuel-associated SO2 and a best-case futuristic scenario with zero fossil fuel sulfur emissions. Model additions include results from (i) quantum chemical calculations that clarify the previously uncertain gas phase mechanism of formation of MSA and (ii) a combination of published and experimental estimates of OSC emissions, such as those from marine, agricultural, and urban processes, which include pet waste and human breath. Results show that in the zero anthropogenic SO2 emissions case, particle formation potential from H2SO4 will drop by about two orders of magnitude compared with the current situation. However, particles will continue to be generated from the oxidation of natural and anthropogenic sources of OSCs, with contributions from MSA and H2SO4 of a similar order of magnitude. Finally, this could be particularly important in agricultural areas where there are significant sources of OSCs.« less

[Non-neoplastic enlargement of salivary glands: clinico-histologic analysis].

PubMed

González Guevara, Martha Beatriz; Torres Tejero, Marco Antonio; Martínez Mata, Guillermo

2005-01-01

We carried out a retrospective study on non-neoplastic enlargement of the salivary glands at the Oral Histopathology Diagnostic Center of the Autonomous Metropolitan University at Xochimilco (UAM-Xochimilco) in Mexico during a period of 24 years (1979-2003). From 5,625 biopsies received and analyzed, a total of 461 (8.2%) were non-neoplastic enlargement of the salivary glands; for each case, we registered demographic data as well as clinic characteristics. These lesions were characterized as a heterogeneous group of pathologic entities among which we included local, obstructive, infectious, and immunopathologic lesions. The most frequent lesion was the extravasation cyst in 341 (74%) cases, followed by chronic sialoadenitis and Sjögren's syndrome with 54 (11.7%) and 41 (8.8%) cases, respectively, and at a lesser percentage mucous retention cyst, sialosis, benign lymphoepithelial lesions and those related with sialolytes. Females were affected more frequently; mean age was second to third life decades. These lesions were most frequently localized on inferior labial mucosa.

OncoSimulR: genetic simulation with arbitrary epistasis and mutator genes in asexual populations.

PubMed

Diaz-Uriarte, Ramon

2017-06-15

OncoSimulR implements forward-time genetic simulations of biallelic loci in asexual populations with special focus on cancer progression. Fitness can be defined as an arbitrary function of genetic interactions between multiple genes or modules of genes, including epistasis, restrictions in the order of accumulation of mutations, and order effects. Mutation rates can differ among genes, and can be affected by (anti)mutator genes. Also available are sampling from simulations (including single-cell sampling), plotting the genealogical relationships of clones and generating and plotting fitness landscapes. Implemented in R and C ++, freely available from BioConductor for Linux, Mac and Windows under the GNU GPL license. Version 2.5.9 or higher available from: http://www.bioconductor.org/packages/devel/bioc/html/OncoSimulR.html . GitHub repository at: https://github.com/rdiaz02/OncoSimul. ramon.diaz@iib.uam.es. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Investigating the Potential Barrier Function of Nanostructured Materials Formed in Engineered Barrier Systems (EBS) Designed for Nuclear Waste Isolation.

PubMed

Cuevas, Jaime; Ruiz, Ana Isabel; Fernández, Raúl

2018-02-21

Clay and cement are known nano-colloids originating from natural processes or traditional materials technology. Currently, they are used together as part of the engineered barrier system (EBS) to isolate high-level nuclear waste (HLW) metallic containers in deep geological repositories (DGR). The EBS should prevent radionuclide (RN) migration into the biosphere until the canisters fail, which is not expected for approximately 10 3  years. The interactions of cementitious materials with bentonite swelling clay have been the scope of our research team at the Autonomous University of Madrid (UAM) with participation in several European Union (EU) projects from 1998 up to now. Here, we describe the mineral and chemical nature and microstructure of the alteration rim generated by the contact between concrete and bentonite. Its ability to buffer the surrounding chemical environment may have potential for further protection against RN migration. © 2018 The Chemical Society of Japan & Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Coupling meteorology, metal concentrations, and Pb isotopes for source attribution in archived precipitation samples.

PubMed

Graney, Joseph R; Landis, Matthew S

2013-03-15

A technique that couples lead (Pb) isotopes and multi-element concentrations with meteorological analysis was used to assess source contributions to precipitation samples at the Bondville, Illinois USA National Trends Network (NTN) site. Precipitation samples collected over a 16month period (July 1994-October 1995) at Bondville were parsed into six unique meteorological flow regimes using a minimum variance clustering technique on back trajectory endpoints. Pb isotope ratios and multi-element concentrations were measured using high resolution inductively coupled plasma-sector field mass spectrometry (ICP-SFMS) on the archived precipitation samples. Bondville is located in central Illinois, ~250km downwind from smelters in southeast Missouri. The Mississippi Valley Type ore deposits in Missouri provided a unique multi-element and Pb isotope fingerprint for smelter emissions which could be contrasted to industrial emissions from the Chicago and Indianapolis urban areas (~125km north and east, of Bondville respectively) and regional emissions from electric utility facilities. Differences in Pb isotopes and element concentrations in precipitation corresponded to flow regime. Industrial sources from urban areas, and thorogenic Pb from coal use, could be differentiated from smelter emissions from Missouri by coupling Pb isotopes with variations in element ratios and relative mass factors. Using a three endmember mixing model based on Pb isotope ratio differences, industrial processes in urban airsheds contributed 56±19%, smelters in southeast Missouri 26±13%, and coal combustion 18±7%, of the Pb in precipitation collected in Bondville in the mid-1990s. Copyright © 2012 Elsevier B.V. All rights reserved.

The influence of scales of atmospheric motion on air pollution over Portugal

NASA Astrophysics Data System (ADS)

Russo, Ana; Trigo, Ricardo; Mendes, Manuel; Jerez, Sonia; Gouveia, Célia Marina

2014-05-01

Air pollution is determined by the combination of different factors, namely, emissions, physical constrains, meteorology and chemical processes [1,2,3]. The relative importance of such factors is influenced by their interaction on diverse scales of atmospheric motion. Each scale depicts different meteorological conditions, which, when combined with the different air pollution sources and photochemistry, result in varying ambient concentrations [2]. Identifying the dominant scales of atmospheric motion over a given airshed can be of great importance for many applications such as air pollution and pollen dispersion or wind energy management [2]. Portugal has been affected by numerous air pollution episodes during the last decade. These episodes are often related to peak emissions from local industry or transport, but can also be associated to regional transport from other urban areas or to exceptional emission events, such as forest fires. This research aims to identify the scales of atmospheric motion which contribute to an increase of air pollution. A method is proposed for differentiating between the scales of atmospheric motion that can be applied on a daily basis from data collected at several wind-measuring sites in a given airshed and to reanalysis datasets. The method is based on the daily mean wind recirculation and the mean and standard deviation between sites. The determination of the thresholds between scales is performed empirically following the approach of Levy et al. [2] and also through a automatic statistical approach computed taking into account the tails of the distributions (e.g. 95% and 99% percentile) of the different wind samples. A comparison is made with two objective approaches: 1) daily synoptic classification for the same period over the region [4] and 2) a 3-D backward trajectory approach [5,6] for specific episodes. Furthermore, the outcomes are expected to support the Portuguese authorities on the implementation of strategies for a

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

Receptor modeling was performed on quadrupole unit mass resolution aerosol mass spectrometer (Q-AMS) sub-micron particulate matter (PM) chemical speciation measurements from Windsor, Ontario, an industrial city situated across the Detroit River from Detroit, Michigan. Aerosol and trace gas measurements were collected on board Environment Canada's Canadian Regional and Urban Investigation System for Environmental Research (CRUISER) mobile laboratory. Positive matrix factorization (PMF) was performed on the AMS full particle-phase mass spectrum (PMFFull MS) encompassing both organic and inorganic components. This approach compared to the more common method of analyzing only the organic mass spectra (PMFOrg MS). PMF of the full mass spectrum revealed that variability in the non-refractory sub-micron aerosol concentration and composition was best explained by six factors: an amine-containing factor (Amine); an ammonium sulfate- and oxygenated organic aerosol-containing factor (Sulfate-OA); an ammonium nitrate- and oxygenated organic aerosol-containing factor (Nitrate-OA); an ammonium chloride-containing factor (Chloride); a hydrocarbon-like organic aerosol (HOA) factor; and a moderately oxygenated organic aerosol factor (OOA). PMF of the organic mass spectrum revealed three factors of similar composition to some of those revealed through PMFFull MS: Amine, HOA and OOA. Including both the inorganic and organic mass proved to be a beneficial approach to analyzing the unit mass resolution AMS data for several reasons. First, it provided a method for potentially calculating more accurate sub-micron PM mass concentrations, particularly when unusual factors are present, in this case the Amine factor. As this method does not rely on a priori knowledge of chemical species, it circumvents the need for any adjustments to the traditional AMS species fragmentation patterns to account for atypical species, and can thus lead to more complete factor profiles. It is expected that this

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

Receptor modelling was performed on quadrupole unit mass resolution aerosol mass spectrometer (Q-AMS) sub-micron particulate matter (PM) chemical speciation measurements from Windsor, Ontario, an industrial city situated across the Detroit River from Detroit, Michigan. Aerosol and trace gas measurements were collected on board Environment Canada's CRUISER mobile laboratory. Positive matrix factorization (PMF) was performed on the AMS full particle-phase mass spectrum (PMFFull MS) encompassing both organic and inorganic components. This approach was compared to the more common method of analysing only the organic mass spectra (PMFOrg MS). PMF of the full mass spectrum revealed that variability in the non-refractory sub-micron aerosol concentration and composition was best explained by six factors: an amine-containing factor (Amine); an ammonium sulphate and oxygenated organic aerosol containing factor (Sulphate-OA); an ammonium nitrate and oxygenated organic aerosol containing factor (Nitrate-OA); an ammonium chloride containing factor (Chloride); a hydrocarbon-like organic aerosol (HOA) factor; and a moderately oxygenated organic aerosol factor (OOA). PMF of the organic mass spectrum revealed three factors of similar composition to some of those revealed through PMFFull MS: Amine, HOA and OOA. Including both the inorganic and organic mass proved to be a beneficial approach to analysing the unit mass resolution AMS data for several reasons. First, it provided a method for potentially calculating more accurate sub-micron PM mass concentrations, particularly when unusual factors are present, in this case, an Amine factor. As this method does not rely on a priori knowledge of chemical species, it circumvents the need for any adjustments to the traditional AMS species fragmentation patterns to account for atypical species, and can thus lead to more complete factor profiles. It is expected that this method would be even more useful for HR-ToF-AMS data, due to the ability

Introduction: Observations and modeling of the Green Ocean Amazon (GoAmazon2014/5)

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

Martin, S. T.; Artaxo, P.; Machado, L. A. T.

The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment was carried out in the environs of Manaus, Brazil, in the central region of the Amazon basin for 2 years from 1 January 2014 through 31 December 2015. The experiment focused on the complex interactions among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other. The objective was to understand and quantify these linked processes, first under natural conditions to obtain a baseline and second when altered by the effects of human activities. To this end, the pollution plume from themore » Manaus metropolis, superimposed on the background conditions of the central Amazon basin, served as a natural laboratory. The present paper, as the introduction to the special issue of GoAmazon2014/5, presents the context and motivation of the GoAmazon2014/5 Experiment. The nine research sites, including the characteristics and instrumentation of each site, are presented. The sites range from time point zero (T0) upwind of the pollution, to T1 in the midst of the pollution, to T2 just downwind of the pollution, to T3 furthest downwind of the pollution (70 km). In addition to the ground sites, a low-altitude G-159 Gulfstream I (G-1) observed the atmospheric boundary layer and low clouds, and a high-altitude Gulfstream G550 (HALO) operated in the free troposphere. During the 2-year experiment, two Intensive Operating Periods (IOP1 and IOP2) also took place that included additional specialized research instrumentation at the ground sites as well as flights of the two aircraft. GoAmazon2014/5 IOP1 was carried out from 1 February to 31 March 2014 in the wet season. GoAmazon2014/5 IOP2 was conducted from 15 August to 15 October 2014 in the dry season. In addition, the G-1 aircraft flew during both IOP1 and IOP2, and the HALO aircraft flew during IOP2. In the context of the Amazon basin, the two IOPs

Introduction: Observations and modeling of the Green Ocean Amazon (GoAmazon2014/5)

DOE PAGES

Martin, S. T.; Artaxo, P.; Machado, L. A. T.; ...

2016-04-19

The Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) Experiment was carried out in the environs of Manaus, Brazil, in the central region of the Amazon basin for 2 years from 1 January 2014 through 31 December 2015. The experiment focused on the complex interactions among vegetation, atmospheric chemistry, and aerosol production on the one hand and their connections to aerosols, clouds, and precipitation on the other. The objective was to understand and quantify these linked processes, first under natural conditions to obtain a baseline and second when altered by the effects of human activities. To this end, the pollution plume from themore » Manaus metropolis, superimposed on the background conditions of the central Amazon basin, served as a natural laboratory. The present paper, as the introduction to the special issue of GoAmazon2014/5, presents the context and motivation of the GoAmazon2014/5 Experiment. The nine research sites, including the characteristics and instrumentation of each site, are presented. The sites range from time point zero (T0) upwind of the pollution, to T1 in the midst of the pollution, to T2 just downwind of the pollution, to T3 furthest downwind of the pollution (70 km). In addition to the ground sites, a low-altitude G-159 Gulfstream I (G-1) observed the atmospheric boundary layer and low clouds, and a high-altitude Gulfstream G550 (HALO) operated in the free troposphere. During the 2-year experiment, two Intensive Operating Periods (IOP1 and IOP2) also took place that included additional specialized research instrumentation at the ground sites as well as flights of the two aircraft. GoAmazon2014/5 IOP1 was carried out from 1 February to 31 March 2014 in the wet season. GoAmazon2014/5 IOP2 was conducted from 15 August to 15 October 2014 in the dry season. In addition, the G-1 aircraft flew during both IOP1 and IOP2, and the HALO aircraft flew during IOP2. In the context of the Amazon basin, the two IOPs

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

Simoneit, B.R.T.; Radzi bin Abas, M.; Cass, G.R.

Biomass combustion is an important primary source of carbonaceous particles in the global atmosphere. Various molecular markers have been proposed for this process but additional specific tracers are needed. The injection of natural product organic compounds into smoke occurs primarily by direct volatilization/steam stripping and by pyrolysis. Although the composition of organic matter in smoke particles is highly variable, the molecular structures of the tracers are generally source specific. Homologous compounds and biomarkers present in smoke are derived directly from plant wax, gum and resin by volatilization and secondarily from pyrolysis of biopolymers (e.g., lignin, cutin, suberin), wax, gum andmore » resin. The component complexity is illustrated with examples from controlled bums of temperate and tropical biomass fuels. Conifer smoke contains characteristic tracers from diterpenoids as well as phenolics and other oxygenated species. These are recognizable in urban airsheds. The major organic components of smoke from tropical biomass are straight-chain, aliphatic and oxygenated compounds and triterpenoids. Several compounds are potential key indicators for combustion of such biomass. The precursor to product approach of organic geochemistry can be applied successfully to provide molecular tracers for studying smoke plume chemistry and dispersion.« less

Dynamic behavior of semivolatile organic compounds in indoor air

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

Loy, Michael David Van

1998-12-09

Exposures to a wide range of air pollutants are often dominated by those occurring in buildings because of three factors: 1) most people spend a large fraction of their time indoors, 2) many pollutants have strong indoor sources, and 3) the dilution volume in buildings is generally several orders of magnitude smaller than that of an urban airshed. Semivolatile organic compounds (SVOCS) are emitted by numerous indoor sources, including tobacco combustion, cooking, carpets, paints, resins, and glues, so indoor gasphase concentrations of these compounds are likely to be elevated relative to ambient levels. The rates of uptake and release ofmore » reversibly sorbing SVOCS by indoor materials directly affect both peak concentrations and persistence of the pollutants indoors after source elimination. Thus, accurate predictions of SVOC dynamics in indoor air require an understanding of contaminant sorption on surface materials such as carpet and wallboard. The dynamic behaviors of gas-phase nicotine and phenanthrene were investigated in a 20 ms stainless steel chamber containing carpet and painted wallboard. Each compound was studied independently, first in the empty chamber, then with each sorbent individually, and finally with both sorbents in the chamber.« less

The University of Utah Urban Undertaking (U4)

NASA Astrophysics Data System (ADS)

Lin, J. C.; Mitchell, L.; Bares, R.; Mendoza, D. L.; Fasoli, B.; Bowling, D. R.; Garcia, M. A.; Buchert, M.; Pataki, D. E.; Crosman, E.; Horel, J.; Catharine, D.; Strong, C.; Ehleringer, J. R.

2015-12-01

The University of Utah is leading efforts to understand the spatiotemporal patterns in both emissions and concentrations of greenhouse gases (GHG) and criteria pollutants within urban systems. The urbanized corridor in northern Utah along the Wasatch Front, anchored by Salt Lake City, is undergoing rapid population growth that is projected to double in the next few decades. The Wasatch Front offers multiple advantages as an unique "urban laboratory": urban regions in multiple valleys spanning numerous orders of magnitude in population, each with unique airsheds, well-defined boundary conditions along deserts and tall mountains, strong signals during cold air pool events, seasonal contrasts in pollution, and a legacy of productive partnerships with local stakeholders and governments. We will show results from GHG measurements from the Wasatch Front, including one of the longest running continuous CO2 records in urban areas. Complementing this record are comprehensive meteorological observations and GHG/pollutant concentrations on mobile platforms: light rail, helicopter, and research vans. Variations in the GHG and pollutant observations illustrate human behavior and the resulting "urban metabolism" taking place on hourly, weekly, and seasonal cycles, resulting in a coupling between GHG and criteria pollutants. Moreover, these observations illustrate systematic spatial gradients in GHG and pollutant distributions between and within urban areas, traced to underlying gradients in population, energy use, terrain, and land use. Over decadal time scales the observations reveal growth of the "urban dome" due to expanding urban development. Using numerical models of the atmosphere, we further link concentrations of GHG and air quality-relevant pollutants to underlying emissions at the neighborhood scale as well as urban planning considerations.

Characterization of metals emitted from motor vehicles.

PubMed

Schauer, James J; Lough, Glynis C; Shafer, Martin M; Christensen, William F; Arndt, Michael F; DeMinter, Jeffrey T; Park, June-Soo

2006-03-01

A systematic approach was used to quantify the metals present in particulate matter emissions associated with on-road motor vehicles. Consistent sampling and chemical analysis techniques were used to determine the chemical composition of particulate matter less than 10 microm in aerodynamic diameter (PM10*) and particulate matter less than 2.5 microm in aerodynamic diameter (PM2.5), including analysis of trace metals by inductively coupled plasma mass spectrometry (ICP-MS). Four sources of metals were analyzed in emissions associated with motor vehicles: tailpipe emissions from gasoline- and diesel-powered vehicles, brake wear, tire wear, and resuspended road dust. Profiles for these sources were used in a chemical mass balance (CMB) model to quantify their relative contributions to the metal emissions measured in roadway tunnel tests in Milwaukee, Wisconsin. Roadway tunnel measurements were supplemented by parallel measurements of atmospheric particulate matter and associated metals at three urban locations: Milwaukee and Waukesha, Wisconsin, and Denver, Colorado. Ambient aerosol samples were collected every sixth day for one year and analyzed by the same chemical analysis techniques used for the source samples. The two Wisconsin sites were studied to assess the spatial differences, within one urban airshed, of trace metals present in atmospheric particulate matter. The measurements were evaluated to help understand source and seasonal trends in atmospheric concentrations of trace metals. ICP-MS methods have not been widely used in analyses of ambient aerosols for metals despite demonstrated advantages over traditional techniques. In a preliminary study, ICP-MS techniques were used to assess the leachability of trace metals present in atmospheric particulate matter samples and motor vehicle source samples in a synthetic lung fluid.

Towards a Consistent and Scientifically Accurate Drug Ontology.

PubMed

Hogan, William R; Hanna, Josh; Joseph, Eric; Brochhausen, Mathias

2013-01-01

Our use case for comparative effectiveness research requires an ontology of drugs that enables querying National Drug Codes (NDCs) by active ingredient, mechanism of action, physiological effect, and therapeutic class of the drug products they represent. We conducted an ontological analysis of drugs from the realist perspective, and evaluated existing drug terminology, ontology, and database artifacts from (1) the technical perspective, (2) the perspective of pharmacology and medical science (3) the perspective of description logic semantics (if they were available in Web Ontology Language or OWL), and (4) the perspective of our realism-based analysis of the domain. No existing resource was sufficient. Therefore, we built the Drug Ontology (DrOn) in OWL, which we populated with NDCs and other classes from RxNorm using only content created by the National Library of Medicine. We also built an application that uses DrOn to query for NDCs as outlined above, available at: http://ingarden.uams.edu/ingredients. The application uses an OWL-based description logic reasoner to execute end-user queries. DrOn is available at http://code.google.com/p/dr-on.

Expression of an alkane monooxygenase (alkB) gene and methyl tert-butyl ether co-metabolic oxidation in Pseudomonas citronellolis.

PubMed

Bravo, Ana Luisa; Sigala, Juan Carlos; Le Borgne, Sylvie; Morales, Marcia

2015-04-01

Pseudomonas citronellolis UAM-Ps1 co-metabolically transforms methyl tert-butyl ether (MTBE) to tert-butyl alcohol with n-pentane (2.6 mM), n-octane (1.5 mM) or dicyclopropylketone (DCPK) (4.4 mM), a gratuitous inducer of alkane hydroxylase (AlkB) activity. The reverse transcription quantitative real-time PCR was used to quantify the alkane monooxygenase (alkB) gene expression. The alkB gene was expressed in the presence of n-alkanes and DCPK and MTBE oxidation occurred only in cultures when alkB was transcribed. A correlation between the number of alkB transcripts and MTBE consumption was found (ΜΤΒΕ consumption in μmol = 1.44e(-13) x DNA copies, R(2) = 0.99) when MTBE (0.84 mM) was added. Furthermore, alkB was cloned and expressed into Escherichia coli and the recombinant AlkB had a molecular weight of 42 kDa. This is the first report where the expression of alkB is related to the co-metabolic oxidation of MTBE.

Acoustical phenomenon in ancient Totonac's monument

NASA Astrophysics Data System (ADS)

Sánchez-Dehesa, José; Ha˚Kansson, Andreas; Cervera, Francisco; Meseguer, Francisco; Manzanares-Martínez, Betsabé; Ramos-Mendieta, Felipe

2004-05-01

The circle of gladiators is a monument built by Totonac Indians in the ceremonial site of Cempoala, which is located near Veracruz (Mexico). The city is believed to date to around 1200 A.D. The monument is a round structure with crenellated wall tops, and it has a diameter of 13.4 m. Though the deterioration of this monument is noticeable, it presents a singular acoustical phenomenon whose strength had to be probably extraordinary on the date of its construction. In brief, along any diameter in the circle, one can find two focal points such that if one person speaks on one focus, another person located on the other hears the sound reinforced. In other words, this circular place acoustically behaves as if it were elliptical. Here, we report the experimental characterization of the phenomenon and present a theoretical explanation. Also, the intentionality of the Totonacs is speculated since these people are associated with the Mayan culture, which is known by its realizations of environments with astonishing sonic properties. [Work supported by CEAL-UAM of Spain.

Ultrasound assisted microextraction-nano material solid phase dispersion for extraction and determination of thymol and carvacrol in pharmaceutical samples: experimental design methodology.

PubMed

Roosta, Mostafa; Ghaedi, Mehrorang; Daneshfar, Ali; Sahraei, Reza

2015-01-15

In the present study, for the first time, a new extraction method based on "ultrasound assisted microextraction-nanomaterial solid phase dispersion (UAME-NMSPD)" was developed to preconcentrate the low quantity of thymol and carvacrol in pharmaceutical samples prior to their HPLC-UV separation/determination. The analytes were accumulated on nickel sulfide nanomaterial loaded on activated carbon (NiS-NP-AC) that with more detail identified by XRD, FESEM and UV-vis technique. Central composite design (CCD) combined with desirability function (DF) was used to search for optimum operational conditions. Working under optimum conditions specified as: 10 min ultrasonic time, pH 3, 0.011 g of adsorbent and 600 μL extraction solvent) permit achievement of high and reasonable linear range over 0.005-2.0 μg mL(-1) (r(2)>0.9993) with LOD of thymol and carvacrol as 0.23 and 0.21 μg L(-1), respectively. The relative standard deviations (RSDs) were less than 4.93% (n=3). Copyright © 2014 Elsevier B.V. All rights reserved.

Featured Image: Stars from Broken Clouds and Disks

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2018-04-01

This still from a simulation captures binary star formation in action. Researchers have long speculated on the processes that lead to clouds of gas and dust breaking up into smaller pieces to form multiple-star systems but these take place over a large range of scales, making them difficult to simulate. In a new study led by Leonardo Sigalotti (UAM Azcapotzalco, Mexico), researchers have used a smoothed-particle hydrodynamics code to model binary star formation on scales of thousands of AU down to scales as small as 0.1 AU. In the scene shown above, a collapsing cloud of gas and dust has recently fragmented into two pieces, forming a pair of disks separated by around 200 AU. In addition, we can see that smaller-scale fragmentation is just starting in one of these disks, Disk B. Here, one of the disks spiral arms has become unstable and is beginning to condense; it will eventually form another star, producing a hierarchical system: a close binary within the larger-scale binary. Check out the broaderprocessin the four panels below (which show the system as it evolves over time), or visitthe paper linked below for more information about what the authors learned.Evolution of a collapsed cloud after large-scale fragmentation into a binary protostar: (a) 44.14 kyr, (b) 44.39 kyr, (c) 44.43 kyr, and (d) 44.68 kyr. The insets show magnifications of the binary cores. [Adapted from Sigalotti et al. 2018]CitationLeonardo Di G. Sigalotti et al 2018 ApJ 857 40. doi:10.3847/1538-4357/aab619

Interactions between reactive nitrogen and the Canadian landscape: A budget approach

NASA Astrophysics Data System (ADS)

Clair, Thomas A.; Pelletier, Nathan; Bittman, Shabtai; Leip, Adrian; Arp, Paul; Moran, Michael D.; Dennis, Ian; Niemi, David; Sterling, Shannon; Drury, Craig F.; Yang, Jingyi

2014-11-01

The movement of excess reactive nitrogen (Nr) from anthropogenic activities to natural ecosystems has been described as one of the most serious environmental threats facing modern society. One of the approaches for tracking this movement is the use of budgets that quantify fluxes. We constructed an Nr budget for Canada using measured and modeled values from the scientific literature, government databases, and data from new agri-environmental indicators, in order to produce information for policy makers and scientists to understand the major flows of nitrogen to allow a better assessment of risks to the Canadian environment. We divided the Canadian territory south of 60°N into areas dominated by natural ecosystems, as well as by agricultural and urban/industrial activities to evaluate Nr flows within, between, and out of these units. We show that Canada is a major exporter of Nr due to the availability of inexpensive commercial fertilizers. The large land area suitable for agriculture makes Canada a significant agricultural Nr exporter of both grain crops and livestock. Finally, Canada exports petroleum N mainly to the United States. Because of its location and prevailing atmospheric transport patterns, Canada is a net receptor of Nr air pollution from the United States, receiving approximately 20% of the Nr leaving the U.S. airshed. We found that overall, terrestrial natural ecosystems as well as the atmosphere are in balance between Nr inputs and outputs when all N reactive and nonreactive fluxes are included. However, when only reactive forms are considered, almost 50% of N entering the Canadian atmosphere cannot be accounted for and is assumed to be lost to the Atlantic and Arctic oceans or to unmeasured dry deposition. However, agricultural and freshwater landscapes are showing large differences between measured inputs and outputs of N as our data suggest that denitrification in soils and aquatic systems is larger than what models predict. Our work also shows

Quantification of hourly variability in NO(x) emissions for baseload coal-fired power plants.

PubMed

Abdel-Aziz, Amr; Frey, H Christopher

2003-11-01

The objectives of this paper are to (1) quantify variability in hourly utility oxides of nitrogen (NO(x)) emission factors, activity factors, and total emissions; (2) investigate the autocorrelation structure and evaluate cyclic effects at short and long scales of the time series of total hourly emissions; (3) compare emissions for the ozone (O3) season versus the entire year to identify seasonal differences, if any; and (4) evaluate interannual variability. Continuous emissions monitoring data were analyzed for 1995 and 1998 for 32 units from nine baseload power plants in the Charlotte, NC, airshed. Unit emissions have a strong 24-hr cycle attributable primarily to the capacity factor. Typical ranges of the coefficient of variation for emissions at a given hour of the day were from 0.2 to 0.45. Little difference was found when comparing weekend emissions with the entire week or when comparing the O3 season with the entire year. There were substantial differences in the mean and standard deviation of emissions when comparing 1995 and 1998 data, indicative of the effect of retrofits of control technology during the intervening time. The wide range of variability and its autocorrelation should be accounted for when developing probabilistic utility emission inventories for analysis of near-term future episodes.

Heavy haze in winter Beijing driven by fast gas phase oxidation

NASA Astrophysics Data System (ADS)

Lu, K.; Tan, Z.; Wang, H.; Li, X.; Wu, Z.; Chen, Q.; Wu, Y.; Ma, X.; Liu, Y.; Chen, X.; Shang, D.; Dong, H.; Zeng, L.; Shao, M.; Hu, M.; Fuchs, H.; Novelli, A.; Broch, S.; Hofzumahaus, A.; Holland, F.; Rohrer, F.; Bohn, B.; Georgios, G.; Schmitt, S. H.; Schlag, P.; Kiendler-Scharr, A.; Wahner, A.; Zhang, Y.

2017-12-01

Heavy haze conditions were frequently presented in the airsheds of Beijing and surrounding areas, especially during winter time. To explore the trace gas oxidation and the subsequent formation of aerosols, a comprehensive field campaign was performed at a regional site (in the campus of University of Chinese Academy of Science, UCAS) in Beijing winter 2016. Serious haze pollution processes were often observed with the fast increase of inorganic salt (especially nitrate) and these pollutions were always associated with enhanced humidity and the concentrations of PAN (PeroxyAcyl Nitrates) which is normally a marker of gas phase oxidations from NOx and VOCs. Moreover, based on the measurements of OH, HO2, RO2, total OH reactivity, N2O5, NO, NO2, SO2, particle concentrations/distributions/chemical compositions, and meteorological parameters, the gas phase oxidation rates that leads to the formation of sulfate, nitrate and secondary organic aerosols were estimated. These determined formation rates were clearly enhanced by several folds during pollution episodes compared to that of the clean air masses. Preliminary analysis result showed that the gas phase formation potential of nitrate and secondary organic aerosols were larger than the observed concentrations of nitrate and SOA of which the excess production may be explained by deposition and dilution.

Secondary organic aerosol from atmospheric photooxidation of indole

NASA Astrophysics Data System (ADS)

Montoya-Aguilera, Julia; Horne, Jeremy R.; Hinks, Mallory L.; Fleming, Lauren T.; Perraud, Véronique; Lin, Peng; Laskin, Alexander; Laskin, Julia; Dabdub, Donald; Nizkorodov, Sergey A.

2017-09-01

Indole is a heterocyclic compound emitted by various plant species under stressed conditions or during flowering events. The formation, optical properties, and chemical composition of secondary organic aerosol (SOA) formed by low-NOx photooxidation of indole were investigated. The SOA yield (1. 3 ± 0. 3) was estimated from measuring the particle mass concentration with a scanning mobility particle sizer (SMPS) and correcting it for wall loss effects. The high value of the SOA mass yield suggests that most oxidized indole products eventually end up in the particle phase. The SOA particles were collected on filters and analysed offline with UV-vis spectrophotometry to measure the mass absorption coefficient (MAC) of the bulk sample. The samples were visibly brown and had MAC values of ˜ 2 m2 g-1 at λ = 300 nm and ˜ 0. 5 m2 g-1 at λ = 400 nm, comparable to strongly absorbing brown carbon emitted from biomass burning. The chemical composition of SOA was examined with several mass spectrometry methods. Direct analysis in real-time mass spectrometry (DART-MS) and nanospray desorption electrospray high-resolution mass spectrometry (nano-DESI-HRMS) were both used to provide information about the overall distribution of SOA compounds. High-performance liquid chromatography, coupled to photodiode array spectrophotometry and high-resolution mass spectrometry (HPLC-PDA-HRMS), was used to identify chromophoric compounds that are responsible for the brown colour of SOA. Indole derivatives, such as tryptanthrin, indirubin, indigo dye, and indoxyl red, were found to contribute significantly to the visible absorption spectrum of indole SOA. The potential effect of indole SOA on air quality was explored with an airshed model, which found elevated concentrations of indole SOA during the afternoon hours contributing considerably to the total organic aerosol under selected scenarios. Because of its high MAC values, indole SOA can contribute to decreased visibility and poor air

New Zealand traffic and local air quality.

PubMed

Irving, Paul; Moncrieff, Ian

2004-12-01

Since 1996 the New Zealand Ministry of Transport (MOT) has been investigating the effects of road transport on local air quality. The outcome has been the government's Vehicle Fleet Emissions Control Strategy (VFECS). This is a programme of measures designed to assist with the improvement in local air quality, and especially in the appropriate management of transport sector emissions. Key to the VFECS has been the development of tools to assess and predict the contribution of vehicle emissions to local air pollution, in a given urban situation. Determining how vehicles behave as an emissions source, and more importantly, how the combined traffic flows contribute to the total emissions within a given airshed location was an important element of the programme. The actual emissions output of a vehicle is more than that determined by a certified emission standard, at the point of manufacture. It is the engine technology's general performance capability, in conjunction with the local driving conditions, that determines its actual emissions output. As vehicles are a mobile emissions source, to understand the effect of vehicle technology, it is necessary to work with the average fleet performance, or "fleet-weighted average emissions rate". This is the unit measure of performance of the general traffic flow that could be passing through a given road corridor or network, as an average, over time. The flow composition can be representative of the national fleet population, but also may feature particular vehicle types in a given locality, thereby have a different emissions 'signature'. A summary of the range of work that has been completed as part of the VFECS programme is provided. The NZ Vehicle Fleet Emissions Model and the derived data set available in the NZ Traffic Emission Rates provide a significant step forward in the consistent analysis of practical, sustainable vehicle emissions policy and air-quality management in New Zealand.

MEPSA: minimum energy pathway analysis for energy landscapes.

PubMed

Marcos-Alcalde, Iñigo; Setoain, Javier; Mendieta-Moreno, Jesús I; Mendieta, Jesús; Gómez-Puertas, Paulino

2015-12-01

From conformational studies to atomistic descriptions of enzymatic reactions, potential and free energy landscapes can be used to describe biomolecular systems in detail. However, extracting the relevant data of complex 3D energy surfaces can sometimes be laborious. In this article, we present MEPSA (Minimum Energy Path Surface Analysis), a cross-platform user friendly tool for the analysis of energy landscapes from a transition state theory perspective. Some of its most relevant features are: identification of all the barriers and minima of the landscape at once, description of maxima edge profiles, detection of the lowest energy path connecting two minima and generation of transition state theory diagrams along these paths. In addition to a built-in plotting system, MEPSA can save most of the generated data into easily parseable text files, allowing more versatile uses of MEPSA's output such as the generation of molecular dynamics restraints from a calculated path. MEPSA is freely available (under GPLv3 license) at: http://bioweb.cbm.uam.es/software/MEPSA/ CONTACT: pagomez@cbm.csic.es. Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dynamic assessment of microbial ecology (DAME): a web app for interactive analysis and visualization of microbial sequencing data.

PubMed

Piccolo, Brian D; Wankhade, Umesh D; Chintapalli, Sree V; Bhattacharyya, Sudeepa; Chunqiao, Luo; Shankar, Kartik

2018-03-15

Dynamic assessment of microbial ecology (DAME) is a Shiny-based web application for interactive analysis and visualization of microbial sequencing data. DAME provides researchers not familiar with R programming the ability to access the most current R functions utilized for ecology and gene sequencing data analyses. Currently, DAME supports group comparisons of several ecological estimates of α-diversity and β-diversity, along with differential abundance analysis of individual taxa. Using the Shiny framework, the user has complete control of all aspects of the data analysis, including sample/experimental group selection and filtering, estimate selection, statistical methods and visualization parameters. Furthermore, graphical and tabular outputs are supported by R packages using D3.js and are fully interactive. DAME was implemented in R but can be modified by Hypertext Markup Language (HTML), Cascading Style Sheets (CSS), and JavaScript. It is freely available on the web at https://acnc-shinyapps.shinyapps.io/DAME/. Local installation and source code are available through Github (https://github.com/bdpiccolo/ACNC-DAME). Any system with R can launch DAME locally provided the shiny package is installed. bdpiccolo@uams.edu.

IAEA Coordinated Research Project on HTGR Reactor Physics, Thermal-hydraulics and Depletion Uncertainty Analysis

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

Strydom, Gerhard; Bostelmann, F.

(CRP) on the HTGR Uncertainty Analysis in Modelling (UAM) be implemented. This CRP is a continuation of the previous IAEA and Organization for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) international activities on Verification and Validation (V&V) of available analytical capabilities for HTGR simulation for design and safety evaluations. Within the framework of these activities different numerical and experimental benchmark problems were performed and insight was gained about specific physics phenomena and the adequacy of analysis methods.« less

The unprecedented 2014 Legionnaires' disease outbreak in Portugal: atmospheric driving mechanisms

NASA Astrophysics Data System (ADS)

Russo, Ana; Gouveia, Célia M.; Soares, Pedro M. M.; Cardoso, Rita M.; Mendes, Manuel T.; Trigo, Ricardo M.

2018-03-01

A large outbreak of Legionnaires' disease occurred in November 2014 nearby Lisbon, Portugal. This epidemic infected 377 individuals by the Legionella pneumophila bacteria, resulting in 14 deaths. The primary source of transmission was contaminated aerosolized water which, when inhaled, lead to atypical pneumonia. The unseasonably warm temperatures during October 2014 may have played a role in the proliferation of Legionella species in cooling tower systems. The episode was further exacerbated by high relative humidity and a thermal inversion which limited the bacterial dispersion. Here, we analyze if the Legionella outbreak event occurred during a situation of extreme potential recirculation and/or stagnation characteristics. In order to achieve this goal, the Allwine and Whiteman approach was applied for a hindcast simulation covering the affected area during a near 20-year long period (1989-2007) and then for an independent period covering the 2014 event (15 October to 13 November 2014). The results regarding the average daily critical transport indices for the 1989-2007 period clearly indicate that the airshed is prone to stagnation as these events have a dominant presence through most of the study period (42%), relatively to the occurrence of recirculation (18%) and ventilation (17%) events. However, the year of 2014 represents an exceptional year when compared to the 1989-2007 period, with 53 and 33% of the days being classified as under stagnation and recirculation conditions, respectively.

The unprecedented 2014 Legionnaires' disease outbreak in Portugal: atmospheric driving mechanisms.

PubMed

Russo, Ana; Gouveia, Célia M; Soares, Pedro M M; Cardoso, Rita M; Mendes, Manuel T; Trigo, Ricardo M

2018-03-23

A large outbreak of Legionnaires' disease occurred in November 2014 nearby Lisbon, Portugal. This epidemic infected 377 individuals by the Legionella pneumophila bacteria, resulting in 14 deaths. The primary source of transmission was contaminated aerosolized water which, when inhaled, lead to atypical pneumonia. The unseasonably warm temperatures during October 2014 may have played a role in the proliferation of Legionella species in cooling tower systems. The episode was further exacerbated by high relative humidity and a thermal inversion which limited the bacterial dispersion. Here, we analyze if the Legionella outbreak event occurred during a situation of extreme potential recirculation and/or stagnation characteristics. In order to achieve this goal, the Allwine and Whiteman approach was applied for a hindcast simulation covering the affected area during a near 20-year long period (1989-2007) and then for an independent period covering the 2014 event (15 October to 13 November 2014). The results regarding the average daily critical transport indices for the 1989-2007 period clearly indicate that the airshed is prone to stagnation as these events have a dominant presence through most of the study period (42%), relatively to the occurrence of recirculation (18%) and ventilation (17%) events. However, the year of 2014 represents an exceptional year when compared to the 1989-2007 period, with 53 and 33% of the days being classified as under stagnation and recirculation conditions, respectively.

[A prospective cohort study on injuries among school-age children with and without behavior problems].

PubMed

Peng, Ying-chun; Ni, Jin-fa; Tao, Fang-biao; Wu, Xi-ke

2003-08-01

To study the annual incidence of injuries and the relationship between behavior problems and injuries among school-age children. A prospective cohort study on injuries for 1-year follow-up period was conducted among 2 005 school-age children selected by cluster sampling from three primary schools in Maanshan city. They subjects were divided into two groups with or without exposure according to behavior problems rated by the Rutter Child Behavior Questionnaire at the beginning of the study. Nonparametric test was performed to analyze the differences in injuries between the two groups of children, and the influential factors for injuries were analyzed with multi-classification ordinal response variable logistic regression model. The overall incidence rate for injuries in school-age children was 42.51%, while among children with and without behavior problems were 64.87% and 38.85%, respectively. There were significant differences between the two groups (u = -6.054, P = 0.000). However, the incidence rates of injuries in school-age children with antisocial (A) behavior, neurotic (N) behavior and mixed (M) behavior were 66.99%, 67.41% and 61.40%, respectively. No significant differences were found among them (u(A,N) = -0.052, P = 0.958; u(A,M) = -0.400, P = 0.689; u(N,M) = -0.364, P = 0.716). Multivariate analysis indicated that injuries in school-age children were associated with children behavior problems, maternal age at childbirth, bad conditions during mother pregnancy, education background of mother, prevention measures for safety at home and the child accompanied to travel between school and home by adults. Behavior problems of children seemed to be the major risk factors for injuries. Children with behavior problems represented a significant risk group for injuries among school-age children. When planning intervention strategies on injuries, behavior problems should be emphasized to ensure optimal effectiveness of intervention.

Experimental Constraints on a Dark Matter Origin for the DAMA Annual Modulation Effect

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

Aalseth, Craig E.; Barbeau, Phil; Cerdeno, D. G.

2008-12-17

Abstract Follows: C. E. Aalseth,1 P. S. Barbeau,2 D. G. Cerdeño,3 J. Colaresi,4 J. I. Collar,2 P. de Lurgio,5 G. Drake,5 J. E. Fast,1 C. H. Greenberg,2 T. W. Hossbach,1 J. D. Kephart,1 M. G. Marino,7 H. S. Miley,1 J. L. Orrell,1 D. Reyna,6 R. G. H. Robertson,7 R. L. Talaga,5 O. Tench,4 T. D. Van Wechel,7 J. F. Wilkerson,7 and K. M. Yocum4 (CoGeNT Collaboration) 1Pacific Northwest National Laboratory, Richland, Washington 99352, USA 2Kavli Institute for Cosmological Physics and Enrico Fermi Institute, University of Chicago, Chicago, Illinois 60637, USA 3Departamento de Física Teórica C-XI & Instituto de Física Teóricamore » UAM-CSIC, Universidad Autónoma de Madrid, Cantoblanco, E-28049 Madrid, Spain 4CANBERRA Industries, Meriden, Connecticut 06450, USA 5Argonne National Laboratory, Argonne, Illinois 60439, USA 6Sandia National Laboratories, Livermore, California 94550, USA 7Center for Experimental Nuclear Physics and Astrophysics, and Department of Physics, University of Washington, Seattle, Washington 98195, USA Received 7 July 2008; revised 6 August 2008; published 17 December 2008 A claim for evidence of dark matter interactions in the DAMA experiment has been recently reinforced. We employ a new type of germanium detector to conclusively rule out a standard isothermal galactic halo of weakly interacting massive particles as the explanation for the annual modulation effect leading to the claim. Bounds are similarly imposed on a suggestion that dark pseudoscalars might lead to the effect. We describe the sensitivity to light dark matter particles achievable with our device, in particular, to next-to-minimal supersymmetric model candidates.« less

The status of the AMS system at MALT in its 20th year

NASA Astrophysics Data System (ADS)

Matsuzaki, Hiroyuki; Nakano, Chuichiro; Tsuchiya, Yoko S.; Ito, Seiji; Morita, Akira; Kusuno, Haruka; Miyake, Yasuto; Honda, Maki; Bautista VII, Angel T.; Kawamoto, Marina; Tokuyama, Hironori

2015-10-01

MALT (Micro Analysis Laboratory, Tandem accelerator, The University of Tokyo) was designed for a 'highly sensitive and precise elemental and isotopic microanalysis system' using an ion-beam generated by a Pelletron™ 5UD tandem accelerator. Currently, a multi-nuclide AMS (10Be, 14C, 26Al, 36Cl, 129I) system is available and shows good performance in both precision and sensitivity, and the accelerator serves for PIXE, NRA, ERDA/RBS measurements as well. The total operation time of the accelerator has been over 95,000 hours since the start of MALT, 20 years ago. After the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, many projects related to 129I have been conducted. The retrospective reconstruction of the 131I distribution at the accident from 129I is one of the most important missions for dose evaluation of the residents. The accident-derived 129I is also quite useful as a tracer for the general iodine dynamics in the environment. As a new tool for environmental assessment related to nuclear activity, including the global fallout from past atmospheric nuclear bomb testing, effects from the spent fuel reprocessing plant, and nuclear accidents such as Chernobyl and FDNPP, a 236U-AMS system is now under development.

A positive correlation between immunohistochemical expression of CD31 and mast cell tryptase in odontogenic tumors.

PubMed

Kouhsoltani, Maryam; Halimi, Monireh; Dibazar, Sana

2015-06-01

In this study, we compared mast cell tryptase and CD31 expression between odontogenic tumors with the aim of predicting the clinical behavior of these lesions at the time of initial biopsy. We also evaluated the correlation between mast cell tryptase and CD31 expression to clarify the role of mast cells (MCs) in the growth of odontogenic tumors. Immunohistochemical staining with anti-MC tryptase and anti-CD31 antibodies was performed on 48 cases of odontogenic tumors including solid ameloblastoma (SAM), unicystic ameloblastoma (UAM), odontogenic myxoma (OM), cystic calcifying odontogenic tumor (CCOT) and adenomatoid odontogenic tumor (AOT). Ten high power fields were analyzed for each sample. Total MC count was significantly increased in SAM compared to other odontogenic tumors (p<0.05). Microvessel density was statistically higher in SAM and AOT compared to remaining odontogenic tumors (p<0.05). A significant correlation was observed between MCs and microvessels in odontogenic tumors (p=0.018, r=0.34). Our findings suggest a role for MCs in aggressive clinical behavior of odontogenic tumors. The significant correlation found between MC count and microvessel density in odontogenic tumors is in agreement with the theory of participation of MCs in tumor progression. Targeting MC activity may represent an important nonsurgical therapeutic approach, especially for aggressive odontogenic tumors.

Impact of implicit effects on uncertainties and sensitivities of the Doppler coefficient of a LWR pin cell

NASA Astrophysics Data System (ADS)

Hursin, Mathieu; Leray, Olivier; Perret, Gregory; Pautz, Andreas; Bostelmann, Friederike; Aures, Alexander; Zwermann, Winfried

2017-09-01

In the present work, PSI and GRS sensitivity analysis (SA) and uncertainty quantification (UQ) methods, SHARK-X and XSUSA respectively, are compared for reactivity coefficient calculation; for reference the results of the TSUNAMI and SAMPLER modules of the SCALE code package are also provided. The main objective of paper is to assess the impact of the implicit effect, e.g., considering the effect of cross section perturbation on the self-shielding calculation, on the Doppler coefficient SA and UQ. Analyses are done for a Light Water Reactor (LWR) pin cell based on Phase I of the UAM LWR benchmark. The negligence of implicit effects in XSUSA and TSUNAMI leads to deviations of a few percent between the sensitivity profiles compared to SAMPLER and TSUNAMI (incl. implicit effects) except for 238U elastic scattering. The implicit effect is much larger for the SHARK-X calculations because of its coarser energy group structure between 10 eV and 10 keV compared to the applied SCALE libraries. It is concluded that the influence of the implicit effect strongly depends on the energy mesh of the nuclear data library of the neutron transport solver involved in the UQ calculations and may be magnified by the response considered.

Trapped Radiation Model Uncertainties: Model-Data and Model-Model Comparisons

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

2000-01-01

The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux and dose measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP, LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir Space Station. This report gives the details of the model-data comparisons-summary results in terms of empirical model uncertainty factors that can be applied for spacecraft design applications are given in a combination report. The results of model-model comparisons are also presented from standard AP8 and AE8 model predictions compared with the European Space Agency versions of AP8 and AE8 and with Russian-trapped radiation models.

Trapped Radiation Model Uncertainties: Model-Data and Model-Model Comparisons

NASA Technical Reports Server (NTRS)

Armstrong, T. W.; Colborn, B. L.

2000-01-01

The standard AP8 and AE8 models for predicting trapped proton and electron environments have been compared with several sets of flight data to evaluate model uncertainties. Model comparisons are made with flux and dose measurements made on various U.S. low-Earth orbit satellites (APEX, CRRES, DMSP. LDEF, NOAA) and Space Shuttle flights, on Russian satellites (Photon-8, Cosmos-1887, Cosmos-2044), and on the Russian Mir space station. This report gives the details of the model-data comparisons -- summary results in terms of empirical model uncertainty factors that can be applied for spacecraft design applications are given in a companion report. The results of model-model comparisons are also presented from standard AP8 and AE8 model predictions compared with the European Space Agency versions of AP8 and AE8 and with Russian trapped radiation models.

Assessing transboundary influences in the lower Rio Grande Valley

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

Mukerjee, S.; Shadwick, D.S.; Dean, K.E.

1999-07-01

The Lower Rio Grande Valley Transboundary Air Pollution Project (TAPP) was a US-Mexico Border XXI Program project to assess transboundary air pollution in and near Brownsville, Texas. The study used a three-site air monitoring network very close to the border to capture the direct impact of local sources and transboundary transport. Ambient data included particulate mass and elemental composition, VOCs, PAHs, pesticides, and meteorology. Also, near real-time, PM{sub 2.5} mass measurements captured potential pollutant plume events occurring over 1-h periods. Data collected were compared to screening levels and other monitoring data to assess general air pollution impacts on nearby bordermore » communities. Wind sector analyses, chemical tracer analyses, principal component analyses, and other techniques were used to assess the extent of transboundary transport of air pollutants and identify possible transboundary air pollution sources. Overall, ambient levels were comparable to or lower than other urban and rural areas in Texas and elsewhere. Movement of air pollution across the border did not appear to cause noticeable deterioration of air quality on the US side of the Lower Rio Grande Valley. Dominant southeasterly winds from the Gulf of Mexico were largely responsible for the clean air conditions in the Brownsville airshed. Few observations of pollutants exceeded effects screening levels, almost all being VOCs; these appeared to be due to local events and immediate influences, not regional phenomena or persistent transboundary plumes.« less

Chemical Composition and Source Apportionment of Size ...

EPA Pesticide Factsheets

The Cleveland airshed comprises a complex mixture of industrial source emissions that contribute to periods of non-attainment for fine particulate matter (PM 2.5 ) and are associated with increased adverse health outcomes in the exposed population. Specific PM sources responsible for health effects however are not fully understood. Size-fractionated PM (coarse, fine, and ultrafine) samples were collected using a ChemVol sampler at an urban site (G.T. Craig (GTC)) and rural site (Chippewa Lake (CLM)) from July 2009 to June 2010, and then chemically analyzed. The resulting speciated PM data were apportioned by EPA positive matrix factorization to identify emission sources for each size fraction and location. For comparisons with the ChemVol results, PM samples were also collected with sequential dichotomous and passive samplers, and evaluated for source contributions to each sampling site. The ChemVol results showed that annual average concentrations of PM, elemental carbon, and inorganic elements in the coarse fraction at GTC were ~ 2, ~7, and ~3 times higher than those at CLM, respectively, while the smaller size fractions at both sites showed similar annual average concentrat ions. Seasonal variations of secondary aerosols (e.g., high N03- level in winter and high SO42- level in summer) were observed at both sites. Source apportionment results demonstrated that the PM samples at GTC and CLM were enriched with local industrial sources (e.g., steel plant and coa

Particle size distribution and composition in a mechanically ventilated school building during air pollution episodes.

PubMed

Parker, J L; Larson, R R; Eskelson, E; Wood, E M; Veranth, J M

2008-10-01

Particle count-based size distribution and PM(2.5) mass were monitored inside and outside an elementary school in Salt Lake City (UT, USA) during the winter atmospheric inversion season. The site is influenced by urban traffic and the airshed is subject to periods of high PM(2.5) concentration that is mainly submicron ammonium and nitrate. The school building has mechanical ventilation with filtration and variable-volume makeup air. Comparison of the indoor and outdoor particle size distribution on the five cleanest and five most polluted school days during the study showed that the ambient submicron particulate matter (PM) penetrated the building, but indoor concentrations were about one-eighth of outdoor levels. The indoor:outdoor PM(2.5) mass ratio averaged 0.12 and particle number ratio for sizes smaller than 1 microm averaged 0.13. The indoor submicron particle count and indoor PM(2.5) mass increased slightly during pollution episodes but remained well below outdoor levels. When the building was occupied the indoor coarse particle count was much higher than ambient levels. These results contribute to understanding the relationship between ambient monitoring station data and the actual human exposure inside institutional buildings. The study confirms that staying inside a mechanically ventilated building reduces exposure to outdoor submicron particles. This study supports the premise that remaining inside buildings during particulate matter (PM) pollution episodes reduces exposure to submicron PM. New data on a mechanically ventilated institutional building supplements similar studies made in residences.

Evaluation of microstructure stability at the interfaces of Al-6061 welds fabricated using ultrasonic additive manufacturing

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

Sridharan, Niyanth S.; Gussev, Maxim N.; Parish, Chad M.

Here, ultrasonic additive manufacturing (UAM) is a solid-state additive manufacturing process that uses fundamental principles of ultrasonic welding and sequential layering of tapes to fabricate complex three-dimensional (3-D) components. One of the factors limiting the use of this technology is the poor tensile strength along the z-axis. Recent work has demonstrated the improvement of the z-axis properties after post-processing treatments. The abnormally high stability of the grains at the interface during post-weld heat treatments is, however, not yet well understood. In this work we use multiscale characterization to understand the stability of the grains during post-weld heat treatments. Aluminum alloymore » (6061) builds, fabricated using ultrasonic additive manufacturing, were post-weld heat treated at 180, 330 and 580 °C. The grains close to the tape interfaces are stable during post-weld heat treatments at high temperatures (i.e., 580 °C). This is in contrast to rapid grain growth that takes place in the bulk. Transmission electron microscopy and atom-probe tomography display a significant enrichment of oxygen and magnesium near the stable interfaces. Based on the detailed characterization, two mechanisms are proposed and evaluated: nonequilibrium nano-dispersed oxides impeding the grain growth due to grain boundary pinning, or grain boundary segregation of magnesium and oxygen reducing the grain boundary energy.« less

Evaluation of microstructure stability at the interfaces of Al-6061 welds fabricated using ultrasonic additive manufacturing

DOE PAGES

Sridharan, Niyanth S.; Gussev, Maxim N.; Parish, Chad M.; ...

2018-03-06

Here, ultrasonic additive manufacturing (UAM) is a solid-state additive manufacturing process that uses fundamental principles of ultrasonic welding and sequential layering of tapes to fabricate complex three-dimensional (3-D) components. One of the factors limiting the use of this technology is the poor tensile strength along the z-axis. Recent work has demonstrated the improvement of the z-axis properties after post-processing treatments. The abnormally high stability of the grains at the interface during post-weld heat treatments is, however, not yet well understood. In this work we use multiscale characterization to understand the stability of the grains during post-weld heat treatments. Aluminum alloymore » (6061) builds, fabricated using ultrasonic additive manufacturing, were post-weld heat treated at 180, 330 and 580 °C. The grains close to the tape interfaces are stable during post-weld heat treatments at high temperatures (i.e., 580 °C). This is in contrast to rapid grain growth that takes place in the bulk. Transmission electron microscopy and atom-probe tomography display a significant enrichment of oxygen and magnesium near the stable interfaces. Based on the detailed characterization, two mechanisms are proposed and evaluated: nonequilibrium nano-dispersed oxides impeding the grain growth due to grain boundary pinning, or grain boundary segregation of magnesium and oxygen reducing the grain boundary energy.« less

A two-period assessment of changes in specialist contact in a high-risk pregnancy telemedical program.

PubMed

Britt, David W; Norton, Jonathan D; Hubanks, Amanda S; Navidad, Susan A; Perkins, Rosalyn J; Lowery, Curtis L

2006-02-01

The purpose was to examine the organizational impact of a state-wide high-risk pregnancy telemedical system, Antenatal and Neonatal Guidelines, Education and Learning System (ANGELS), after the first year of its roll out. The focus is on several aspects of system organization, including the volume and diversity of patient-based telemedical consultations and weekly telemedical case discussions, telephone consultations, and changes in the pattern of birth-related patient transports. Individual data on patient transports and associated hospital days, provider-specialist telephone calls, and telemedical consultations were collected for two time periods: December 2002-May 2003 (prior to initiation of ANGELS), and December 2003-May 2004 (postinitiation of ANGELS). Different statistical tests were constructed to compare the two periods as appropriate. Significant increases were observed in the volume and geographic diversity of telemedical consultations and the volume of telephone consultations. There was a moderate, but nonsignificant decrease in the number of maternal transports to University of Arkansas School of Medical Sciences (UAMS), and the average length of stay decreased. The type of specialist-provider and specialist-patient contact has changed as the ANGELS high-risk pregnancy telemedical system has evolved over the first year. We conclude that the rollout of the ANGELS program is changing the shape of high-risk patient care in Arkansas, and we attribute that to an evolving collegial network between specialists and generalists.

Propionibacterium-Produced Coproporphyrin III Induces Staphylococcus aureus Aggregation and Biofilm Formation

PubMed Central

Wollenberg, Michael S.; Claesen, Jan; Escapa, Isabel F.; Aldridge, Kelly L.; Fischbach, Michael A.

2014-01-01

ABSTRACT The majority of bacteria detected in the nostril microbiota of most healthy adults belong to three genera: Propionibacterium, Corynebacterium, and Staphylococcus. Among these staphylococci is the medically important bacterium Staphylococcus aureus. Almost nothing is known about interspecies interactions among bacteria in the nostrils. We observed that crude extracts of cell-free conditioned medium from Propionibacterium spp. induce S. aureus aggregation in culture. Bioassay-guided fractionation implicated coproporphyrin III (CIII), the most abundant extracellular porphyrin produced by human-associated Propionibacterium spp., as a cause of S. aureus aggregation. This aggregation response depended on the CIII dose and occurred during early stationary-phase growth, and a low pH (~4 to 6) was necessary but was not sufficient for its induction. Additionally, CIII induced plasma-independent S. aureus biofilm development on an abiotic surface in multiple S. aureus strains. In strain UAMS-1, CIII stimulation of biofilm depended on sarA, a key biofilm regulator. This study is one of the first demonstrations of a small-molecule-mediated interaction among medically relevant members of the nostril microbiota and the first description of a role for CIII in bacterial interspecies interactions. Our results indicate that CIII may be an important mediator of S. aureus aggregation and/or biofilm formation in the nostril or other sites inhabited by Propionibacterium spp. and S. aureus. PMID:25053784

In situ characterization of uranium and americium oxide solid solution formation for CRMP process: first combination of in situ XRD and XANES measurements.

PubMed

Caisso, Marie; Picart, Sébastien; Belin, Renaud C; Lebreton, Florent; Martin, Philippe M; Dardenne, Kathy; Rothe, Jörg; Neuville, Daniel R; Delahaye, Thibaud; Ayral, André

2015-04-14

Transmutation of americium in heterogeneous mode through the use of U1-xAmxO2±δ ceramic pellets, also known as Americium Bearing Blankets (AmBB), has become a major research axis. Nevertheless, in order to consider future large-scale deployment, the processes involved in AmBB fabrication have to minimize fine particle dissemination, due to the presence of americium, which considerably increases the risk of contamination. New synthesis routes avoiding the use of pulverulent precursors are thus currently under development, such as the Calcined Resin Microsphere Pelletization (CRMP) process. It is based on the use of weak-acid resin (WAR) microspheres as precursors, loaded with actinide cations. After two specific calcinations under controlled atmospheres, resin microspheres are converted into oxide microspheres composed of a monophasic U1-xAmxO2±δ phase. Understanding the different mechanisms during thermal conversion, that lead to the release of organic matter and the formation of a solid solution, appear essential. By combining in situ techniques such as XRD and XAS, it has become possible to identify the key temperatures for oxide formation, and the corresponding oxidation states taken by uranium and americium during mineralization. This paper thus presents the first results on the mineralization of (U,Am) loaded resin microspheres into a solid solution, through in situ XAS analysis correlated with HT-XRD.

Contribution of the Staphylococcus aureus Atl AM and GL murein hydrolase activities in cell division, autolysis, and biofilm formation.

PubMed

Bose, Jeffrey L; Lehman, McKenzie K; Fey, Paul D; Bayles, Kenneth W

2012-01-01

The most prominent murein hydrolase of Staphylococcus aureus, AtlA, is a bifunctional enzyme that undergoes proteolytic cleavage to yield two catalytically active proteins, an amidase (AM) and a glucosaminidase (GL). Although the bifunctional nature of AtlA has long been recognized, most studies have focused on the combined functions of this protein in cell wall metabolism and biofilm development. In this study, we generated mutant derivatives of the clinical S. aureus isolate, UAMS-1, in which one or both of the AM and GL domains of AtlA have been deleted. Examination of these strains revealed that each mutant exhibited growth rates comparable to the parental strain, but showed clumping phenotypes and lysis profiles that were distinct from the parental strain and each other, suggesting distinct roles in cell wall metabolism. Given the known function of autolysis in the release of genomic DNA for use as a biofilm matrix molecule, we also tested the mutants in biofilm assays and found both AM and GL necessary for biofilm development. Furthermore, the use of enzymatically inactive point mutations revealed that both AM and GL must be catalytically active for S. aureus to form a biofilm. The results of this study provide insight into the relative contributions of AM and GL in S. aureus and demonstrate the contribution of Atl-mediated lysis in biofilm development.

Daily ambient air pollution metrics for five cities: Evaluation of data-fusion-based estimates and uncertainties

NASA Astrophysics Data System (ADS)

Friberg, Mariel D.; Kahn, Ralph A.; Holmes, Heather A.; Chang, Howard H.; Sarnat, Stefanie Ebelt; Tolbert, Paige E.; Russell, Armistead G.; Mulholland, James A.

2017-06-01

Birmingham. The greatest improvements occur for O3 and PM2.5. Squared spatiotemporal correlation coefficients range between simulations and observations determined using cross-validation across all cities for air pollutants of secondary and mixed origins are R2 = 0.88-0.93 (O3), 0.81-0.89 (SO4), 0.67-0.83 (PM2.5), 0.52-0.72 (NO3), 0.43-0.80 (NH4), 0.32-0.51 (OC), and 0.14-0.71 (PM10). Results for relatively homogeneous pollutants of secondary origin, tend to be better than those for more spatially heterogeneous (larger spatial gradients) pollutants of primary origin (NOx, CO, SO2 and EC). Generally, background concentrations and spatial concentration gradients reflect interurban airshed complexity and the effects of regional transport, whereas daily spatial pattern variability shows intra-urban consistency in the fused data. With sufficiently high CTM spatial resolution, traffic-related pollutants exhibit gradual concentration gradients that peak toward the urban centers. Ambient pollutant concentration uncertainty estimates for the fused data are both more accurate and smaller than those for either the observations or the model simulations alone.

Models and role models.

PubMed

ten Cate, Jacob M

2015-01-01

Developing experimental models to understand dental caries has been the theme in our research group. Our first, the pH-cycling model, was developed to investigate the chemical reactions in enamel or dentine, which lead to dental caries. It aimed to leverage our understanding of the fluoride mode of action and was also utilized for the formulation of oral care products. In addition, we made use of intra-oral (in situ) models to study other features of the oral environment that drive the de/remineralization balance in individual patients. This model addressed basic questions, such as how enamel and dentine are affected by challenges in the oral cavity, as well as practical issues related to fluoride toothpaste efficacy. The observation that perhaps fluoride is not sufficiently potent to reduce dental caries in the present-day society triggered us to expand our knowledge in the bacterial aetiology of dental caries. For this we developed the Amsterdam Active Attachment biofilm model. Different from studies on planktonic ('single') bacteria, this biofilm model captures bacteria in a habitat similar to dental plaque. With data from the combination of these models, it should be possible to study separate processes which together may lead to dental caries. Also products and novel agents could be evaluated that interfere with either of the processes. Having these separate models in place, a suggestion is made to design computer models to encompass the available information. Models but also role models are of the utmost importance in bringing and guiding research and researchers. 2015 S. Karger AG, Basel

Expert models and modeling processes associated with a computer-modeling tool

NASA Astrophysics Data System (ADS)

Zhang, Baohui; Liu, Xiufeng; Krajcik, Joseph S.

2006-07-01

Holding the premise that the development of expertise is a continuous process, this study concerns expert models and modeling processes associated with a modeling tool called Model-It. Five advanced Ph.D. students in environmental engineering and public health used Model-It to create and test models of water quality. Using think aloud technique and video recording, we captured their computer screen modeling activities and thinking processes. We also interviewed them the day following their modeling sessions to further probe the rationale of their modeling practices. We analyzed both the audio-video transcripts and the experts' models. We found the experts' modeling processes followed the linear sequence built in the modeling program with few instances of moving back and forth. They specified their goals up front and spent a long time thinking through an entire model before acting. They specified relationships with accurate and convincing evidence. Factors (i.e., variables) in expert models were clustered, and represented by specialized technical terms. Based on the above findings, we made suggestions for improving model-based science teaching and learning using Model-It.

10. MOVABLE BED SEDIMENTATION MODELS. DOGTOOTH BEND MODEL (MODEL SCALE: ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

10. MOVABLE BED SEDIMENTATION MODELS. DOGTOOTH BEND MODEL (MODEL SCALE: 1' = 400' HORIZONTAL, 1' = 100' VERTICAL), AND GREENVILLE BRIDGE MODEL (MODEL SCALE: 1' = 360' HORIZONTAL, 1' = 100' VERTICAL). - Waterways Experiment Station, Hydraulics Laboratory, Halls Ferry Road, 2 miles south of I-20, Vicksburg, Warren County, MS

Anthropogenic climate change has driven Lake Superior productivity beyond the range of Holocene variability

NASA Astrophysics Data System (ADS)

OBeirne, M. D.; Werne, J. P.; Hecky, R. E.; Johnson, T. C.; Katsev, S.; Reavie, E. D.

2013-12-01

Recent studies have noted that changes in Lake Superior's physical, chemical and biological processes are apparent - including a warming of the surface waters at a rate twice as great as the surrounding airshed in the last 20 years. These changes are often difficult to perceive as cause for concern when not placed within a historical context. In this study, bulk C and N abundance and stable isotope composition was determined on sediments from three piston and corresponding gravity cores, representing a record of lake-wide paleoproductivity trends spanning the Holocene. These data are compared with the same measurements on eight multi-cores sampled at high resolution spanning the past ~200 years, which allows for the historical comparison with recent (1800 A.D. to present) productivity trends. Throughout the Holocene, Lake Superior experienced a slow, steady increase in productivity consistent with conventional lake ontogeny. During the last 200 years, however, the Lake Superior basin has undergone biogeochemical changes that are unique in the context of the Holocene. Lake-wide sedimentary bulk organic carbon data indicate increasing primary production between 1900 and present, as indicated by a ~2‰ increase in δ13Corg. In contrast,δ15Norg values, which increased throughout the Holocene, become progressively 15N-depleted after 1900, likely due to atmospheric deposition of NOx from fossil fuel combustion. The most recent increases in primary productivity are likely a response to increasing water temperatures, leading to longer ice-free periods as previously documented in Lake Superior.

The relationship between airborne small ions and particles in urban environments

NASA Astrophysics Data System (ADS)

Ling, Xuan; Jayaratne, Rohan; Morawska, Lidia

2013-11-01

Ions play an important role in affecting climate and particle formation in the atmosphere. Small ions rapidly attach to particles in the air and, therefore, studies have shown that they are suppressed in polluted environments. Urban environments, in particular, are dominated by motor vehicle emissions and, since motor vehicles are a source of both particles and small ions, the relationship between these two parameters is not well known. In order to gain a better understanding of this relationship, an intensive campaign was undertaken where particles and small ions of both signs were monitored over two week periods at each of three sites A, B and C that were affected to varying degrees by vehicle emissions. Site A was close to a major road and reported the highest particle number and lowest small ion concentrations. Precursors from motor vehicle emissions gave rise to clear particle formation events on five days and, on each day this was accompanied by a suppression of small ions. Observations at Site B, which was located within the urban airshed, though not adjacent to motor traffic, showed particle enhancement but no formation events. Site C was a clean site, away from urban sources. This site reported the lowest particle number and highest small ion concentration. The positive small ion concentration was 10%-40% higher than the corresponding negative value at all sites. These results confirm previous findings that there is a clear inverse relationship between small ions and particles in urban environments dominated by motor vehicle emissions.

Source-to-exposure assessment with the Pangea multi-scale framework - case study in Australia.

PubMed

Wannaz, Cedric; Fantke, Peter; Lane, Joe; Jolliet, Olivier

2018-01-24

Effective planning of airshed pollution mitigation is often constrained by a lack of integrative analysis able to relate the relevant emitters to the receptor populations at risk. Both emitter and receptor perspectives are therefore needed to consistently inform emission and exposure reduction measures. This paper aims to extend the Pangea spatial multi-scale multimedia framework to evaluate source-to-receptor relationships of industrial sources of organic pollutants in Australia. Pangea solves a large compartmental system in parallel by block to determine arrays of masses at steady-state for 100 000+ compartments and 4000+ emission scenarios, and further computes population exposure by inhalation and ingestion. From an emitter perspective, radial spatial distributions of population intakes show high spatial variation in intake fractions from 0.68 to 33 ppm for benzene, and from 0.006 to 9.5 ppm for formaldehyde, contrasting urban, rural, desert, and sea source locations. Extending analyses to the receptor perspective, population exposures from the combined emissions of 4101 Australian point sources are more extended for benzene that travels over longer distances, versus formaldehyde that has a more local impact. Decomposing exposure per industrial sector shows petroleum and steel industry as the highest contributing industrial sectors for benzene, whereas the electricity sector and petroleum refining contribute most to formaldehyde exposures. The source apportionment identifies the main sources contributing to exposure at five locations. Overall, this paper demonstrates high interest in addressing exposures from both an emitter perspective well-suited to inform product oriented approaches such as LCA, and from a receptor perspective for health risk mitigation.

Summarising climate and air quality (ozone) data on self-organising maps: a Sydney case study.

PubMed

Jiang, Ningbo; Betts, Alan; Riley, Matt

2016-02-01

This paper explores the classification and visualisation utility of the self-organising map (SOM) method in the context of New South Wales (NSW), Australia, using gridded NCEP/NCAR geopotential height reanalysis for east Australia, together with multi-site meteorological and air quality data for Sydney from the NSW Office of Environment and Heritage Air Quality Monitoring Network. A twice-daily synoptic classification has been derived for east Australia for the period of 1958-2012. The classification has not only reproduced the typical synoptic patterns previously identified in the literature but also provided an opportunity to visualise the subtle, non-linear change in the eastward-migrating synoptic systems influencing NSW (including Sydney). The summarisation of long-term, multi-site air quality/meteorological data from the Sydney basin on the SOM plane has identified a set of typical air pollution/meteorological spatial patterns in the region. Importantly, the examination of these patterns in relation to synoptic weather types has provided important visual insights into how local and synoptic meteorological conditions interact with each other and affect the variability of air quality in tandem. The study illustrates that while synoptic circulation types are influential, the within-type variability in mesoscale flows plays a critical role in determining local ozone levels in Sydney. These results indicate that the SOM can be a useful tool for assessing the impact of weather and climatic conditions on air quality in the regional airshed. This study further promotes the use of the SOM method in environmental research.

Students' Models of Curve Fitting: A Models and Modeling Perspective

ERIC Educational Resources Information Center

Gupta, Shweta

2010-01-01

The Models and Modeling Perspectives (MMP) has evolved out of research that began 26 years ago. MMP researchers use Model Eliciting Activities (MEAs) to elicit students' mental models. In this study MMP was used as the conceptual framework to investigate the nature of students' models of curve fitting in a problem-solving environment consisting of…

Semiparametric modeling: Correcting low-dimensional model error in parametric models

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

Berry, Tyrus, E-mail: thb11@psu.edu; Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, 503 Walker Building, University Park, PA 16802-5013

2016-03-01

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consistsmore » of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.« less

Global Carbon Cycle Modeling in GISS ModelE2 GCM

NASA Astrophysics Data System (ADS)

Aleinov, I. D.; Kiang, N. Y.; Romanou, A.; Romanski, J.

2014-12-01

Consistent and accurate modeling of the Global Carbon Cycle remains one of the main challenges for the Earth System Models. NASA Goddard Institute for Space Studies (GISS) ModelE2 General Circulation Model (GCM) was recently equipped with a complete Global Carbon Cycle algorithm, consisting of three integrated components: Ent Terrestrial Biosphere Model (Ent TBM), Ocean Biogeochemistry Module and atmospheric CO2 tracer. Ent TBM provides CO2 fluxes from the land surface to the atmosphere. Its biophysics utilizes the well-known photosynthesis functions of Farqhuar, von Caemmerer, and Berry and Farqhuar and von Caemmerer, and stomatal conductance of Ball and Berry. Its phenology is based on temperature, drought, and radiation fluxes, and growth is controlled via allocation of carbon from labile carbohydrate reserve storage to different plant components. Soil biogeochemistry is based on the Carnegie-Ames-Stanford (CASA) model of Potter et al. Ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. Atmospheric CO2 is advected with a quadratic upstream algorithm implemented in atmospheric part of ModelE2. Here we present the results for pre-industrial equilibrium and modern transient simulations and provide comparison to available observations. We also discuss the process of validation and tuning of particular algorithms used in the model.

Target Scattering Metrics: Model-Model and Model-Data Comparisons

DTIC Science & Technology

2017-12-13

measured synthetic aperture sonar (SAS) data or from numerical models is investigated. Metrics are needed for quantitative comparisons for signals...candidate metrics for model-model comparisons are examined here with a goal to consider raw data prior to its reduction to data products, which may...be suitable for input to classification schemes. The investigated metrics are then applied to model-data comparisons. INTRODUCTION Metrics for

Target Scattering Metrics: Model-Model and Model Data comparisons

DTIC Science & Technology

2017-12-13

measured synthetic aperture sonar (SAS) data or from numerical models is investigated. Metrics are needed for quantitative comparisons for signals...candidate metrics for model-model comparisons are examined here with a goal to consider raw data prior to its reduction to data products, which may...be suitable for input to classification schemes. The investigated metrics are then applied to model-data comparisons. INTRODUCTION Metrics for

Comparative Protein Structure Modeling Using MODELLER

PubMed Central

Webb, Benjamin; Sali, Andrej

2016-01-01

Comparative protein structure modeling predicts the three-dimensional structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and how to use the ModBase database of such models, and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. PMID:27322406

[Bone remodeling and modeling/mini-modeling.

PubMed

Hasegawa, Tomoka; Amizuka, Norio

Modeling, adapting structures to loading by changing bone size and shapes, often takes place in bone of the fetal and developmental stages, while bone remodeling-replacement of old bone into new bone-is predominant in the adult stage. Modeling can be divided into macro-modeling(macroscopic modeling)and mini-modeling(microscopic modeling). In the cellular process of mini-modeling, unlike bone remodeling, bone lining cells, i.e., resting flattened osteoblasts covering bone surfaces will become active form of osteoblasts, and then, deposit new bone onto the old bone without mediating osteoclastic bone resorption. Among the drugs for osteoporotic treatment, eldecalcitol(a vitamin D3 analog)and teriparatide(human PTH[1-34])could show mini-modeling based bone formation. Histologically, mature, active form of osteoblasts are localized on the new bone induced by mini-modeling, however, only a few cell layer of preosteoblasts are formed over the newly-formed bone, and accordingly, few osteoclasts are present in the region of mini-modeling. In this review, histological characteristics of bone remodeling and modeling including mini-modeling will be introduced.

Vector models and generalized SYK models

DOE PAGES

Peng, Cheng

2017-05-23

Here, we consider the relation between SYK-like models and vector models by studying a toy model where a tensor field is coupled with a vector field. By integrating out the tensor field, the toy model reduces to the Gross-Neveu model in 1 dimension. On the other hand, a certain perturbation can be turned on and the toy model flows to an SYK-like model at low energy. Furthermore, a chaotic-nonchaotic phase transition occurs as the sign of the perturbation is altered. We further study similar models that possess chaos and enhanced reparameterization symmetries.

Comparative Protein Structure Modeling Using MODELLER.

PubMed

Webb, Benjamin; Sali, Andrej

2014-09-08

Functional characterization of a protein sequence is one of the most frequent problems in biology. This task is usually facilitated by accurate three-dimensional (3-D) structure of the studied protein. In the absence of an experimentally determined structure, comparative or homology modeling can sometimes provide a useful 3-D model for a protein that is related to at least one known protein structure. Comparative modeling predicts the 3-D structure of a given protein sequence (target) based primarily on its alignment to one or more proteins of known structure (templates). The prediction process consists of fold assignment, target-template alignment, model building, and model evaluation. This unit describes how to calculate comparative models using the program MODELLER and discusses all four steps of comparative modeling, frequently observed errors, and some applications. Modeling lactate dehydrogenase from Trichomonas vaginalis (TvLDH) is described as an example. The download and installation of the MODELLER software is also described. Copyright © 2014 John Wiley & Sons, Inc.

The Essential Role of Tethered Balloons in Characterizing Boundary Layer Structure and Evolution during Discover-AQ

NASA Astrophysics Data System (ADS)

Clark, R. D.

2014-12-01

The NASA DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) provided the opportunity to observe the influence of local and regional circulations on the structure and evolution of the boundary layer (BL) and in turn study the associated effects on air quality and aerosol trends within four different airsheds. An extended network of ground-based instruments, balloon-borne profilers, and remote sensing instruments supported the in-situ airborne measurements made by the NASA aircraft in capturing the structure and evolution of the daytime BL. The Millersville University Atmospheric Research and Aerostat Facility (MARAF) is one of many assets deployed for DISCOVER-AQ. Central to MARAF is a heavy-lift-capacity tethered balloon (aerostat) used to obtain high resolution profiles of meteorological variables, trace gases, and particulates in the BL. The benefit of including a tethered balloon is that it can fill a data void between the surface and the lowest altitudes flown by the aircraft and provide critical time-height series for ground-based remote sensing instruments in the layer below their first range gate. MARAF also includes an acoustic sodar with RASS, MPL4 micropulse Lidar, 4-meter flux tower, rawinsonde system, and a suite of trace gas analyzers (O3, NOx/NO2/NO, CO, and SO2), 3-wavelength nephelometer, and particle sizers/counters spanning the range from 10 nm to 10 microns. MARAF is capable of providing a detailed and nearly continuous Eulerian characterization of the surface layer and lower BL, and with proper FAA airspace authorization, can be deployed both day and night. Three case studies will be presented that incorporate the MARAF into the combined assets of DISCOVER-AQ to better characterize: 1) bay breeze convergence, recirculation, and ramp-up events in Edgewood, MD in July 2011; 2) aerosol transport over Central Valley, CA in January 2013; and 3) multiple sea-bay breeze

The SELGIFS data challenge: generating synthetic observations of CALIFA galaxies from hydrodynamical simulations

NASA Astrophysics Data System (ADS)

Guidi, G.; Casado, J.; Ascasibar, Y.; García-Benito, R.; Galbany, L.; Sánchez-Blázquez, P.; Sánchez, S. F.; Rosales-Ortega, F. F.; Scannapieco, C.

2018-06-01

In this work we present a set of synthetic observations that mimic the properties of the Integral Field Spectroscopy (IFS) survey CALIFA, generated using radiative transfer techniques applied to hydrodynamical simulations of galaxies in a cosmological context. The simulated spatially-resolved spectra include stellar and nebular emission, kinematic broadening of the lines, and dust extinction and scattering. The results of the radiative transfer simulations have been post-processed to reproduce the main properties of the CALIFA V500 and V1200 observational setups. The data has been further formatted to mimic the CALIFA survey in terms of field of view size, spectral range and sampling. We have included the effect of the spatial and spectral Point Spread Functions affecting CALIFA observations, and added detector noise after characterizing it on a sample of 367 galaxies. The simulated datacubes are suited to be analysed by the same algorithms used on real IFS data. In order to provide a benchmark to compare the results obtained applying IFS observational techniques to our synthetic datacubes, and test the calibration and accuracy of the analysis tools, we have computed the spatially-resolved properties of the simulations. Hence, we provide maps derived directly from the hydrodynamical snapshots or the noiseless spectra, in a way that is consistent with the values recovered by the observational analysis algorithms. Both the synthetic observations and the product datacubes are public and can be found in the collaboration website http://astro.ft.uam.es/selgifs/data_challenge/.

Temperature Influences the Production and Transport of Saxitoxin and the Expression of sxt Genes in the Cyanobacterium Aphanizomenon gracile

PubMed Central

Delgado, Adrián; González-Pleiter, Miguel

2017-01-01

The cyanobacterium Aphanizomenon gracile is the most widely distributed producer of the potent neurotoxin saxitoxin in freshwaters. In this work, total and extracellular saxitoxin and the transcriptional response of three genes linked to saxitoxin biosynthesis (sxtA) and transport (sxtM, sxtPer) were assessed in Aphanizomenon gracile UAM529 cultures under temperatures covering its annual cycle (12 °C, 23 °C, and 30 °C). Temperature influenced saxitoxin production being maximum at high temperatures (30 °C) above the growth optimum (23 °C), concurring with a 4.3-fold increased sxtA expression at 30 °C. Extracellular saxitoxin transport was temperature-dependent, with maxima at extremes of temperature (12 °C with 16.9% extracellular saxitoxin; and especially 30 °C with 53.8%) outside the growth optimum (23 °C), coinciding with a clear upregulation of sxtM at both 12 °C and 30 °C (3.8–4.1 fold respectively), and yet with just a slight upregulation of sxtPer at 30 °C (2.1-fold). Nitrate depletion also induced a high extracellular saxitoxin release (51.2%), although without variations of sxtM and sxtPer transcription, and showing evidence of membrane damage. This is the first study analysing the transcriptional response of sxtPer under environmental gradients, as well as the effect of temperature on putative saxitoxin transporters (sxtM and sxtPer) in cyanobacteria in general. PMID:29027918

Temperature Influences the Production and Transport of Saxitoxin and the Expression of sxt Genes in the Cyanobacterium Aphanizomenon gracile.

PubMed

Cirés, Samuel; Delgado, Adrián; González-Pleiter, Miguel; Quesada, Antonio

2017-10-13

The cyanobacterium Aphanizomenon gracile is the most widely distributed producer of the potent neurotoxin saxitoxin in freshwaters. In this work, total and extracellular saxitoxin and the transcriptional response of three genes linked to saxitoxin biosynthesis ( sxtA ) and transport ( sxtM , sxtPer ) were assessed in Aphanizomenon gracile UAM529 cultures under temperatures covering its annual cycle (12 °C, 23 °C, and 30 °C). Temperature influenced saxitoxin production being maximum at high temperatures (30 °C) above the growth optimum (23 °C), concurring with a 4.3-fold increased sxtA expression at 30 °C. Extracellular saxitoxin transport was temperature-dependent, with maxima at extremes of temperature (12 °C with 16.9% extracellular saxitoxin; and especially 30 °C with 53.8%) outside the growth optimum (23 °C), coinciding with a clear upregulation of sxtM at both 12 °C and 30 °C (3.8-4.1 fold respectively), and yet with just a slight upregulation of sxtPer at 30 °C (2.1-fold). Nitrate depletion also induced a high extracellular saxitoxin release (51.2%), although without variations of sxtM and sxtPer transcription, and showing evidence of membrane damage. This is the first study analysing the transcriptional response of sxtPer under environmental gradients, as well as the effect of temperature on putative saxitoxin transporters ( sxtM and sxtPer ) in cyanobacteria in general.

Geologic Framework Model Analysis Model Report

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

R. Clayton

2000-12-19

The purpose of this report is to document the Geologic Framework Model (GFM), Version 3.1 (GFM3.1) with regard to data input, modeling methods, assumptions, uncertainties, limitations, and validation of the model results, qualification status of the model, and the differences between Version 3.1 and previous versions. The GFM represents a three-dimensional interpretation of the stratigraphy and structural features of the location of the potential Yucca Mountain radioactive waste repository. The GFM encompasses an area of 65 square miles (170 square kilometers) and a volume of 185 cubic miles (771 cubic kilometers). The boundaries of the GFM were chosen to encompassmore » the most widely distributed set of exploratory boreholes (the Water Table or WT series) and to provide a geologic framework over the area of interest for hydrologic flow and radionuclide transport modeling through the unsaturated zone (UZ). The depth of the model is constrained by the inferred depth of the Tertiary-Paleozoic unconformity. The GFM was constructed from geologic map and borehole data. Additional information from measured stratigraphy sections, gravity profiles, and seismic profiles was also considered. This interim change notice (ICN) was prepared in accordance with the Technical Work Plan for the Integrated Site Model Process Model Report Revision 01 (CRWMS M&O 2000). The constraints, caveats, and limitations associated with this model are discussed in the appropriate text sections that follow. The GFM is one component of the Integrated Site Model (ISM) (Figure l), which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components: (1) Geologic Framework Model (GFM); (2) Rock Properties Model (RPM); and (3) Mineralogic Model (MM). The ISM merges the detailed project stratigraphy into model stratigraphic units that are most useful for the primary downstream models

Pre-Modeling Ensures Accurate Solid Models

ERIC Educational Resources Information Center

Gow, George

2010-01-01

Successful solid modeling requires a well-organized design tree. The design tree is a list of all the object's features and the sequential order in which they are modeled. The solid-modeling process is faster and less prone to modeling errors when the design tree is a simple and geometrically logical definition of the modeled object. Few high…

Frequentist Model Averaging in Structural Equation Modelling.

PubMed

Jin, Shaobo; Ankargren, Sebastian

2018-06-04

Model selection from a set of candidate models plays an important role in many structural equation modelling applications. However, traditional model selection methods introduce extra randomness that is not accounted for by post-model selection inference. In the current study, we propose a model averaging technique within the frequentist statistical framework. Instead of selecting an optimal model, the contributions of all candidate models are acknowledged. Valid confidence intervals and a [Formula: see text] test statistic are proposed. A simulation study shows that the proposed method is able to produce a robust mean-squared error, a better coverage probability, and a better goodness-of-fit test compared to model selection. It is an interesting compromise between model selection and the full model.

Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

PubMed

Hong, Sehee; Kim, Soyoung

2018-01-01

There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

Translating building information modeling to building energy modeling using model view definition.

PubMed

Jeong, WoonSeong; Kim, Jong Bum; Clayton, Mark J; Haberl, Jeff S; Yan, Wei

2014-01-01

This paper presents a new approach to translate between Building Information Modeling (BIM) and Building Energy Modeling (BEM) that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM) has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD) consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM) and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica) development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1) the BIM-based Modelica models generated from Revit2Modelica and (2) BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1) enables BIM models to be translated into ModelicaBEM models, (2) enables system interface development based on the MVD for thermal simulation, and (3) facilitates the reuse of original BIM data into building energy simulation without an import/export process.

Translating Building Information Modeling to Building Energy Modeling Using Model View Definition

PubMed Central

Kim, Jong Bum; Clayton, Mark J.; Haberl, Jeff S.

2014-01-01

This paper presents a new approach to translate between Building Information Modeling (BIM) and Building Energy Modeling (BEM) that uses Modelica, an object-oriented declarative, equation-based simulation environment. The approach (BIM2BEM) has been developed using a data modeling method to enable seamless model translations of building geometry, materials, and topology. Using data modeling, we created a Model View Definition (MVD) consisting of a process model and a class diagram. The process model demonstrates object-mapping between BIM and Modelica-based BEM (ModelicaBEM) and facilitates the definition of required information during model translations. The class diagram represents the information and object relationships to produce a class package intermediate between the BIM and BEM. The implementation of the intermediate class package enables system interface (Revit2Modelica) development for automatic BIM data translation into ModelicaBEM. In order to demonstrate and validate our approach, simulation result comparisons have been conducted via three test cases using (1) the BIM-based Modelica models generated from Revit2Modelica and (2) BEM models manually created using LBNL Modelica Buildings library. Our implementation shows that BIM2BEM (1) enables BIM models to be translated into ModelicaBEM models, (2) enables system interface development based on the MVD for thermal simulation, and (3) facilitates the reuse of original BIM data into building energy simulation without an import/export process. PMID:25309954

Models Archive and ModelWeb at NSSDC

NASA Astrophysics Data System (ADS)

Bilitza, D.; Papitashvili, N.; King, J. H.

2002-05-01

In addition to its large data holdings, NASA's National Space Science Data Center (NSSDC) also maintains an archive of space physics models for public use (ftp://nssdcftp.gsfc.nasa.gov/models/). The more than 60 model entries cover a wide range of parameters from the atmosphere, to the ionosphere, to the magnetosphere, to the heliosphere. The models are primarily empirical models developed by the respective model authors based on long data records from ground and space experiments. An online model catalog (http://nssdc.gsfc.nasa.gov/space/model/) provides information about these and other models and links to the model software if available. We will briefly review the existing model holdings and highlight some of its usages and users. In response to a growing need by the user community, NSSDC began to develop web-interfaces for the most frequently requested models. These interfaces enable users to compute and plot model parameters online for the specific conditions that they are interested in. Currently included in the Modelweb system (http://nssdc.gsfc.nasa.gov/space/model/) are the following models: the International Reference Ionosphere (IRI) model, the Mass Spectrometer Incoherent Scatter (MSIS) E90 model, the International Geomagnetic Reference Field (IGRF) and the AP/AE-8 models for the radiation belt electrons and protons. User accesses to both systems have been steadily increasing over the last years with occasional spikes prior to large scientific meetings. The current monthly rate is between 5,000 to 10,000 accesses for either system; in February 2002 13,872 accesses were recorded to the Modelsweb and 7092 accesses to the models archive.

Modeling uncertainty: quicksand for water temperature modeling

USGS Publications Warehouse

Bartholow, John M.

2003-01-01

Uncertainty has been a hot topic relative to science generally, and modeling specifically. Modeling uncertainty comes in various forms: measured data, limited model domain, model parameter estimation, model structure, sensitivity to inputs, modelers themselves, and users of the results. This paper will address important components of uncertainty in modeling water temperatures, and discuss several areas that need attention as the modeling community grapples with how to incorporate uncertainty into modeling without getting stuck in the quicksand that prevents constructive contributions to policy making. The material, and in particular the reference, are meant to supplement the presentation given at this conference.

Evolution of computational models in BioModels Database and the Physiome Model Repository.

PubMed

Scharm, Martin; Gebhardt, Tom; Touré, Vasundra; Bagnacani, Andrea; Salehzadeh-Yazdi, Ali; Wolkenhauer, Olaf; Waltemath, Dagmar

2018-04-12

A useful model is one that is being (re)used. The development of a successful model does not finish with its publication. During reuse, models are being modified, i.e. expanded, corrected, and refined. Even small changes in the encoding of a model can, however, significantly affect its interpretation. Our motivation for the present study is to identify changes in models and make them transparent and traceable. We analysed 13734 models from BioModels Database and the Physiome Model Repository. For each model, we studied the frequencies and types of updates between its first and latest release. To demonstrate the impact of changes, we explored the history of a Repressilator model in BioModels Database. We observed continuous updates in the majority of models. Surprisingly, even the early models are still being modified. We furthermore detected that many updates target annotations, which improves the information one can gain from models. To support the analysis of changes in model repositories we developed MoSt, an online tool for visualisations of changes in models. The scripts used to generate the data and figures for this study are available from GitHub https://github.com/binfalse/BiVeS-StatsGenerator and as a Docker image at https://hub.docker.com/r/binfalse/bives-statsgenerator/ . The website https://most.bio.informatik.uni-rostock.de/ provides interactive access to model versions and their evolutionary statistics. The reuse of models is still impeded by a lack of trust and documentation. A detailed and transparent documentation of all aspects of the model, including its provenance, will improve this situation. Knowledge about a model's provenance can avoid the repetition of mistakes that others already faced. More insights are gained into how the system evolves from initial findings to a profound understanding. We argue that it is the responsibility of the maintainers of model repositories to offer transparent model provenance to their users.

Integrity modelling of tropospheric delay models

NASA Astrophysics Data System (ADS)

Rózsa, Szabolcs; Bastiaan Ober, Pieter; Mile, Máté; Ambrus, Bence; Juni, Ildikó

2017-04-01

The effect of the neutral atmosphere on signal propagation is routinely estimated by various tropospheric delay models in satellite navigation. Although numerous studies can be found in the literature investigating the accuracy of these models, for safety-of-life applications it is crucial to study and model the worst case performance of these models using very low recurrence frequencies. The main objective of the INTegrity of TROpospheric models (INTRO) project funded by the ESA PECS programme is to establish a model (or models) of the residual error of existing tropospheric delay models for safety-of-life applications. Such models are required to overbound rare tropospheric delays and should thus include the tails of the error distributions. Their use should lead to safe error bounds on the user position and should allow computation of protection levels for the horizontal and vertical position errors. The current tropospheric model from the RTCA SBAS Minimal Operational Standards has an associated residual error that equals 0.12 meters in the vertical direction. This value is derived by simply extrapolating the observed distribution of the residuals into the tail (where no data is present) and then taking the point where the cumulative distribution has an exceedance level would be 10-7.While the resulting standard deviation is much higher than the estimated standard variance that best fits the data (0.05 meters), it surely is conservative for most applications. In the context of the INTRO project some widely used and newly developed tropospheric delay models (e.g. RTCA MOPS, ESA GALTROPO and GPT2W) were tested using 16 years of daily ERA-INTERIM Reanalysis numerical weather model data and the raytracing technique. The results showed that the performance of some of the widely applied models have a clear seasonal dependency and it is also affected by a geographical position. In order to provide a more realistic, but still conservative estimation of the residual

Model documentation report: Transportation sector model of the National Energy Modeling System

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

Not Available

1994-03-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Transportation Model (TRAN). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated by the model. This document serves three purposes. First, it is a reference document providing a detailed description of TRAN for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports (Public Law 93-275, 57(b)(1)). Third, it permits continuity inmore » model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.« less

Modeling complexes of modeled proteins.

PubMed

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Metabolic network modeling with model organisms.

PubMed

Yilmaz, L Safak; Walhout, Albertha Jm

2017-02-01

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. Published by Elsevier Ltd.

Metabolic network modeling with model organisms

PubMed Central

Yilmaz, L. Safak; Walhout, Albertha J.M.

2017-01-01

Flux balance analysis (FBA) with genome-scale metabolic network models (GSMNM) allows systems level predictions of metabolism in a variety of organisms. Different types of predictions with different accuracy levels can be made depending on the applied experimental constraints ranging from measurement of exchange fluxes to the integration of gene expression data. Metabolic network modeling with model organisms has pioneered method development in this field. In addition, model organism GSMNMs are useful for basic understanding of metabolism, and in the case of animal models, for the study of metabolic human diseases. Here, we discuss GSMNMs of most highly used model organisms with the emphasis on recent reconstructions. PMID:28088694

Modeling abundance using multinomial N-mixture models

USGS Publications Warehouse

Royle, Andy

2016-01-01

Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.

EasyModeller: A graphical interface to MODELLER

PubMed Central

2010-01-01

Background MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently. Findings The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way. Conclusion EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system. PMID:20712861

Model averaging techniques for quantifying conceptual model uncertainty.

PubMed

Singh, Abhishek; Mishra, Srikanta; Ruskauff, Greg

2010-01-01

In recent years a growing understanding has emerged regarding the need to expand the modeling paradigm to include conceptual model uncertainty for groundwater models. Conceptual model uncertainty is typically addressed by formulating alternative model conceptualizations and assessing their relative likelihoods using statistical model averaging approaches. Several model averaging techniques and likelihood measures have been proposed in the recent literature for this purpose with two broad categories--Monte Carlo-based techniques such as Generalized Likelihood Uncertainty Estimation or GLUE (Beven and Binley 1992) and criterion-based techniques that use metrics such as the Bayesian and Kashyap Information Criteria (e.g., the Maximum Likelihood Bayesian Model Averaging or MLBMA approach proposed by Neuman 2003) and Akaike Information Criterion-based model averaging (AICMA) (Poeter and Anderson 2005). These different techniques can often lead to significantly different relative model weights and ranks because of differences in the underlying statistical assumptions about the nature of model uncertainty. This paper provides a comparative assessment of the four model averaging techniques (GLUE, MLBMA with KIC, MLBMA with BIC, and AIC-based model averaging) mentioned above for the purpose of quantifying the impacts of model uncertainty on groundwater model predictions. Pros and cons of each model averaging technique are examined from a practitioner's perspective using two groundwater modeling case studies. Recommendations are provided regarding the use of these techniques in groundwater modeling practice.

Model compilation: An approach to automated model derivation

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Baudin, Catherine; Iwasaki, Yumi; Nayak, Pandurang; Tanaka, Kazuo

1990-01-01

An approach is introduced to automated model derivation for knowledge based systems. The approach, model compilation, involves procedurally generating the set of domain models used by a knowledge based system. With an implemented example, how this approach can be used to derive models of different precision and abstraction is illustrated, and models are tailored to different tasks, from a given set of base domain models. In particular, two implemented model compilers are described, each of which takes as input a base model that describes the structure and behavior of a simple electromechanical device, the Reaction Wheel Assembly of NASA's Hubble Space Telescope. The compilers transform this relatively general base model into simple task specific models for troubleshooting and redesign, respectively, by applying a sequence of model transformations. Each transformation in this sequence produces an increasingly more specialized model. The compilation approach lessens the burden of updating and maintaining consistency among models by enabling their automatic regeneration.

Radiation Environment Modeling for Spacecraft Design: New Model Developments

NASA Technical Reports Server (NTRS)

Barth, Janet; Xapsos, Mike; Lauenstein, Jean-Marie; Ladbury, Ray

2006-01-01

A viewgraph presentation on various new space radiation environment models for spacecraft design is described. The topics include: 1) The Space Radiatio Environment; 2) Effects of Space Environments on Systems; 3) Space Radiatio Environment Model Use During Space Mission Development and Operations; 4) Space Radiation Hazards for Humans; 5) "Standard" Space Radiation Environment Models; 6) Concerns about Standard Models; 7) Inadequacies of Current Models; 8) Development of New Models; 9) New Model Developments: Proton Belt Models; 10) Coverage of New Proton Models; 11) Comparison of TPM-1, PSB97, AP-8; 12) New Model Developments: Electron Belt Models; 13) Coverage of New Electron Models; 14) Comparison of "Worst Case" POLE, CRESELE, and FLUMIC Models with the AE-8 Model; 15) New Model Developments: Galactic Cosmic Ray Model; 16) Comparison of NASA, MSU, CIT Models with ACE Instrument Data; 17) New Model Developmemts: Solar Proton Model; 18) Comparison of ESP, JPL91, KIng/Stassinopoulos, and PSYCHIC Models; 19) New Model Developments: Solar Heavy Ion Model; 20) Comparison of CREME96 to CREDO Measurements During 2000 and 2002; 21) PSYCHIC Heavy ion Model; 22) Model Standardization; 23) Working Group Meeting on New Standard Radiation Belt and Space Plasma Models; and 24) Summary.

Using Moss to Detect Fine-Scaled Deposition of Heavy Metals in Urban Environments

NASA Astrophysics Data System (ADS)

Jovan, S.; Donovan, G.; Demetrios, G.; Monleon, V. J.; Amacher, M. C.

2017-12-01

Mosses are commonly used as bio-indicators of heavy metal deposition to forests. Their application in urban airsheds is relatively rare. Our objective was to develop fine-scaled, city-wide maps for heavy metals in Portland, Oregon, to identify pollution "hotspots" and serve as a screening tool for more effective placement of air quality monitoring instruments. In 2013 we measured twenty-two elements in epiphytic moss sampled on a 1km x1km sampling grid (n = 346). We detected large hotspots of cadmium and arsenic in two neighborhoods associated with stained glass manufacturers. Air instruments deployed by local regulators measured cadmium concentrations 49 times and arsenic levels 155 times the state health benchmarks. Moss maps also detected a large nickel hotspot in a neighborhood near a forge where air instruments later measured concentrations 4 times the health benchmark. In response, the facilities implemented new pollution controls, air quality improved in all three affected neighborhoods, revision of regulations for stained glass furnace emissions are underway, and Oregon's governor launched an initiative to develop health-based (vs technology-based) regulations for air toxics in the state. The moss maps also indicated a couple dozen smaller hotspots of heavy metals, including lead, chromium, and cobalt, in Portland neighborhoods. Ongoing follow-up work includes: 1) use of moss sampling by local regulators to investigate source and extent of the smaller hotspots, 2) use of lead isotopes to determine origins of higher lead levels observed in moss collected from the inner city, and 3) co-location of air instruments and moss sampling to determine accuracy, timeframe represented, and seasonality of heavy metals in moss.

A satellite view of the sources and interannual variability of free tropospheric PAN over the eastern Pacific Ocean during summer and its timeline for trend detection

NASA Astrophysics Data System (ADS)

Zhu, L.; Fischer, E. V.; Payne, V.; Walker, T. W.; Worden, J. R.; Jiang, Z.; Kulawik, S. S.

2016-12-01

Peroxyacetyl nitrate (PAN) is the most important reservoir for nitrogen oxide radicals (NOx = NO + NO2) in the troposphere and plays a significant role in the redistribution of NOx to remote regions. There is strong evidence that PAN decomposition in specific plumes of Asian origin subsiding over the eastern Pacific Ocean can lead to significant ozone (O3) enhancements in the troposphere. Thus quantifying the spatial and temporal variability of PAN over the eastern Pacific Ocean is an important part of understanding the O3 budget upwind of the North American airshed. Here we present observations of PAN from the Tropospheric Emission Spectrometer (TES) over the eastern Pacific for July 2006-2010. We focus our analysis on July because prior work based on in situ observations has primarily addressed the transpacific transport of PAN in spring. Plumes containing elevated PAN are present almost every day in the month of July, and we show that elevated PAN observed in July has multiple sources, including fires in Siberia, anthropogenic and lightning sources in eastern China, and re-circulated pollution from the continental U.S. We provide examples of each type of source using both HYPLIT trajectories and a GEOS-Chem adjoint sensitivity analysis. Based on the variability observed in the TES PAN retrievals over this region, we predict it would be faster to detect a trend of a given magnitude in PAN using satellite observations over the eastern Pacific Ocean region rather than surface in situ observations at one site, and that a trend of a given magnitude would be more quickly detected in summer than spring.

Atmospheric mercury and fine particulate matter in coastal New England: implications for mercury and trace element sources in the northeastern United States

USGS Publications Warehouse

Kolker, Allan; Engle, Mark A.; Peucker-Ehrenbrink, Bernhard; Geboy, Nicholas J.; Krabbenhotft, David P.; Bothner, Michael H.; Tate, Michael T.

2013-01-01

Intensive sampling of ambient atmospheric fine particulate matter was conducted at Woods Hole, Massachusetts over a four-month period from 3 April to 29 July, 2008, in conjunction with year-long deployment of the USGS Mobile Mercury Lab. Results were obtained for trace elements in fine particulate matter concurrently with determination of ambient atmospheric mercury speciation and concentrations of ancillary gasses (SO2, NOx, and O3). For particulate matter, trace element enrichment factors greater than 10 relative to crustal background values were found for As, Bi, Cd, Cu, Hg, Pb, Sb, V, and Zn, indicating contribution of these elements by anthropogenic sources. For other elements, enrichments are consistent with natural marine (Na, Ca, Mg, Sr) or crustal (Ba, Ce, Co, Cs, Fe, Ga, La, Rb, Sc, Th, Ti, U, Y) sources, respectively. Positive matrix factorization was used together with concentration weighted air-mass back trajectories to better define element sources and their locations. Our analysis, based on events exhibiting the 10% highest PM2.5 contributions for each source category, identifies coal-fired power stations concentrated in the U.S. Ohio Valley, metal smelting in eastern Canada, and marine and crustal sources showing surprisingly similar back trajectories, at times each sampling Atlantic coastal airsheds. This pattern is consistent with contribution of Saharan dust by a summer maximum at the latitude of Florida and northward transport up the Atlantic Coast by clockwise circulation of the summer Bermuda High. Results for mercury speciation show diurnal production of RGM by photochemical oxidation of Hg° in a marine environment, and periodic traverse of the study area by correlated RGM-SO2(NOx) plumes, indicative of coal combustion sources.

High Precision, Absolute Total Column Ozone Measurements from the Pandora Spectrometer System: Comparisons with Data from a Brewer Double Monochromator and Aura OMI

NASA Technical Reports Server (NTRS)

Tzortziou, Maria A.; Herman, Jay R.; Cede, Alexander; Abuhassan, Nader

2012-01-01

We present new, high precision, high temporal resolution measurements of total column ozone (TCO) amounts derived from ground-based direct-sun irradiance measurements using our recently deployed Pandora single-grating spectrometers. Pandora's small size and portability allow deployment at multiple sites within an urban air-shed and development of a ground-based monitoring network for studying small-scale atmospheric dynamics, spatial heterogeneities in trace gas distribution, local pollution conditions, photochemical processes and interdependencies of ozone and its major precursors. Results are shown for four mid- to high-latitude sites where different Pandora instruments were used. Comparisons with a well calibrated double-grating Brewer spectrometer over a period of more than a year in Greenbelt MD showed excellent agreement and a small bias of approximately 2 DU (or, 0.6%). This was constant with slant column ozone amount over the full range of observed solar zenith angles (15-80), indicating adequate Pandora stray light correction. A small (1-2%) seasonal difference was found, consistent with sensitivity studies showing that the Pandora spectral fitting TCO retrieval has a temperature dependence of 1% per 3K, with an underestimation in temperature (e.g., during summer) resulting in an underestimation of TCO. Pandora agreed well with Aura-OMI (Ozone Measuring Instrument) satellite data, with average residuals of <1% at the different sites when the OMI view was within 50 km from the Pandora location and OMI-measured cloud fraction was <0.2. The frequent and continuous measurements by Pandora revealed significant short-term (hourly) temporal changes in TCO, not possible to capture by sun-synchronous satellites, such as OMI, alone.

Leadership Models.

ERIC Educational Resources Information Center

Freeman, Thomas J.

This paper discusses six different models of organizational structure and leadership, including the scalar chain or pyramid model, the continuum model, the grid model, the linking pin model, the contingency model, and the circle or democratic model. Each model is examined in a separate section that describes the model and its development, lists…

Building mental models by dissecting physical models.

PubMed

Srivastava, Anveshna

2016-01-01

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "model-dissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic time-efficiency of "model dissection," suggest that it could be a valuable pedagogical tool. © 2015 The International Union of Biochemistry and Molecular Biology.

Better models are more effectively connected models

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Bielders, Charles; Darboux, Frederic; Fiener, Peter; Finger, David; Turnbull-Lloyd, Laura; Wainwright, John

2016-04-01

The concept of hydrologic and geomorphologic connectivity describes the processes and pathways which link sources (e.g. rainfall, snow and ice melt, springs, eroded areas and barren lands) to accumulation areas (e.g. foot slopes, streams, aquifers, reservoirs), and the spatial variations thereof. There are many examples of hydrological and sediment connectivity on a watershed scale; in consequence, a process-based understanding of connectivity is crucial to help managers understand their systems and adopt adequate measures for flood prevention, pollution mitigation and soil protection, among others. Modelling is often used as a tool to understand and predict fluxes within a catchment by complementing observations with model results. Catchment models should therefore be able to reproduce the linkages, and thus the connectivity of water and sediment fluxes within the systems under simulation. In modelling, a high level of spatial and temporal detail is desirable to ensure taking into account a maximum number of components, which then enables connectivity to emerge from the simulated structures and functions. However, computational constraints and, in many cases, lack of data prevent the representation of all relevant processes and spatial/temporal variability in most models. In most cases, therefore, the level of detail selected for modelling is too coarse to represent the system in a way in which connectivity can emerge; a problem which can be circumvented by representing fine-scale structures and processes within coarser scale models using a variety of approaches. This poster focuses on the results of ongoing discussions on modelling connectivity held during several workshops within COST Action Connecteur. It assesses the current state of the art of incorporating the concept of connectivity in hydrological and sediment models, as well as the attitudes of modellers towards this issue. The discussion will focus on the different approaches through which connectivity

Constructive Epistemic Modeling: A Hierarchical Bayesian Model Averaging Method

NASA Astrophysics Data System (ADS)

Tsai, F. T. C.; Elshall, A. S.

2014-12-01

Constructive epistemic modeling is the idea that our understanding of a natural system through a scientific model is a mental construct that continually develops through learning about and from the model. Using the hierarchical Bayesian model averaging (HBMA) method [1], this study shows that segregating different uncertain model components through a BMA tree of posterior model probabilities, model prediction, within-model variance, between-model variance and total model variance serves as a learning tool [2]. First, the BMA tree of posterior model probabilities permits the comparative evaluation of the candidate propositions of each uncertain model component. Second, systemic model dissection is imperative for understanding the individual contribution of each uncertain model component to the model prediction and variance. Third, the hierarchical representation of the between-model variance facilitates the prioritization of the contribution of each uncertain model component to the overall model uncertainty. We illustrate these concepts using the groundwater modeling of a siliciclastic aquifer-fault system. The sources of uncertainty considered are from geological architecture, formation dip, boundary conditions and model parameters. The study shows that the HBMA analysis helps in advancing knowledge about the model rather than forcing the model to fit a particularly understanding or merely averaging several candidate models. [1] Tsai, F. T.-C., and A. S. Elshall (2013), Hierarchical Bayesian model averaging for hydrostratigraphic modeling: Uncertainty segregation and comparative evaluation. Water Resources Research, 49, 5520-5536, doi:10.1002/wrcr.20428. [2] Elshall, A.S., and F. T.-C. Tsai (2014). Constructive epistemic modeling of groundwater flow with geological architecture and boundary condition uncertainty under Bayesian paradigm, Journal of Hydrology, 517, 105-119, doi: 10.1016/j.jhydrol.2014.05.027.

SUMMA and Model Mimicry: Understanding Differences Among Land Models

NASA Astrophysics Data System (ADS)

Nijssen, B.; Nearing, G. S.; Ou, G.; Clark, M. P.

2016-12-01

Model inter-comparison and model ensemble experiments suffer from an inability to explain the mechanisms behind differences in model outcomes. We can clearly demonstrate that the models are different, but we cannot necessarily identify the reasons why, because most models exhibit myriad differences in process representations, model parameterizations, model parameters and numerical solution methods. This inability to identify the reasons for differences in model performance hampers our understanding and limits model improvement, because we cannot easily identify the most promising paths forward. We have developed the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to allow for controlled experimentation with model construction, numerical techniques, and parameter values and therefore isolate differences in model outcomes to specific choices during the model development process. In developing SUMMA, we recognized that hydrologic models can be thought of as individual instantiations of a master modeling template that is based on a common set of conservation equations for energy and water. Given this perspective, SUMMA provides a unified approach to hydrologic modeling that integrates different modeling methods into a consistent structure with the ability to instantiate alternative hydrologic models at runtime. Here we employ SUMMA to revisit a previous multi-model experiment and demonstrate its use for understanding differences in model performance. Specifically, we implement SUMMA to mimic the spread of behaviors exhibited by the land models that participated in the Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) and draw conclusions about the relative performance of specific model parameterizations for water and energy fluxes through the soil-vegetation continuum. SUMMA's ability to mimic the spread of model ensembles and the behavior of individual models can be an important tool in

When smoke comes to town - effects of biomass burning smoke on air quality down under

NASA Astrophysics Data System (ADS)

Keywood, Melita; Cope, Martin; (C. P) Meyer, Mick; Iinuma, Yoshi; Emmerson, Kathryn

2014-05-01

Annually, biomass burning results in the emission of quantities of trace gases and aerosol to the atmosphere. Biomass burning emissions have a significant effect on atmospheric chemistry due to the presence of reactive species. Biomass burning aerosols influence the radiative balance of the earth-atmosphere system directly through the scattering and absorption of radiation, and indirectly through their influence on cloud microphysical processes, and therefore constitute an important forcing in climate models. They also reduce visibility, influence atmospheric photochemistry and can be inhaled into the deepest parts of the lungs, so that they can have a significant effect on human health. Australia experiences bushfires on an annual basis. In most years fires are restricted to the tropical savannah forests of Northern Australia. However in the summer of 2006/2007 (December 2006 - February 2007), South Eastern Australia was affected by the longest recorded fires in its history. During this time the State of Victoria was ravaged by 690 separate bushfires, including the major Great Divide Fire, which devastated 1,048,238 hectares over 69 days. On several occasions, thick smoke haze was transported to the Melbourne central business district and PM10 concentrations at several air quality monitoring stations peaked at over 200 µg m-3 (four times the National Environment Protection Measure PM10 24 hour standard). During this period, a comprehensive suite of air quality measurements was carried out at a location 25 km south of the Melbourne CBD, including detailed aerosol microphysical and chemical composition measurements. Here we examine the chemical and physical properties of the smoke plume as it impacted Melbourne's air shed and discuss its impact on air quality over the city. We estimate the aerosol emission rates of the source fires, the age of the plumes and investigate the transformation of the smoke as it progressed from its source to the Melbourne airshed. We

Modeller's attitude in catchment modelling: a comparative study

NASA Astrophysics Data System (ADS)

Battista Chirico, Giovanni

2010-05-01

Ten modellers have been invited to predict, independently from each other, the discharge of the artificial Chicken Creek catchment in North-East Germany for simulation period of three years, providing them only soil texture, terrain and meteorological data. No data concerning the discharge or other sources of state variables and fluxes within the catchment have been provided. Modellers had however the opportunity to visit the experimental catchment and inspect areal photos of the catchments since its initial development stage. This study has been a unique comparative study focussing on how different modellers deal with the key issues in predicting the discharge in ungauged catchments: 1) choice of the model structure; 2) identification of model parameters; 3) identification of model initial and boundary conditions. The first general lesson learned during this study was that the modeller is just part of the entire modelling process and has a major bearing on the model results, particularly in ungauged catchments where there are more degrees of freedom in making modelling decisions. Modellers' attitudes during the stages of the model implementation and parameterisation have been deeply influenced by their own experience from previous modelling studies. A common outcome was that modellers have been mainly oriented to apply process-based models able to exploit the available data concerning the physical properties of the catchment and therefore could be more suitable to cope with the lack of data concerning state variables or fluxes. The second general lesson learned during this study was the role of dominant processes. We believed that the modelling task would have been much easier in an artificial catchment, where heterogeneity were expected to be negligible and processes simpler, than in catchments that have evolved over a longer time period. The results of the models were expected to converge, and this would have been a good starting point to proceed for a model

Model selection for logistic regression models

NASA Astrophysics Data System (ADS)

Duller, Christine

2012-09-01

Model selection for logistic regression models decides which of some given potential regressors have an effect and hence should be included in the final model. The second interesting question is whether a certain factor is heterogeneous among some subsets, i.e. whether the model should include a random intercept or not. In this paper these questions will be answered with classical as well as with Bayesian methods. The application show some results of recent research projects in medicine and business administration.

Building Mental Models by Dissecting Physical Models

ERIC Educational Resources Information Center

Srivastava, Anveshna

2016-01-01

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to…

Multiscale musculoskeletal modelling, data–model fusion and electromyography-informed modelling

PubMed Central

Zhang, J.; Heidlauf, T.; Sartori, M.; Besier, T.; Röhrle, O.; Lloyd, D.

2016-01-01

This paper proposes methods and technologies that advance the state of the art for modelling the musculoskeletal system across the spatial and temporal scales; and storing these using efficient ontologies and tools. We present population-based modelling as an efficient method to rapidly generate individual morphology from only a few measurements and to learn from the ever-increasing supply of imaging data available. We present multiscale methods for continuum muscle and bone models; and efficient mechanostatistical methods, both continuum and particle-based, to bridge the scales. Finally, we examine both the importance that muscles play in bone remodelling stimuli and the latest muscle force prediction methods that use electromyography-assisted modelling techniques to compute musculoskeletal forces that best reflect the underlying neuromuscular activity. Our proposal is that, in order to have a clinically relevant virtual physiological human, (i) bone and muscle mechanics must be considered together; (ii) models should be trained on population data to permit rapid generation and use underlying principal modes that describe both muscle patterns and morphology; and (iii) these tools need to be available in an open-source repository so that the scientific community may use, personalize and contribute to the database of models. PMID:27051510

Gradient-based model calibration with proxy-model assistance

NASA Astrophysics Data System (ADS)

Burrows, Wesley; Doherty, John

2016-02-01

Use of a proxy model in gradient-based calibration and uncertainty analysis of a complex groundwater model with large run times and problematic numerical behaviour is described. The methodology is general, and can be used with models of all types. The proxy model is based on a series of analytical functions that link all model outputs used in the calibration process to all parameters requiring estimation. In enforcing history-matching constraints during the calibration and post-calibration uncertainty analysis processes, the proxy model is run for the purposes of populating the Jacobian matrix, while the original model is run when testing parameter upgrades; the latter process is readily parallelized. Use of a proxy model in this fashion dramatically reduces the computational burden of complex model calibration and uncertainty analysis. At the same time, the effect of model numerical misbehaviour on calculation of local gradients is mitigated, this allowing access to the benefits of gradient-based analysis where lack of integrity in finite-difference derivatives calculation would otherwise have impeded such access. Construction of a proxy model, and its subsequent use in calibration of a complex model, and in analysing the uncertainties of predictions made by that model, is implemented in the PEST suite.

Modelling, teachers' views on the nature of modelling, and implications for the education of modellers

NASA Astrophysics Data System (ADS)

Justi, Rosária S.; Gilbert, John K.

2002-04-01

In this paper, the role of modelling in the teaching and learning of science is reviewed. In order to represent what is entailed in modelling, a 'model of modelling' framework is proposed. Five phases in moving towards a full capability in modelling are established by a review of the literature: learning models; learning to use models; learning how to revise models; learning to reconstruct models; learning to construct models de novo. In order to identify the knowledge and skills that science teachers think are needed to produce a model successfully, a semi-structured interview study was conducted with 39 Brazilian serving science teachers: 10 teaching at the 'fundamental' level (6-14 years); 10 teaching at the 'medium'-level (15-17 years); 10 undergraduate pre-service 'medium'-level teachers; 9 university teachers of chemistry. Their responses are used to establish what is entailed in implementing the 'model of modelling' framework. The implications for students, teachers, and for teacher education, of moving through the five phases of capability, are discussed.

Measurement of the Isotopic Signature of Soil Carbon Dioxide: Methods Development and Initial Field Results

NASA Astrophysics Data System (ADS)

Kayler, Z.; Rugh, W.; Mix, A. C.; Bond, B. J.; Sulzman, E. W.

2005-12-01

Soil respiration is a significant component of ecosystem respiration and its isotopic composition is likely to lend insight into ecosystem processes. We have designed probes to determine the isotopic signature of soil-respired CO2 using a two end-member mixing model approach (i.e., Keeling plot). Each probe consists of three 35 ml PVC chambers cased in fiberglass mesh and connected to the soil surface via stainless steel tubing with a septa-lined swagelok fitting. Chambers are vertically connected such that they sample gases at depth intervals centered on 5, 15, and 30 cm. Gases are sampled via a hand vacuum pump equipped with a two-way valve, which allows vials pre-filled with N2 gas in the laboratory to be evacuated and re-filled with only a single septa puncture in the field. Data indicate samples can be stored reliably for up to three days if punctured septa are coated in silicone sealant. To test whether this field sampling method was robust, we constructed a carbon-free sand column out of PVC pipe into which we plumbed a tank of known CO2 concentration and isotopic composition. We have tested the effects of wetting and flow rate on our ability to reproduce tank values. A linear model (geometric mean regression) yielded a more negative isotopic value than the actual gas, but a simple polynomial curve fit the tank value. After laboratory testing, the probes were established in a steep drainage in the H.J. Andrews LTER site in the Cascade Mountains of western Oregon (as part of the Andrews Airshed project). We established a transect of five 10 m2 plots with four soil probes and a companion respiration collar and measured soil CO2 efflux and soil δ13CO2 values biweekly from June-Sept. Results indicate there is a clear difference in isotopic and respiration flux patterns between the north- and south-facing slopes, with the north facing slope exhibiting higher fluxes and more 13C enriched respiration. The temporal pattern of respiration correlates well with

NARSTO critical review of photochemical models and modeling

NASA Astrophysics Data System (ADS)

Russell, Armistead; Dennis, Robin

Photochemical air quality models play a central role in both schentific investigation of how pollutants evlove in the atmosphere as well as developing policies to manage air quality. In the past 30 years, these models have evolved from rather crude representations of the physics and chemistry impacting trace species to their current state: comprehensive, but not complete. The evolution has included advancements in not only the level of process descriptions, but also the computational implementation, including numerical methods. As part of the NARSTO Critical Reviews, this article discusses the current strengths and weaknesses of air quality models and the modeling process. Current Eulerian models are found to represent well the primary processes impacting the evolution of trace species in most cases though some exceptions may exist. For example, sub-grid-scale processes, such as concentrated power plant plumes, are treated only approximately. It is not apparent how much such approximations affect their results and the polices based upon those results. A significant weakness has been in how investigators have addressed, and communicated, such uncertainties. Studies find that major uncertainties are due to model inputs, e.g., emissions and meteorology, more so than the model itself. One of the primary weakness identified is in the modeling process, not the models. Evaluation has been limited both due to data constraints. Seldom is there ample observational data to conduct a detailed model intercomparison using consistent data (e.g., the same emissions and meteorology). Further model advancement, and development of greater confidence in the use of models, is hampered by the lack of thorough evaluation and intercomparisons. Model advances are seen in the use of new tools for extending the interpretation of model results, e.g., process and sensitivity analysis, modeling systems to facilitate their use, and extension of model capabilities, e.g., aerosol dynamics

Coupling Climate Models and Forward-Looking Economic Models

NASA Astrophysics Data System (ADS)

Judd, K.; Brock, W. A.

2010-12-01

Authors: Dr. Kenneth L. Judd, Hoover Institution, and Prof. William A. Brock, University of Wisconsin Current climate models range from General Circulation Models (GCM’s) with millions of degrees of freedom to models with few degrees of freedom. Simple Energy Balance Climate Models (EBCM’s) help us understand the dynamics of GCM’s. The same is true in economics with Computable General Equilibrium Models (CGE’s) where some models are infinite-dimensional multidimensional differential equations but some are simple models. Nordhaus (2007, 2010) couples a simple EBCM with a simple economic model. One- and two- dimensional ECBM’s do better at approximating damages across the globe and positive and negative feedbacks from anthroprogenic forcing (North etal. (1981), Wu and North (2007)). A proper coupling of climate and economic systems is crucial for arriving at effective policies. Brock and Xepapadeas (2010) have used Fourier/Legendre based expansions to study the shape of socially optimal carbon taxes over time at the planetary level in the face of damages caused by polar ice cap melt (as discussed by Oppenheimer, 2005) but in only a “one dimensional” EBCM. Economists have used orthogonal polynomial expansions to solve dynamic, forward-looking economic models (Judd, 1992, 1998). This presentation will couple EBCM climate models with basic forward-looking economic models, and examine the effectiveness and scaling properties of alternative solution methods. We will use a two dimensional EBCM model on the sphere (Wu and North, 2007) and a multicountry, multisector regional model of the economic system. Our aim will be to gain insights into intertemporal shape of the optimal carbon tax schedule, and its impact on global food production, as modeled by Golub and Hertel (2009). We will initially have limited computing resources and will need to focus on highly aggregated models. However, this will be more complex than existing models with forward

EIA model documentation: Petroleum Market Model of the National Energy Modeling System

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

NONE

1994-12-30

The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. Documentation of the model is in accordance with EIA`s legal obligation to provide adequate documentation in support of its models (Public Law 94-385, section 57.b.2). The PMM models petroleum refining activities, the marketing of products, the production of natural gas liquids and domestic methanol, projects petroleum provides and sources of supplies for meeting demand. In addition, the PMMmore » estimates domestic refinery capacity expansion and fuel consumption.« less

The Impact of TexAQS 2000 on Air Quality Planning in Houston

NASA Astrophysics Data System (ADS)

Thomas, J. W.; Price, J. H.

2002-12-01

Before the Texas 2000 Air Quality Study (TexAQS 2000) the State used the Urban Airshed Model to model nine different episodes in Houston with very poor results: only one episode met EPA model performance criteria. Questions existed regarding emissions uncertainties, meteorological modeling, and model chemistry. NOAA, DOE, and SOS led more than 35 organizations and 250 investigators who participated in TexAQS 2000. Major findings from TexAQS 2000 are: 1. There are two types of meteorological patterns that lead to ozone episodes in the Houston area: (i) stagnation associated with the sea breeze flow reversal causes a pool of industrial emissions and ozone to accumulate, then to move across the city as the wind flow picks up and (ii) plumes of ozone form when relatively persistent winds carry the emissions away from the city and industrial areas. 2. The chemistry that produces high ozone concentrations and rapid rises in ozone in the Houston area has been explained: multiple investigators in TexAQS 2000 have documented more rapid and more efficient formation of ozone in the plume from the Houston industrial area than any of them has observed in any previous field study. Houston's exceptionally rapid ozone formation arises from large amounts of anthropogenic VOCs in the atmosphere, often from the same plants that provide sufficient NOx. 3. This rapid and efficient ozone formation results most often from the presence of a specific subclass of hydrocarbons called light olefins, primarily ethylene and propylene. 4. Sometimes it is other specific hydrocarbons that cause the rapid formation of high concentrations of ozone, and sometimes it is just the total mass of a lot of relatively unreactive hydrocarbons. 5. The current emissions inventory for ethylene and propylene, as well as other VOCs, underestimates their routine emissions by a factor of roughly five to ten or perhaps even more. 6. It is not clear whether the emissions causing Houston's rapid ozone formation are

Advances in Geoscience Modeling: Smart Modeling Frameworks, Self-Describing Models and the Role of Standardized Metadata

NASA Astrophysics Data System (ADS)

Peckham, Scott

2016-04-01

Over the last decade, model coupling frameworks like CSDMS (Community Surface Dynamics Modeling System) and ESMF (Earth System Modeling Framework) have developed mechanisms that make it much easier for modelers to connect heterogeneous sets of process models in a plug-and-play manner to create composite "system models". These mechanisms greatly simplify code reuse, but must simultaneously satisfy many different design criteria. They must be able to mediate or compensate for differences between the process models, such as their different programming languages, computational grids, time-stepping schemes, variable names and variable units. However, they must achieve this interoperability in a way that: (1) is noninvasive, requiring only relatively small and isolated changes to the original source code, (2) does not significantly reduce performance, (3) is not time-consuming or confusing for a model developer to implement, (4) can very easily be updated to accommodate new versions of a given process model and (5) does not shift the burden of providing model interoperability to the model developers. In tackling these design challenges, model framework developers have learned that the best solution is to provide each model with a simple, standardized interface, i.e. a set of standardized functions that make the model: (1) fully-controllable by a caller (e.g. a model framework) and (2) self-describing with standardized metadata. Model control functions are separate functions that allow a caller to initialize the model, advance the model's state variables in time and finalize the model. Model description functions allow a caller to retrieve detailed information on the model's input and output variables, its computational grid and its timestepping scheme. If the caller is a modeling framework, it can use the self description functions to learn about each process model in a collection to be coupled and then automatically call framework service components (e.g. regridders

Modeling Methods

USGS Publications Warehouse

Healy, Richard W.; Scanlon, Bridget R.

2010-01-01

Simulation models are widely used in all types of hydrologic studies, and many of these models can be used to estimate recharge. Models can provide important insight into the functioning of hydrologic systems by identifying factors that influence recharge. The predictive capability of models can be used to evaluate how changes in climate, water use, land use, and other factors may affect recharge rates. Most hydrological simulation models, including watershed models and groundwater-flow models, are based on some form of water-budget equation, so the material in this chapter is closely linked to that in Chapter 2. Empirical models that are not based on a water-budget equation have also been used for estimating recharge; these models generally take the form of simple estimation equations that define annual recharge as a function of precipitation and possibly other climatic data or watershed characteristics.Model complexity varies greatly. Some models are simple accounting models; others attempt to accurately represent the physics of water movement through each compartment of the hydrologic system. Some models provide estimates of recharge explicitly; for example, a model based on the Richards equation can simulate water movement from the soil surface through the unsaturated zone to the water table. Recharge estimates can be obtained indirectly from other models. For example, recharge is a parameter in groundwater-flow models that solve for hydraulic head (i.e. groundwater level). Recharge estimates can be obtained through a model calibration process in which recharge and other model parameter values are adjusted so that simulated water levels agree with measured water levels. The simulation that provides the closest agreement is called the best fit, and the recharge value used in that simulation is the model-generated estimate of recharge.

Models for Models: An Introduction to Polymer Models Employing Simple Analogies

NASA Astrophysics Data System (ADS)

Tarazona, M. Pilar; Saiz, Enrique

1998-11-01

An introduction to the most common models used in the calculations of conformational properties of polymers, ranging from the freely jointed chain approximation to Monte Carlo or molecular dynamics methods, is presented. Mathematical formalism is avoided and simple analogies, such as human chains, gases, opinion polls, or marketing strategies, are used to explain the different models presented. A second goal of the paper is to teach students how models required for the interpretation of a system can be elaborated, starting with the simplest model and introducing successive improvements until the refinements become so sophisticated that it is much better to use an alternative approach.

Hybrid Model of IRT and Latent Class Models.

ERIC Educational Resources Information Center

Yamamoto, Kentaro

This study developed a hybrid of item response theory (IRT) models and latent class models, which combined the strengths of each type of model. The primary motivation for developing the new model is to describe characteristics of examinees' knowledge at the time of the examination. Hence, the application of the model lies mainly in so-called…

New 3D model for dynamics modeling

NASA Astrophysics Data System (ADS)

Perez, Alain

1994-05-01

The wrist articulation represents one of the most complex mechanical systems of the human body. It is composed of eight bones rolling and sliding along their surface and along the faces of the five metacarpals of the hand and the two bones of the arm. The wrist dynamics are however fundamental for the hand movement, but it is so complex that it still remains incompletely explored. This work is a part of a new concept of computer-assisted surgery, which consists in developing computer models to perfect surgery acts by predicting their consequences. The modeling of the wrist dynamics are based first on the static model of its bones in three dimensions. This 3D model must optimise the collision detection procedure which is the necessary step to estimate the physical contact constraints. As many other possible computer vision models do not fit with enough precision to this problem, a new 3D model has been developed thanks to the median axis of the digital distance map of the bones reconstructed volume. The collision detection procedure is then simplified for contacts are detected between spheres. The experiment of this original 3D dynamic model products realistic computer animation images of solids in contact. It is now necessary to detect ligaments on digital medical images and to model them in order to complete a wrist model.

Bayesian model evidence as a model evaluation metric

NASA Astrophysics Data System (ADS)

Guthke, Anneli; Höge, Marvin; Nowak, Wolfgang

2017-04-01

When building environmental systems models, we are typically confronted with the questions of how to choose an appropriate model (i.e., which processes to include or neglect) and how to measure its quality. Various metrics have been proposed that shall guide the modeller towards a most robust and realistic representation of the system under study. Criteria for evaluation often address aspects of accuracy (absence of bias) or of precision (absence of unnecessary variance) and need to be combined in a meaningful way in order to address the inherent bias-variance dilemma. We suggest using Bayesian model evidence (BME) as a model evaluation metric that implicitly performs a tradeoff between bias and variance. BME is typically associated with model weights in the context of Bayesian model averaging (BMA). However, it can also be seen as a model evaluation metric in a single-model context or in model comparison. It combines a measure for goodness of fit with a penalty for unjustifiable complexity. Unjustifiable refers to the fact that the appropriate level of model complexity is limited by the amount of information available for calibration. Derived in a Bayesian context, BME naturally accounts for measurement errors in the calibration data as well as for input and parameter uncertainty. BME is therefore perfectly suitable to assess model quality under uncertainty. We will explain in detail and with schematic illustrations what BME measures, i.e. how complexity is defined in the Bayesian setting and how this complexity is balanced with goodness of fit. We will further discuss how BME compares to other model evaluation metrics that address accuracy and precision such as the predictive logscore or other model selection criteria such as the AIC, BIC or KIC. Although computationally more expensive than other metrics or criteria, BME represents an appealing alternative because it provides a global measure of model quality. Even if not applicable to each and every case, we aim

Integrative structure modeling with the Integrative Modeling Platform.

PubMed

Webb, Benjamin; Viswanath, Shruthi; Bonomi, Massimiliano; Pellarin, Riccardo; Greenberg, Charles H; Saltzberg, Daniel; Sali, Andrej

2018-01-01

Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use. © 2017 The Protein Society.

Modeling volatility using state space models.

PubMed

Timmer, J; Weigend, A S

1997-08-01

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict their time evolution adequately, we estimate state space models that explicitly include observational noise. We obtain relaxation times for shocks in the logarithm of volatility ranging from three weeks (for foreign exchange) to three to five months (for stock indices). In most cases, a two-dimensional hidden state is required to yield residuals that are consistent with white noise. We compare these results with ordinary autoregressive models (without a hidden state) and find that autoregressive models underestimate the relaxation times by about two orders of magnitude since they do not distinguish between observational and dynamic noise. This new interpretation of the dynamics of volatility in terms of relaxators in a state space model carries over to stochastic volatility models and to GARCH models, and is useful for several problems in finance, including risk management and the pricing of derivative securities. Data sets used: Olsen & Associates high frequency DEM/USD foreign exchange rates (8 years). Nikkei 225 index (40 years). Dow Jones Industrial Average (25 years).

Bayesian Data-Model Fit Assessment for Structural Equation Modeling

ERIC Educational Resources Information Center

Levy, Roy

2011-01-01

Bayesian approaches to modeling are receiving an increasing amount of attention in the areas of model construction and estimation in factor analysis, structural equation modeling (SEM), and related latent variable models. However, model diagnostics and model criticism remain relatively understudied aspects of Bayesian SEM. This article describes…

Downscaling GISS ModelE Boreal Summer Climate over Africa

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.; Fulakeza, Matthew

2015-01-01

The study examines the perceived added value of downscaling atmosphere-ocean global climate model simulations over Africa and adjacent oceans by a nested regional climate model. NASA/Goddard Institute for Space Studies (GISS) coupled ModelE simulations for June- September 1998-2002 are used to form lateral boundary conditions for synchronous simulations by the GISS RM3 regional climate model. The ModelE computational grid spacing is 2deg latitude by 2.5deg longitude and the RM3 grid spacing is 0.44deg. ModelE precipitation climatology for June-September 1998-2002 is shown to be a good proxy for 30-year means so results based on the 5-year sample are presumed to be generally representative. Comparison with observational evidence shows several discrepancies in ModelE configuration of the boreal summer inter-tropical convergence zone (ITCZ). One glaring shortcoming is that ModelE simulations do not advance the West African rain band northward during the summer to represent monsoon precipitation onset over the Sahel. Results for 1998-2002 show that onset simulation is an important added value produced by downscaling with RM3. ModelE Eastern South Atlantic Ocean computed sea-surface temperatures (SST) are some 4 K warmer than reanalysis, contributing to large positive biases in overlying surface air temperatures (Tsfc). ModelE Tsfc are also too warm over most of Africa. RM3 downscaling somewhat mitigates the magnitude of Tsfc biases over the African continent, it eliminates the ModelE double ITCZ over the Atlantic and it produces more realistic orographic precipitation maxima. Parallel ModelE and RM3 simulations with observed SST forcing (in place of the predicted ocean) lower Tsfc errors but have mixed impacts on circulation and precipitation biases. Downscaling improvements of the meridional movement of the rain band over West Africa and the configuration of orographic precipitation maxima are realized irrespective of the SST biases.

An online model composition tool for system biology models

PubMed Central

2013-01-01

Background There are multiple representation formats for Systems Biology computational models, and the Systems Biology Markup Language (SBML) is one of the most widely used. SBML is used to capture, store, and distribute computational models by Systems Biology data sources (e.g., the BioModels Database) and researchers. Therefore, there is a need for all-in-one web-based solutions that support advance SBML functionalities such as uploading, editing, composing, visualizing, simulating, querying, and browsing computational models. Results We present the design and implementation of the Model Composition Tool (Interface) within the PathCase-SB (PathCase Systems Biology) web portal. The tool helps users compose systems biology models to facilitate the complex process of merging systems biology models. We also present three tools that support the model composition tool, namely, (1) Model Simulation Interface that generates a visual plot of the simulation according to user’s input, (2) iModel Tool as a platform for users to upload their own models to compose, and (3) SimCom Tool that provides a side by side comparison of models being composed in the same pathway. Finally, we provide a web site that hosts BioModels Database models and a separate web site that hosts SBML Test Suite models. Conclusions Model composition tool (and the other three tools) can be used with little or no knowledge of the SBML document structure. For this reason, students or anyone who wants to learn about systems biology will benefit from the described functionalities. SBML Test Suite models will be a nice starting point for beginners. And, for more advanced purposes, users will able to access and employ models of the BioModels Database as well. PMID:24006914

ModelMate - A graphical user interface for model analysis

USGS Publications Warehouse

Banta, Edward R.

2011-01-01

ModelMate is a graphical user interface designed to facilitate use of model-analysis programs with models. This initial version of ModelMate supports one model-analysis program, UCODE_2005, and one model software program, MODFLOW-2005. ModelMate can be used to prepare input files for UCODE_2005, run UCODE_2005, and display analysis results. A link to the GW_Chart graphing program facilitates visual interpretation of results. ModelMate includes capabilities for organizing directories used with the parallel-processing capabilities of UCODE_2005 and for maintaining files in those directories to be identical to a set of files in a master directory. ModelMate can be used on its own or in conjunction with ModelMuse, a graphical user interface for MODFLOW-2005 and PHAST.

Mineralogic Model (MM3.0) Analysis Model Report

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

C. Lum

2002-02-12

The purpose of this report is to document the Mineralogic Model (MM), Version 3.0 (MM3.0) with regard to data input, modeling methods, assumptions, uncertainties, limitations and validation of the model results, qualification status of the model, and the differences between Version 3.0 and previous versions. A three-dimensional (3-D) Mineralogic Model was developed for Yucca Mountain to support the analyses of hydrologic properties, radionuclide transport, mineral health hazards, repository performance, and repository design. Version 3.0 of the MM was developed from mineralogic data obtained from borehole samples. It consists of matrix mineral abundances as a function of x (easting), y (northing),more » and z (elevation), referenced to the stratigraphic framework defined in Version 3.1 of the Geologic Framework Model (GFM). The MM was developed specifically for incorporation into the 3-D Integrated Site Model (ISM). The MM enables project personnel to obtain calculated mineral abundances at any position, within any region, or within any stratigraphic unit in the model area. The significance of the MM for key aspects of site characterization and performance assessment is explained in the following subsections. This work was conducted in accordance with the Development Plan for the MM (CRWMS M&O 2000). The planning document for this Rev. 00, ICN 02 of this AMR is Technical Work Plan, TWP-NBS-GS-000003, Technical Work Plan for the Integrated Site Model, Process Model Report, Revision 01 (CRWMS M&O 2000). The purpose of this ICN is to record changes in the classification of input status by the resolution of the use of TBV software and data in this report. Constraints and limitations of the MM are discussed in the appropriate sections that follow. The MM is one component of the ISM, which has been developed to provide a consistent volumetric portrayal of the rock layers, rock properties, and mineralogy of the Yucca Mountain site. The ISM consists of three components

Simplified subsurface modelling: data assimilation and violated model assumptions

NASA Astrophysics Data System (ADS)

Erdal, Daniel; Lange, Natascha; Neuweiler, Insa

2017-04-01

Integrated models are gaining more and more attention in hydrological modelling as they can better represent the interaction between different compartments. Naturally, these models come along with larger numbers of unknowns and requirements on computational resources compared to stand-alone models. If large model domains are to be represented, e.g. on catchment scale, the resolution of the numerical grid needs to be reduced or the model itself needs to be simplified. Both approaches lead to a reduced ability to reproduce the present processes. This lack of model accuracy may be compensated by using data assimilation methods. In these methods observations are used to update the model states, and optionally model parameters as well, in order to reduce the model error induced by the imposed simplifications. What is unclear is whether these methods combined with strongly simplified models result in completely data-driven models or if they can even be used to make adequate predictions of the model state for times when no observations are available. In the current work we consider the combined groundwater and unsaturated zone, which can be modelled in a physically consistent way using 3D-models solving the Richards equation. For use in simple predictions, however, simpler approaches may be considered. The question investigated here is whether a simpler model, in which the groundwater is modelled as a horizontal 2D-model and the unsaturated zones as a few sparse 1D-columns, can be used within an Ensemble Kalman filter to give predictions of groundwater levels and unsaturated fluxes. This is tested under conditions where the feedback between the two model-compartments are large (e.g. shallow groundwater table) and the simplification assumptions are clearly violated. Such a case may be a steep hill-slope or pumping wells, creating lateral fluxes in the unsaturated zone, or strong heterogeneous structures creating unaccounted flows in both the saturated and unsaturated

BATMAN: Bayesian Technique for Multi-image Analysis

NASA Astrophysics Data System (ADS)

Casado, J.; Ascasibar, Y.; García-Benito, R.; Guidi, G.; Choudhury, O. S.; Bellocchi, E.; Sánchez, S. F.; Díaz, A. I.

2017-04-01

This paper describes the Bayesian Technique for Multi-image Analysis (BATMAN), a novel image-segmentation technique based on Bayesian statistics that characterizes any astronomical data set containing spatial information and performs a tessellation based on the measurements and errors provided as input. The algorithm iteratively merges spatial elements as long as they are statistically consistent with carrying the same information (I.e. identical signal within the errors). We illustrate its operation and performance with a set of test cases including both synthetic and real integral-field spectroscopic data. The output segmentations adapt to the underlying spatial structure, regardless of its morphology and/or the statistical properties of the noise. The quality of the recovered signal represents an improvement with respect to the input, especially in regions with low signal-to-noise ratio. However, the algorithm may be sensitive to small-scale random fluctuations, and its performance in presence of spatial gradients is limited. Due to these effects, errors may be underestimated by as much as a factor of 2. Our analysis reveals that the algorithm prioritizes conservation of all the statistically significant information over noise reduction, and that the precise choice of the input data has a crucial impact on the results. Hence, the philosophy of BaTMAn is not to be used as a 'black box' to improve the signal-to-noise ratio, but as a new approach to characterize spatially resolved data prior to its analysis. The source code is publicly available at http://astro.ft.uam.es/SELGIFS/BaTMAn.

Development of an unbiased, semi-automated approach for classifying plasma cell immunophenotype following multicolor flow cytometry of bone marrow aspirates.

PubMed

Post, Steven R; Post, Ginell R; Nikolic, Dejan; Owens, Rebecca; Insuasti-Beltran, Giovanni

2018-03-24

Despite increased usage of multiparameter flow cytometry (MFC) to assess diagnosis, prognosis, and therapeutic efficacy (minimal residual disease, MRD) in plasma cell neoplasms (PCNs), standardization of methodology and data analysis is suboptimal. We investigated the utility of using the mean and median fluorescence intensities (FI) obtained from MFC to objectively describe parameters that distinguish plasma cell (PC) phenotypes. In this retrospective study, flow cytometry results from bone marrow aspirate specimens from 570 patients referred to the Myeloma Institute at UAMS were evaluated. Mean and median FI data were obtained from 8-color MFC of non-neoplastic, malignant, and mixed PC populations using antibodies to CD38, CD138, CD19, CD20, CD27, CD45, CD56, and CD81. Of 570 cases, 252 cases showed only non-neoplastic PCs, 168 showed only malignant PCs, and 150 showed mixed PC populations. Statistical analysis of median FI data for each CD marker showed no difference in expression intensity on non-neoplastic and malignant PCs, between pure and mixed PC populations. ROC analysis of the median FI of CD expression in non-neoplastic and malignant PCs was used to develop an algorithm to convert quantitative FI values to qualitative assessments including "negative," "positive," "dim," and "heterogeneous" expression. FI data derived from 8-color MFC can be used to define marker expression on PCs. Translation of FI data from Infinicyt software to an Excel worksheet streamlines workflow and eliminates transcriptional errors when generating flow reports. © 2018 International Clinical Cytometry Society. © 2018 International Clinical Cytometry Society.

The immunoprofile of odontogenic keratocyst (keratocystic odontogenic tumor) that includes expression of PTCH, SMO, GLI-1 and bcl-2 is similar to ameloblastoma but different from odontogenic cysts.

PubMed

Vered, M; Peleg, O; Taicher, S; Buchner, A

2009-08-01

The aggressive biological behavior of odontogenic keratocysts (OKCs), unlike that of other odontogenic cysts, has argued for its recent re-classification as a neoplasm, 'keratocystic odontogenic tumor'. Identification of mutations in the PTCH gene in some of the OKCs that were expected to produce truncated proteins, resulting in loss of control of the cell cycle, provided additional support for OKCs having a neoplastic nature. We investigated the immunohistochemical expression of the sonic hedgehog (SHH) signaling pathway-related proteins, PTCH, smoothened (SMO) and GLI-1, and of the SHH-induced bcl-2 oncoprotein in a series of primary OKC (pOKC), recurrent OKC (rOKC) and nevoid basal cell carcinoma syndrome-associated OKCs (NBCCS-OKCs), and compared them to solid ameloblastomas (SAMs), unicystic ameloblastomas (UAMs), 'orthokeratinized' OKCs (oOKCs), dentigerous cysts (DCs) and radicular cysts (RCs). All studied lesions expressed the SHH pathway-related proteins in a similar pattern. The expression of bcl-2 in OKCs (pOKCs and NBCCS-OKCs) and SAMs was significantly higher than in oOKCs, DCs and RCs (P < 0.001). The present results of the immunoprofile of OKCs (that includes the expression of the SHH-related proteins and the SHH-induced bcl-2 oncoprotein) further support the notion of OKC having a neoplastic nature. As OKCs vary considerably in their biologic behavior, it is suggested that the quality and quantity of interactions between the SHH and other cell cycle regulatory pathways are likely to work synergistically to define the individual phenotype and corresponding biological behavior of this lesion.

Non-target adjacent stimuli classification improves performance of classical ERP-based brain computer interface

NASA Astrophysics Data System (ADS)

Ceballos, G. A.; Hernández, L. F.

2015-04-01

Objective. The classical ERP-based speller, or P300 Speller, is one of the most commonly used paradigms in the field of Brain Computer Interfaces (BCI). Several alterations to the visual stimuli presentation system have been developed to avoid unfavorable effects elicited by adjacent stimuli. However, there has been little, if any, regard to useful information contained in responses to adjacent stimuli about spatial location of target symbols. This paper aims to demonstrate that combining the classification of non-target adjacent stimuli with standard classification (target versus non-target) significantly improves classical ERP-based speller efficiency. Approach. Four SWLDA classifiers were trained and combined with the standard classifier: the lower row, upper row, right column and left column classifiers. This new feature extraction procedure and the classification method were carried out on three open databases: the UAM P300 database (Universidad Autonoma Metropolitana, Mexico), BCI competition II (dataset IIb) and BCI competition III (dataset II). Main results. The inclusion of the classification of non-target adjacent stimuli improves target classification in the classical row/column paradigm. A gain in mean single trial classification of 9.6% and an overall improvement of 25% in simulated spelling speed was achieved. Significance. We have provided further evidence that the ERPs produced by adjacent stimuli present discriminable features, which could provide additional information about the spatial location of intended symbols. This work promotes the searching of information on the peripheral stimulation responses to improve the performance of emerging visual ERP-based spellers.

ERM model analysis for adaptation to hydrological model errors

NASA Astrophysics Data System (ADS)

Baymani-Nezhad, M.; Han, D.

2018-05-01

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Embedded Model Error Representation and Propagation in Climate Models

NASA Astrophysics Data System (ADS)

Sargsyan, K.; Ricciuto, D. M.; Safta, C.; Thornton, P. E.

2017-12-01

Over the last decade, parametric uncertainty quantification (UQ) methods have reached a level of maturity, while the same can not be said about representation and quantification of structural or model errors. Lack of characterization of model errors, induced by physical assumptions, phenomenological parameterizations or constitutive laws, is a major handicap in predictive science. In particular, e.g. in climate models, significant computational resources are dedicated to model calibration without gaining improvement in predictive skill. Neglecting model errors during calibration/tuning will lead to overconfident and biased model parameters. At the same time, the most advanced methods accounting for model error merely correct output biases, augmenting model outputs with statistical error terms that can potentially violate physical laws, or make the calibrated model ineffective for extrapolative scenarios. This work will overview a principled path for representing and quantifying model errors, as well as propagating them together with the rest of the predictive uncertainty budget, including data noise, parametric uncertainties and surrogate-related errors. Namely, the model error terms will be embedded in select model components rather than as external corrections. Such embedding ensures consistency with physical constraints on model predictions, and renders calibrated model predictions meaningful and robust with respect to model errors. Besides, in the presence of observational data, the approach can effectively differentiate model structural deficiencies from those of data acquisition. The methodology is implemented in UQ Toolkit (www.sandia.gov/uqtoolkit), relying on a host of available forward and inverse UQ tools. We will demonstrate the application of the technique on few application of interest, including ACME Land Model calibration via a wide range of measurements obtained at select sites.

TUNS/TCIS information model/process model

NASA Technical Reports Server (NTRS)

Wilson, James

1992-01-01

An Information Model is comprised of graphical and textual notation suitable for describing and defining the problem domain - in our case, TUNS or TCIS. The model focuses on the real world under study. It identifies what is in the problem and organizes the data into a formal structure for documentation and communication purposes. The Information Model is composed of an Entity Relationship Diagram (ERD) and a Data Dictionary component. The combination of these components provide an easy to understand methodology for expressing the entities in the problem space, the relationships between entities and the characteristics (attributes) of the entities. This approach is the first step in information system development. The Information Model identifies the complete set of data elements processed by TUNS. This representation provides a conceptual view of TUNS from the perspective of entities, data, and relationships. The Information Model reflects the business practices and real-world entities that users must deal with.

Modelling human skull growth: a validated computational model

PubMed Central

Marghoub, Arsalan; Johnson, David; Khonsari, Roman H.; Fagan, Michael J.; Moazen, Mehran

2017-01-01

During the first year of life, the brain grows rapidly and the neurocranium increases to about 65% of its adult size. Our understanding of the relationship between the biomechanical forces, especially from the growing brain, the craniofacial soft tissue structures and the individual bone plates of the skull vault is still limited. This basic knowledge could help in the future planning of craniofacial surgical operations. The aim of this study was to develop a validated computational model of skull growth, based on the finite-element (FE) method, to help understand the biomechanics of skull growth. To do this, a two-step validation study was carried out. First, an in vitro physical three-dimensional printed model and an in silico FE model were created from the same micro-CT scan of an infant skull and loaded with forces from the growing brain from zero to two months of age. The results from the in vitro model validated the FE model before it was further developed to expand from 0 to 12 months of age. This second FE model was compared directly with in vivo clinical CT scans of infants without craniofacial conditions (n = 56). The various models were compared in terms of predicted skull width, length and circumference, while the overall shape was quantified using three-dimensional distance plots. Statistical analysis yielded no significant differences between the male skull models. All size measurements from the FE model versus the in vitro physical model were within 5%, with one exception showing a 7.6% difference. The FE model and in vivo data also correlated well, with the largest percentage difference in size being 8.3%. Overall, the FE model results matched well with both the in vitro and in vivo data. With further development and model refinement, this modelling method could be used to assist in preoperative planning of craniofacial surgery procedures and could help to reduce reoperation rates. PMID:28566514

Modelling human skull growth: a validated computational model.

PubMed

Libby, Joseph; Marghoub, Arsalan; Johnson, David; Khonsari, Roman H; Fagan, Michael J; Moazen, Mehran

2017-05-01

During the first year of life, the brain grows rapidly and the neurocranium increases to about 65% of its adult size. Our understanding of the relationship between the biomechanical forces, especially from the growing brain, the craniofacial soft tissue structures and the individual bone plates of the skull vault is still limited. This basic knowledge could help in the future planning of craniofacial surgical operations. The aim of this study was to develop a validated computational model of skull growth, based on the finite-element (FE) method, to help understand the biomechanics of skull growth. To do this, a two-step validation study was carried out. First, an in vitro physical three-dimensional printed model and an in silico FE model were created from the same micro-CT scan of an infant skull and loaded with forces from the growing brain from zero to two months of age. The results from the in vitro model validated the FE model before it was further developed to expand from 0 to 12 months of age. This second FE model was compared directly with in vivo clinical CT scans of infants without craniofacial conditions ( n = 56). The various models were compared in terms of predicted skull width, length and circumference, while the overall shape was quantified using three-dimensional distance plots. Statistical analysis yielded no significant differences between the male skull models. All size measurements from the FE model versus the in vitro physical model were within 5%, with one exception showing a 7.6% difference. The FE model and in vivo data also correlated well, with the largest percentage difference in size being 8.3%. Overall, the FE model results matched well with both the in vitro and in vivo data. With further development and model refinement, this modelling method could be used to assist in preoperative planning of craniofacial surgery procedures and could help to reduce reoperation rates. © 2017 The Author(s).

A Model-Model and Data-Model Comparison for the Early Eocene Hydrological Cycle

NASA Technical Reports Server (NTRS)

Carmichael, Matthew J.; Lunt, Daniel J.; Huber, Matthew; Heinemann, Malte; Kiehl, Jeffrey; LeGrande, Allegra; Loptson, Claire A.; Roberts, Chris D.; Sagoo, Navjit; Shields, Christine

2016-01-01

A range of proxy observations have recently provided constraints on how Earth's hydrological cycle responded to early Eocene climatic changes. However, comparisons of proxy data to general circulation model (GCM) simulated hydrology are limited and inter-model variability remains poorly characterised. In this work, we undertake an intercomparison of GCM-derived precipitation and P - E distributions within the extended EoMIP ensemble (Eocene Modelling Intercomparison Project; Lunt et al., 2012), which includes previously published early Eocene simulations performed using five GCMs differing in boundary conditions, model structure, and precipitation-relevant parameterisation schemes. We show that an intensified hydrological cycle, manifested in enhanced global precipitation and evaporation rates, is simulated for all Eocene simulations relative to the preindustrial conditions. This is primarily due to elevated atmospheric paleo-CO2, resulting in elevated temperatures, although the effects of differences in paleogeography and ice sheets are also important in some models. For a given CO2 level, globally averaged precipitation rates vary widely between models, largely arising from different simulated surface air temperatures. Models with a similar global sensitivity of precipitation rate to temperature (dP=dT ) display different regional precipitation responses for a given temperature change. Regions that are particularly sensitive to model choice include the South Pacific, tropical Africa, and the Peri-Tethys, which may represent targets for future proxy acquisition. A comparison of early and middle Eocene leaf-fossil-derived precipitation estimates with the GCM output illustrates that GCMs generally underestimate precipitation rates at high latitudes, although a possible seasonal bias of the proxies cannot be excluded. Models which warm these regions, either via elevated CO2 or by varying poorly constrained model parameter values, are most successful in simulating a

A Distributed Snow Evolution Modeling System (SnowModel)

NASA Astrophysics Data System (ADS)

Liston, G. E.; Elder, K.

2004-12-01

A spatially distributed snow-evolution modeling system (SnowModel) has been specifically designed to be applicable over a wide range of snow landscapes, climates, and conditions. To reach this goal, SnowModel is composed of four sub-models: MicroMet defines the meteorological forcing conditions, EnBal calculates surface energy exchanges, SnowMass simulates snow depth and water-equivalent evolution, and SnowTran-3D accounts for snow redistribution by wind. While other distributed snow models exist, SnowModel is unique in that it includes a well-tested blowing-snow sub-model (SnowTran-3D) for application in windy arctic, alpine, and prairie environments where snowdrifts are common. These environments comprise 68% of the seasonally snow-covered Northern Hemisphere land surface. SnowModel also accounts for snow processes occurring in forested environments (e.g., canopy interception related processes). SnowModel is designed to simulate snow-related physical processes occurring at spatial scales of 5-m and greater, and temporal scales of 1-hour and greater. These include: accumulation from precipitation; wind redistribution and sublimation; loading, unloading, and sublimation within forest canopies; snow-density evolution; and snowpack ripening and melt. To enhance its wide applicability, SnowModel includes the physical calculations required to simulate snow evolution within each of the global snow classes defined by Sturm et al. (1995), e.g., tundra, taiga, alpine, prairie, maritime, and ephemeral snow covers. The three, 25-km by 25-km, Cold Land Processes Experiment (CLPX) mesoscale study areas (MSAs: Fraser, North Park, and Rabbit Ears) are used as SnowModel simulation examples to highlight model strengths, weaknesses, and features in forested, semi-forested, alpine, and shrubland environments.

Implementing multiresolution models and families of models: from entity-level simulation to desktop stochastic models and "repro" models

NASA Astrophysics Data System (ADS)

McEver, Jimmie; Davis, Paul K.; Bigelow, James H.

2000-06-01

We have developed and used families of multiresolution and multiple-perspective models (MRM and MRMPM), both in our substantive analytic work for the Department of Defense and to learn more about how such models can be designed and implemented. This paper is a brief case history of our experience with a particular family of models addressing the use of precision fires in interdicting and halting an invading army. Our models were implemented as closed-form analytic solutions, in spreadsheets, and in the more sophisticated AnalyticaTM environment. We also drew on an entity-level simulation for data. The paper reviews the importance of certain key attributes of development environments (visual modeling, interactive languages, friendly use of array mathematics, facilities for experimental design and configuration control, statistical analysis tools, graphical visualization tools, interactive post-processing, and relational database tools). These can go a long way towards facilitating MRMPM work, but many of these attributes are not yet widely available (or available at all) in commercial model-development tools--especially for use with personal computers. We conclude with some lessons learned from our experience.

The Relationships Between Modelling and Argumentation from the Perspective of the Model of Modelling Diagram

NASA Astrophysics Data System (ADS)

Cardoso Mendonça, Paula Cristina; Justi, Rosária

2013-09-01

Some studies related to the nature of scientific knowledge demonstrate that modelling is an inherently argumentative process. This study aims at discussing the relationship between modelling and argumentation by analysing data collected during the modelling-based teaching of ionic bonding and intermolecular interactions. The teaching activities were planned from the transposition of the main modelling stages that constitute the 'Model of Modelling Diagram' so that students could experience each of such stages. All the lessons were video recorded and their transcriptions supported the elaboration of case studies for each group of students. From the analysis of the case studies, we identified argumentative situations when students performed all of the modelling stages. Our data show that the argumentative situations were related to sense making, articulating and persuasion purposes, and were closely related to the generation of explanations in the modelling processes. They also show that representations are important resources for argumentation. Our results are consistent with some of those already reported in the literature regarding the relationship between modelling and argumentation, but are also divergent when they show that argumentation is not only related to the model evaluation phase.

Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration

NASA Astrophysics Data System (ADS)

Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.

2017-12-01

Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.

`Models of' versus `Models for'. Toward an Agent-Based Conception of Modeling in the Science Classroom

NASA Astrophysics Data System (ADS)

Gouvea, Julia; Passmore, Cynthia

2017-03-01

The inclusion of the practice of "developing and using models" in the Framework for K-12 Science Education and in the Next Generation Science Standards provides an opportunity for educators to examine the role this practice plays in science and how it can be leveraged in a science classroom. Drawing on conceptions of models in the philosophy of science, we bring forward an agent-based account of models and discuss the implications of this view for enacting modeling in science classrooms. Models, according to this account, can only be understood with respect to the aims and intentions of a cognitive agent (models for), not solely in terms of how they represent phenomena in the world (models of). We present this contrast as a heuristic— models of versus models for—that can be used to help educators notice and interpret how models are positioned in standards, curriculum, and classrooms.

A Model for Math Modeling

ERIC Educational Resources Information Center

Lin, Tony; Erfan, Sasan

2016-01-01

Mathematical modeling is an open-ended research subject where no definite answers exist for any problem. Math modeling enables thinking outside the box to connect different fields of studies together including statistics, algebra, calculus, matrices, programming and scientific writing. As an integral part of society, it is the foundation for many…

Model fit evaluation in multilevel structural equation models

PubMed Central

Ryu, Ehri

2014-01-01

Assessing goodness of model fit is one of the key questions in structural equation modeling (SEM). Goodness of fit is the extent to which the hypothesized model reproduces the multivariate structure underlying the set of variables. During the earlier development of multilevel structural equation models, the “standard” approach was to evaluate the goodness of fit for the entire model across all levels simultaneously. The model fit statistics produced by the standard approach have a potential problem in detecting lack of fit in the higher-level model for which the effective sample size is much smaller. Also when the standard approach results in poor model fit, it is not clear at which level the model does not fit well. This article reviews two alternative approaches that have been proposed to overcome the limitations of the standard approach. One is a two-step procedure which first produces estimates of saturated covariance matrices at each level and then performs single-level analysis at each level with the estimated covariance matrices as input (Yuan and Bentler, 2007). The other level-specific approach utilizes partially saturated models to obtain test statistics and fit indices for each level separately (Ryu and West, 2009). Simulation studies (e.g., Yuan and Bentler, 2007; Ryu and West, 2009) have consistently shown that both alternative approaches performed well in detecting lack of fit at any level, whereas the standard approach failed to detect lack of fit at the higher level. It is recommended that the alternative approaches are used to assess the model fit in multilevel structural equation model. Advantages and disadvantages of the two alternative approaches are discussed. The alternative approaches are demonstrated in an empirical example. PMID:24550882

Using the Model Coupling Toolkit to couple earth system models

USGS Publications Warehouse

Warner, J.C.; Perlin, N.; Skyllingstad, E.D.

2008-01-01

Continued advances in computational resources are providing the opportunity to operate more sophisticated numerical models. Additionally, there is an increasing demand for multidisciplinary studies that include interactions between different physical processes. Therefore there is a strong desire to develop coupled modeling systems that utilize existing models and allow efficient data exchange and model control. The basic system would entail model "1" running on "M" processors and model "2" running on "N" processors, with efficient exchange of model fields at predetermined synchronization intervals. Here we demonstrate two coupled systems: the coupling of the ocean circulation model Regional Ocean Modeling System (ROMS) to the surface wave model Simulating WAves Nearshore (SWAN), and the coupling of ROMS to the atmospheric model Coupled Ocean Atmosphere Prediction System (COAMPS). Both coupled systems use the Model Coupling Toolkit (MCT) as a mechanism for operation control and inter-model distributed memory transfer of model variables. In this paper we describe requirements and other options for model coupling, explain the MCT library, ROMS, SWAN and COAMPS models, methods for grid decomposition and sparse matrix interpolation, and provide an example from each coupled system. Methods presented in this paper are clearly applicable for coupling of other types of models. ?? 2008 Elsevier Ltd. All rights reserved.

Modeling Non-Gaussian Time Series with Nonparametric Bayesian Model.

PubMed

Xu, Zhiguang; MacEachern, Steven; Xu, Xinyi

2015-02-01

We present a class of Bayesian copula models whose major components are the marginal (limiting) distribution of a stationary time series and the internal dynamics of the series. We argue that these are the two features with which an analyst is typically most familiar, and hence that these are natural components with which to work. For the marginal distribution, we use a nonparametric Bayesian prior distribution along with a cdf-inverse cdf transformation to obtain large support. For the internal dynamics, we rely on the traditionally successful techniques of normal-theory time series. Coupling the two components gives us a family of (Gaussian) copula transformed autoregressive models. The models provide coherent adjustments of time scales and are compatible with many extensions, including changes in volatility of the series. We describe basic properties of the models, show their ability to recover non-Gaussian marginal distributions, and use a GARCH modification of the basic model to analyze stock index return series. The models are found to provide better fit and improved short-range and long-range predictions than Gaussian competitors. The models are extensible to a large variety of fields, including continuous time models, spatial models, models for multiple series, models driven by external covariate streams, and non-stationary models.

The Real and the Mathematical in Quantum Modeling: From Principles to Models and from Models to Principles

NASA Astrophysics Data System (ADS)

Plotnitsky, Arkady

2017-06-01

The history of mathematical modeling outside physics has been dominated by the use of classical mathematical models, C-models, primarily those of a probabilistic or statistical nature. More recently, however, quantum mathematical models, Q-models, based in the mathematical formalism of quantum theory have become more prominent in psychology, economics, and decision science. The use of Q-models in these fields remains controversial, in part because it is not entirely clear whether Q-models are necessary for dealing with the phenomena in question or whether C-models would still suffice. My aim, however, is not to assess the necessity of Q-models in these fields, but instead to reflect on what the possible applicability of Q-models may tell us about the corresponding phenomena there, vis-à-vis quantum phenomena in physics. In order to do so, I shall first discuss the key reasons for the use of Q-models in physics. In particular, I shall examine the fundamental principles that led to the development of quantum mechanics. Then I shall consider a possible role of similar principles in using Q-models outside physics. Psychology, economics, and decision science borrow already available Q-models from quantum theory, rather than derive them from their own internal principles, while quantum mechanics was derived from such principles, because there was no readily available mathematical model to handle quantum phenomena, although the mathematics ultimately used in quantum did in fact exist then. I shall argue, however, that the principle perspective on mathematical modeling outside physics might help us to understand better the role of Q-models in these fields and possibly to envision new models, conceptually analogous to but mathematically different from those of quantum theory, helpful or even necessary there or in physics itself. I shall suggest one possible type of such models, singularized probabilistic, SP, models, some of which are time-dependent, TDSP-models. The

A model-averaging method for assessing groundwater conceptual model uncertainty.

PubMed

Ye, Ming; Pohlmann, Karl F; Chapman, Jenny B; Pohll, Greg M; Reeves, Donald M

2010-01-01

This study evaluates alternative groundwater models with different recharge and geologic components at the northern Yucca Flat area of the Death Valley Regional Flow System (DVRFS), USA. Recharge over the DVRFS has been estimated using five methods, and five geological interpretations are available at the northern Yucca Flat area. Combining the recharge and geological components together with additional modeling components that represent other hydrogeological conditions yields a total of 25 groundwater flow models. As all the models are plausible given available data and information, evaluating model uncertainty becomes inevitable. On the other hand, hydraulic parameters (e.g., hydraulic conductivity) are uncertain in each model, giving rise to parametric uncertainty. Propagation of the uncertainty in the models and model parameters through groundwater modeling causes predictive uncertainty in model predictions (e.g., hydraulic head and flow). Parametric uncertainty within each model is assessed using Monte Carlo simulation, and model uncertainty is evaluated using the model averaging method. Two model-averaging techniques (on the basis of information criteria and GLUE) are discussed. This study shows that contribution of model uncertainty to predictive uncertainty is significantly larger than that of parametric uncertainty. For the recharge and geological components, uncertainty in the geological interpretations has more significant effect on model predictions than uncertainty in the recharge estimates. In addition, weighted residuals vary more for the different geological models than for different recharge models. Most of the calibrated observations are not important for discriminating between the alternative models, because their weighted residuals vary only slightly from one model to another.

Climate Models

NASA Technical Reports Server (NTRS)

Druyan, Leonard M.

2012-01-01

Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.

Predicting category intuitiveness with the rational model, the simplicity model, and the generalized context model.

PubMed

Pothos, Emmanuel M; Bailey, Todd M

2009-07-01

Naïve observers typically perceive some groupings for a set of stimuli as more intuitive than others. The problem of predicting category intuitiveness has been historically considered the remit of models of unsupervised categorization. In contrast, this article develops a measure of category intuitiveness from one of the most widely supported models of supervised categorization, the generalized context model (GCM). Considering different category assignments for a set of instances, the authors asked how well the GCM can predict the classification of each instance on the basis of all the other instances. The category assignment that results in the smallest prediction error is interpreted as the most intuitive for the GCM-the authors refer to this way of applying the GCM as "unsupervised GCM." The authors systematically compared predictions of category intuitiveness from the unsupervised GCM and two models of unsupervised categorization: the simplicity model and the rational model. The unsupervised GCM compared favorably with the simplicity model and the rational model. This success of the unsupervised GCM illustrates that the distinction between supervised and unsupervised categorization may need to be reconsidered. However, no model emerged as clearly superior, indicating that there is more work to be done in understanding and modeling category intuitiveness.

Personalized Modeling for Prediction with Decision-Path Models

PubMed Central

Visweswaran, Shyam; Ferreira, Antonio; Ribeiro, Guilherme A.; Oliveira, Alexandre C.; Cooper, Gregory F.

2015-01-01

Deriving predictive models in medicine typically relies on a population approach where a single model is developed from a dataset of individuals. In this paper we describe and evaluate a personalized approach in which we construct a new type of decision tree model called decision-path model that takes advantage of the particular features of a given person of interest. We introduce three personalized methods that derive personalized decision-path models. We compared the performance of these methods to that of Classification And Regression Tree (CART) that is a population decision tree to predict seven different outcomes in five medical datasets. Two of the three personalized methods performed statistically significantly better on area under the ROC curve (AUC) and Brier skill score compared to CART. The personalized approach of learning decision path models is a new approach for predictive modeling that can perform better than a population approach. PMID:26098570

A Lagrangian mixing frequency model for transported PDF modeling

NASA Astrophysics Data System (ADS)

Turkeri, Hasret; Zhao, Xinyu

2017-11-01

In this study, a Lagrangian mixing frequency model is proposed for molecular mixing models within the framework of transported probability density function (PDF) methods. The model is based on the dissipations of mixture fraction and progress variables obtained from Lagrangian particles in PDF methods. The new model is proposed as a remedy to the difficulty in choosing the optimal model constant parameters when using conventional mixing frequency models. The model is implemented in combination with the Interaction by exchange with the mean (IEM) mixing model. The performance of the new model is examined by performing simulations of Sandia Flame D and the turbulent premixed flame from the Cambridge stratified flame series. The simulations are performed using the pdfFOAM solver which is a LES/PDF solver developed entirely in OpenFOAM. A 16-species reduced mechanism is used to represent methane/air combustion, and in situ adaptive tabulation is employed to accelerate the finite-rate chemistry calculations. The results are compared with experimental measurements as well as with the results obtained using conventional mixing frequency models. Dynamic mixing frequencies are predicted using the new model without solving additional transport equations, and good agreement with experimental data is observed.

Modelling MIZ dynamics in a global model

NASA Astrophysics Data System (ADS)

Rynders, Stefanie; Aksenov, Yevgeny; Feltham, Daniel; Nurser, George; Naveira Garabato, Alberto

2016-04-01

Exposure of large, previously ice-covered areas of the Arctic Ocean to the wind and surface ocean waves results in the Arctic pack ice cover becoming more fragmented and mobile, with large regions of ice cover evolving into the Marginal Ice Zone (MIZ). The need for better climate predictions, along with growing economic activity in the Polar Oceans, necessitates climate and forecasting models that can simulate fragmented sea ice with a greater fidelity. Current models are not fully fit for the purpose, since they neither model surface ocean waves in the MIZ, nor account for the effect of floe fragmentation on drag, nor include sea ice rheology that represents both the now thinner pack ice and MIZ ice dynamics. All these processes affect the momentum transfer to the ocean. We present initial results from a global ocean model NEMO (Nucleus for European Modelling of the Ocean) coupled to the Los Alamos sea ice model CICE. The model setup implements a novel rheological formulation for sea ice dynamics, accounting for ice floe collisions, thus offering a seamless framework for pack ice and MIZ simulations. The effect of surface waves on ice motion is included through wave pressure and the turbulent kinetic energy of ice floes. In the multidecadal model integrations we examine MIZ and basin scale sea ice and oceanic responses to the changes in ice dynamics. We analyse model sensitivities and attribute them to key sea ice and ocean dynamical mechanisms. The results suggest that the effect of the new ice rheology is confined to the MIZ. However with the current increase in summer MIZ area, which is projected to continue and may become the dominant type of sea ice in the Arctic, we argue that the effects of the combined sea ice rheology will be noticeable in large areas of the Arctic Ocean, affecting sea ice and ocean. With this study we assert that to make more accurate sea ice predictions in the changing Arctic, models need to include MIZ dynamics and physics.

Variable selection and model choice in geoadditive regression models.

PubMed

Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

2009-06-01

Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

Modeling arson - An exercise in qualitative model building

NASA Technical Reports Server (NTRS)

Heineke, J. M.

1975-01-01

A detailed example is given of the role of von Neumann and Morgenstern's 1944 'expected utility theorem' (in the theory of games and economic behavior) in qualitative model building. Specifically, an arsonist's decision as to the amount of time to allocate to arson and related activities is modeled, and the responsiveness of this time allocation to changes in various policy parameters is examined. Both the activity modeled and the method of presentation are intended to provide an introduction to the scope and power of the expected utility theorem in modeling situations of 'choice under uncertainty'. The robustness of such a model is shown to vary inversely with the number of preference restrictions used in the analysis. The fewer the restrictions, the wider is the class of agents to which the model is applicable, and accordingly more confidence is put in the derived results. A methodological discussion on modeling human behavior is included.

Air Quality Dispersion Modeling - Alternative Models

EPA Pesticide Factsheets

Models, not listed in Appendix W, that can be used in regulatory applications with case-by-case justification to the Reviewing Authority as noted in Section 3.2, Use of Alternative Models, in Appendix W.

Model Organisms and Traditional Chinese Medicine Syndrome Models

PubMed Central

Xu, Jin-Wen

2013-01-01

Traditional Chinese medicine (TCM) is an ancient medical system with a unique cultural background. Nowadays, more and more Western countries due to its therapeutic efficacy are accepting it. However, safety and clear pharmacological action mechanisms of TCM are still uncertain. Due to the potential application of TCM in healthcare, it is necessary to construct a scientific evaluation system with TCM characteristics and benchmark the difference from the standard of Western medicine. Model organisms have played an important role in the understanding of basic biological processes. It is easier to be studied in certain research aspects and to obtain the information of other species. Despite the controversy over suitable syndrome animal model under TCM theoretical guide, it is unquestionable that many model organisms should be used in the studies of TCM modernization, which will bring modern scientific standards into mysterious ancient Chinese medicine. In this review, we aim to summarize the utilization of model organisms in the construction of TCM syndrome model and highlight the relevance of modern medicine with TCM syndrome animal model. It will serve as the foundation for further research of model organisms and for its application in TCM syndrome model. PMID:24381636

Evaluating model accuracy for model-based reasoning

NASA Technical Reports Server (NTRS)

Chien, Steve; Roden, Joseph

1992-01-01

Described here is an approach to automatically assessing the accuracy of various components of a model. In this approach, actual data from the operation of a target system is used to drive statistical measures to evaluate the prediction accuracy of various portions of the model. We describe how these statistical measures of model accuracy can be used in model-based reasoning for monitoring and design. We then describe the application of these techniques to the monitoring and design of the water recovery system of the Environmental Control and Life Support System (ECLSS) of Space Station Freedom.

Examination of simplified travel demand model. [Internal volume forecasting model

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

Smith, R.L. Jr.; McFarlane, W.J.

1978-01-01

A simplified travel demand model, the Internal Volume Forecasting (IVF) model, proposed by Low in 1972 is evaluated as an alternative to the conventional urban travel demand modeling process. The calibration of the IVF model for a county-level study area in Central Wisconsin results in what appears to be a reasonable model; however, analysis of the structure of the model reveals two primary mis-specifications. Correction of the mis-specifications leads to a simplified gravity model version of the conventional urban travel demand models. Application of the original IVF model to ''forecast'' 1960 traffic volumes based on the model calibrated for 1970more » produces accurate estimates. Shortcut and ad hoc models may appear to provide reasonable results in both the base and horizon years; however, as shown by the IVF mode, such models will not always provide a reliable basis for transportation planning and investment decisions.« less

Development of Ensemble Model Based Water Demand Forecasting Model

NASA Astrophysics Data System (ADS)

Kwon, Hyun-Han; So, Byung-Jin; Kim, Seong-Hyeon; Kim, Byung-Seop

2014-05-01

In recent years, Smart Water Grid (SWG) concept has globally emerged over the last decade and also gained significant recognition in South Korea. Especially, there has been growing interest in water demand forecast and optimal pump operation and this has led to various studies regarding energy saving and improvement of water supply reliability. Existing water demand forecasting models are categorized into two groups in view of modeling and predicting their behavior in time series. One is to consider embedded patterns such as seasonality, periodicity and trends, and the other one is an autoregressive model that is using short memory Markovian processes (Emmanuel et al., 2012). The main disadvantage of the abovementioned model is that there is a limit to predictability of water demands of about sub-daily scale because the system is nonlinear. In this regard, this study aims to develop a nonlinear ensemble model for hourly water demand forecasting which allow us to estimate uncertainties across different model classes. The proposed model is consist of two parts. One is a multi-model scheme that is based on combination of independent prediction model. The other one is a cross validation scheme named Bagging approach introduced by Brieman (1996) to derive weighting factors corresponding to individual models. Individual forecasting models that used in this study are linear regression analysis model, polynomial regression, multivariate adaptive regression splines(MARS), SVM(support vector machine). The concepts are demonstrated through application to observed from water plant at several locations in the South Korea. Keywords: water demand, non-linear model, the ensemble forecasting model, uncertainty. Acknowledgements This subject is supported by Korea Ministry of Environment as "Projects for Developing Eco-Innovation Technologies (GT-11-G-02-001-6)

An analytically linearized helicopter model with improved modeling accuracy

NASA Technical Reports Server (NTRS)

Jensen, Patrick T.; Curtiss, H. C., Jr.; Mckillip, Robert M., Jr.

1991-01-01

An analytically linearized model for helicopter flight response including rotor blade dynamics and dynamic inflow, that was recently developed, was studied with the objective of increasing the understanding, the ease of use, and the accuracy of the model. The mathematical model is described along with a description of the UH-60A Black Hawk helicopter and flight test used to validate the model. To aid in utilization of the model for sensitivity analysis, a new, faster, and more efficient implementation of the model was developed. It is shown that several errors in the mathematical modeling of the system caused a reduction in accuracy. These errors in rotor force resolution, trim force and moment calculation, and rotor inertia terms were corrected along with improvements to the programming style and documentation. Use of a trim input file to drive the model is examined. Trim file errors in blade twist, control input phase angle, coning and lag angles, main and tail rotor pitch, and uniform induced velocity, were corrected. Finally, through direct comparison of the original and corrected model responses to flight test data, the effect of the corrections on overall model output is shown.

Beauty and the beast: Some perspectives on efficient model analysis, surrogate models, and the future of modeling

NASA Astrophysics Data System (ADS)

Hill, M. C.; Jakeman, J.; Razavi, S.; Tolson, B.

2015-12-01

For many environmental systems model runtimes have remained very long as more capable computers have been used to add more processes and more time and space discretization. Scientists have also added more parameters and kinds of observations, and many model runs are needed to explore the models. Computational demand equals run time multiplied by number of model runs divided by parallelization opportunities. Model exploration is conducted using sensitivity analysis, optimization, and uncertainty quantification. Sensitivity analysis is used to reveal consequences of what may be very complex simulated relations, optimization is used to identify parameter values that fit the data best, or at least better, and uncertainty quantification is used to evaluate the precision of simulated results. The long execution times make such analyses a challenge. Methods for addressing this challenges include computationally frugal analysis of the demanding original model and a number of ingenious surrogate modeling methods. Both commonly use about 50-100 runs of the demanding original model. In this talk we consider the tradeoffs between (1) original model development decisions, (2) computationally frugal analysis of the original model, and (3) using many model runs of the fast surrogate model. Some questions of interest are as follows. If the added processes and discretization invested in (1) are compared with the restrictions and approximations in model analysis produced by long model execution times, is there a net benefit related of the goals of the model? Are there changes to the numerical methods that could reduce the computational demands while giving up less fidelity than is compromised by using computationally frugal methods or surrogate models for model analysis? Both the computationally frugal methods and surrogate models require that the solution of interest be a smooth function of the parameters or interest. How does the information obtained from the local methods typical

Particle Tracking Model (PTM) with Coastal Modeling System (CMS)

DTIC Science & Technology

2015-11-04

Coastal Inlets Research Program Particle Tracking Model (PTM) with Coastal Modeling System ( CMS ) The Particle Tracking Model (PTM) is a Lagrangian...currents and waves. The Coastal Inlets Research Program (CIRP) supports the PTM with the Coastal Modeling System ( CMS ), which provides coupled wave...and current forcing for PTM simulations. CMS -PTM is implemented in the Surface-water Modeling System, a GUI environment for input development

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic

A BRDF statistical model applying to space target materials modeling

NASA Astrophysics Data System (ADS)

Liu, Chenghao; Li, Zhi; Xu, Can; Tian, Qichen

2017-10-01

In order to solve the problem of poor effect in modeling the large density BRDF measured data with five-parameter semi-empirical model, a refined statistical model of BRDF which is suitable for multi-class space target material modeling were proposed. The refined model improved the Torrance-Sparrow model while having the modeling advantages of five-parameter model. Compared with the existing empirical model, the model contains six simple parameters, which can approximate the roughness distribution of the material surface, can approximate the intensity of the Fresnel reflectance phenomenon and the attenuation of the reflected light's brightness with the azimuth angle changes. The model is able to achieve parameter inversion quickly with no extra loss of accuracy. The genetic algorithm was used to invert the parameters of 11 different samples in the space target commonly used materials, and the fitting errors of all materials were below 6%, which were much lower than those of five-parameter model. The effect of the refined model is verified by comparing the fitting results of the three samples at different incident zenith angles in 0° azimuth angle. Finally, the three-dimensional modeling visualizations of these samples in the upper hemisphere space was given, in which the strength of the optical scattering of different materials could be clearly shown. It proved the good describing ability of the refined model at the material characterization as well.

EIA model documentation: Petroleum market model of the national energy modeling system

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

NONE

1995-12-28

The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. Documentation of the model is in accordance with EIA`s legal obligation to provide adequate documentation in support of its models. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions, the production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supplymore » for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcohols and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level.« less

Towards policy relevant environmental modeling: contextual validity and pragmatic models

USGS Publications Warehouse

Miles, Scott B.

2000-01-01

"What makes for a good model?" In various forms, this question is a question that, undoubtedly, many people, businesses, and institutions ponder with regards to their particular domain of modeling. One particular domain that is wrestling with this question is the multidisciplinary field of environmental modeling. Examples of environmental models range from models of contaminated ground water flow to the economic impact of natural disasters, such as earthquakes. One of the distinguishing claims of the field is the relevancy of environmental modeling to policy and environment-related decision-making in general. A pervasive view by both scientists and decision-makers is that a "good" model is one that is an accurate predictor. Thus, determining whether a model is "accurate" or "correct" is done by comparing model output to empirical observations. The expected outcome of this process, usually referred to as "validation" or "ground truthing," is a stamp on the model in question of "valid" or "not valid" that serves to indicate whether or not the model will be reliable before it is put into service in a decision-making context. In this paper, I begin by elaborating on the prevailing view of model validation and why this view must change. Drawing from concepts coming out of the studies of science and technology, I go on to propose a contextual view of validity that can overcome the problems associated with "ground truthing" models as an indicator of model goodness. The problem of how we talk about and determine model validity has much to do about how we perceive the utility of environmental models. In the remainder of the paper, I argue that we should adopt ideas of pragmatism in judging what makes for a good model and, in turn, developing good models. From such a perspective of model goodness, good environmental models should facilitate communication, convey—not bury or "eliminate"—uncertainties, and, thus, afford the active building of consensus decisions, instead

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

AIR QUALITY MODELING OF AMMONIA: A REGIONAL MODELING PERSPECTIVE

EPA Science Inventory

The talk will address the status of modeling of ammonia from a regional modeling perspective, yet the observations and comments should have general applicability. The air quality modeling system components that are central to modeling ammonia will be noted and a perspective on ...

Temperature-based modeling of reference evapotranspiration using several artificial intelligence models: application of different modeling scenarios

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Maroufpoor, Eisa; Yaseen, Zaher Mundher

2018-02-01

The establishment of an accurate computational model for predicting reference evapotranspiration (ET0) process is highly essential for several agricultural and hydrological applications, especially for the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this research, six artificial intelligence (AI) models were investigated for modeling ET0 using a small number of climatic data generated from the minimum and maximum temperatures of the air and extraterrestrial radiation. The investigated models were multilayer perceptron (MLP), generalized regression neural networks (GRNN), radial basis neural networks (RBNN), integrated adaptive neuro-fuzzy inference systems with grid partitioning and subtractive clustering (ANFIS-GP and ANFIS-SC), and gene expression programming (GEP). The implemented monthly time scale data set was collected at the Antalya and Isparta stations which are located in the Mediterranean Region of Turkey. The Hargreaves-Samani (HS) equation and its calibrated version (CHS) were used to perform a verification analysis of the established AI models. The accuracy of validation was focused on multiple quantitative metrics, including root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R 2), coefficient of residual mass (CRM), and Nash-Sutcliffe efficiency coefficient (NS). The results of the conducted models were highly practical and reliable for the investigated case studies. At the Antalya station, the performance of the GEP and GRNN models was better than the other investigated models, while the performance of the RBNN and ANFIS-SC models was best compared to the other models at the Isparta station. Except for the MLP model, all the other investigated models presented a better performance accuracy compared to the HS and CHS empirical models when applied in a cross-station scenario. A cross-station scenario examination implies the

The medical model versus the just deserts model.

PubMed

Wolfgang, M E

1988-01-01

This paper traces the history of two models that have been influential in shaping modern views toward criminals. One of these two--the medical model--is based on the concept of rehabilitation, that is, treatment predicated on the attributes of the offender. The second of these two--the just deserts model--centers on retribution, that is, punishment deserved for the seriousness of the crime. Each model has been dominant in various periods of history.

DRI Model of the U.S. Economy -- Model Documentation

EIA Publications

1993-01-01

Provides documentation on Data Resources, Inc., DRI Model of the U.S. Economy and the DRI Personal Computer Input/Output Model. It also describes the theoretical basis, structure and functions of both DRI models; and contains brief descriptions of the models and their equations.

Bayesian Model Averaging of Artificial Intelligence Models for Hydraulic Conductivity Estimation

NASA Astrophysics Data System (ADS)

Nadiri, A.; Chitsazan, N.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

This research presents a Bayesian artificial intelligence model averaging (BAIMA) method that incorporates multiple artificial intelligence (AI) models to estimate hydraulic conductivity and evaluate estimation uncertainties. Uncertainty in the AI model outputs stems from error in model input as well as non-uniqueness in selecting different AI methods. Using one single AI model tends to bias the estimation and underestimate uncertainty. BAIMA employs Bayesian model averaging (BMA) technique to address the issue of using one single AI model for estimation. BAIMA estimates hydraulic conductivity by averaging the outputs of AI models according to their model weights. In this study, the model weights were determined using the Bayesian information criterion (BIC) that follows the parsimony principle. BAIMA calculates the within-model variances to account for uncertainty propagation from input data to AI model output. Between-model variances are evaluated to account for uncertainty due to model non-uniqueness. We employed Takagi-Sugeno fuzzy logic (TS-FL), artificial neural network (ANN) and neurofuzzy (NF) to estimate hydraulic conductivity for the Tasuj plain aquifer, Iran. BAIMA combined three AI models and produced better fitting than individual models. While NF was expected to be the best AI model owing to its utilization of both TS-FL and ANN models, the NF model is nearly discarded by the parsimony principle. The TS-FL model and the ANN model showed equal importance although their hydraulic conductivity estimates were quite different. This resulted in significant between-model variances that are normally ignored by using one AI model.

Quelccaya Ice Core Evidence of Widespread Atmospheric Pollution from Colonial Metallurgy after the Spanish Conquest of South America (1532 AD)

NASA Astrophysics Data System (ADS)

Gabrielli, P.; Uglietti, C.; Cooke, C. A.; Thompson, L. G.

2014-12-01

A few ice core records recovered from remote arctic regions suggest a widespread impact of toxic trace elements (Pb, Cu, Sb, As and Bi) to the North Hemisphere atmosphere prior to the onset of the Industrial Revolution (1780s-1830s). In the Southern Hemisphere, evidence for preindustrial trace element emissions are, to date, limited to sediment cores recovered from lakes located within the immediate airshed of major metallurgical centers of South America. Thus it remains unresolved whether they could have had a larger scale impact. Here, we present an annually resolved ice core record of anthropogenic trace element deposition from the remote drilling site of the Quelccaya Ice Cap (Peru) that spans 793-1989 AD. During the pre-Inca period (i.e., prior to ~1450 AD) the deposition of trace elements was dominated by the fallout of aeolian dust from the deglaciated margins of the ice cap and of ash from occasional volcanic eruptions. In contrast, the ice core record indicates a clear anthropogenic signal emerging after the onset of large scale colonial mining and metallurgy (1532-1820 AD), ~300 years prior to the Industrial Revolution during the last part of the Little Ice Age. This shift was coincidental with a major technological transition for silver extraction (1572 AD), from lead-based smelting to mercury amalgamation, that initiated a major increase in ore mining and milling that likely resulted in an increase of metallic dust emissions. While atmospheric trace element deposition resulting from colonial metallurgy was certainly much larger than during the pre-Colonial period, trace element fallout during the Colonial era was still several factors lower than during the 20th century, when the construction of the trans-Andean railway and highways promoted a widespread societal and industrial development of South America.

Optimizing best management practices to control anthropogenic sources of atmospheric phosphorus deposition to inland lakes.

PubMed

Weiss, Lee; Thé, Jesse; Winter, Jennifer; Gharabaghi, Bahram

2018-04-18

Excessive phosphorus loading to inland freshwater lakes around the globe has resulted in nuisance plant growth along the waterfronts, degraded habitat for cold water fisheries, and impaired beaches, marinas and waterfront property. The direct atmospheric deposition of phosphorus can be a significant contributing source to inland lakes. The atmospheric deposition monitoring program for Lake Simcoe, Ontario indicates roughly 20% of the annual total phosphorus load (2010-2014 period) is due to direct atmospheric deposition (both wet and dry deposition) on the lake. This novel study presents a first-time application of the Genetic Algorithm (GA) methodology to optimize the application of best management practices (BMPs) related to agriculture and mobile sources to achieve atmospheric phosphorus reduction targets and restore the ecological health of the lake. The novel methodology takes into account the spatial distribution of the emission sources in the airshed, the complex atmospheric long-range transport and deposition processes, cost and efficiency of the popular management practices and social constraints related to the adoption of BMPs. The optimization scenarios suggest that the optimal overall capital investment of approximately $2M, $4M, and $10M annually can achieve roughly 3, 4 and 5 tonnes reduction in atmospheric P load to the lake, respectively. The exponential trend indicates diminishing returns for the investment beyond roughly $3M per year and that focussing much of this investment in the upwind, nearshore area will significantly impact deposition to the lake. The optimization is based on a combination of the lowest-cost, most-beneficial and socially-acceptable management practices that develops a science-informed promotion of implementation/BMP adoption strategy. The geospatial aspect to the optimization (i.e. proximity and location with respect to the lake) will help land managers to encourage the use of these targeted best practices in areas that

Source Characterization of Volatile Organic Compounds Affecting the Air Quality in a Coastal Urban Area of South Texas

PubMed Central

Sanchez, Marciano; Karnae, Saritha; John, Kuruvilla

2008-01-01

Selected Volatile Organic Compounds (VOC) emitted from various anthropogenic sources including industries and motor vehicles act as primary precursors of ozone, while some VOC are classified as air toxic compounds. Significantly large VOC emission sources impact the air quality in Corpus Christi, Texas. This urban area is located in a semi-arid region of South Texas and is home to several large petrochemical refineries and industrial facilities along a busy ship-channel. The Texas Commission on Environmental Quality has setup two continuous ambient monitoring stations (CAMS 633 and 634) along the ship channel to monitor VOC concentrations in the urban atmosphere. The hourly concentrations of 46 VOC compounds were acquired from TCEQ for a comprehensive source apportionment study. The primary objective of this study was to identify and quantify the sources affecting the ambient air quality within this urban airshed. Principal Component Analysis/Absolute Principal Component Scores (PCA/APCS) was applied to the dataset. PCA identified five possible sources accounting for 69% of the total variance affecting the VOC levels measured at CAMS 633 and six possible sources affecting CAMS 634 accounting for 75% of the total variance. APCS identified natural gas emissions to be the major source contributor at CAMS 633 and it accounted for 70% of the measured VOC concentrations. The other major sources identified at CAMS 633 included flare emissions (12%), fugitive gasoline emissions (9%), refinery operations (7%), and vehicle exhaust (2%). At CAMS 634, natural gas sources were identified as the major source category contributing to 31% of the observed VOC. The other sources affecting this site included: refinery operations (24%), flare emissions (22%), secondary industrial processes (12%), fugitive gasoline emissions (8%) and vehicle exhaust (3%). PMID:19139530

Gas and Particulate Aircraft Emissions Measurements: Impacts on local air quality.

NASA Astrophysics Data System (ADS)

Jayne, J. T.; Onasch, T.; Northway, M.; Canagaratna, M.; Worsnop, D.; Timko, M.; Wood, E.; Miake-Lye, R.; Herndon, S.; Knighton, B.; Whitefield, P.; Hagen, D.; Lobo, P.; Anderson, B.

2007-12-01

Air travel and freight shipping by air are becoming increasingly important and are expected to continue to expand. The resulting increases in the local concentrations of pollutants, including particulate matter (PM), volatile organic compounds (VOCs), and nitrogen oxides (NOX), can have negative impacts on regional air quality, human health and can impact climate change. In order to construct valid emission inventories, accurate measurements of aircraft emissions are needed. These measurements must be done both at the engine exit plane (certification) and downwind following the rapid cooling, dilution and initial atmospheric processing of the exhaust plume. We present here results from multiple field experiments which include the Experiment to Characterize Volatile Aerosol and Trace Species Emissions (EXCAVATE) and the four Aircraft Particle Emissions eXperiments (APEX- 1/Atlanta/2/3) which characterized gas and particle emissions from both stationary or in-use aircraft. Emission indices (EIs) for NOx and VOCs and for particle number concentration, refractory PM (black carbon soot) and volatile PM (primarily sulfate and organic) particles are reported. Measurements were made at the engine exit plane and at several downstream locations (10 and 30 meters) for a number of different engine types and engine thrust settings. A significant fraction of organic particle mass is composed of low volatility oil-related compounds and is not combustion related, potentially emitted by vents or heated surfaces within aircraft engines. Advected plumes measurements from in-use aircraft show that the practice of reduced thrust take-offs has a significant effect on total NOx and soot emitted in the vicinity of the airport. The measurements reported here represent a first observation of this effect and new insights have been gained with respect to the chemical processing of gases and particulates important to the urban airshed.

Patterns of mercury dispersion from local and regional emission sources, rural Central Wisconsin, USA

USGS Publications Warehouse

Kolker, A.; Olson, M.L.; Krabbenhoft, D.P.; Tate, M.T.; Engle, M.A.

2010-01-01

Simultaneous real-time changes in mercury (Hg) speciation ?????" reactive gaseous Hg (RGM), elemental Hg (Hg??), and fine particulate Hg (Hg-PM2.5), were determined from June to November 2007, in ambient air at three locations in rural Central Wisconsin. Known Hg emission sources within the airshed of the monitoring sites include: 1) a 1114 megawatt (MW) coal-fired electric utility generating station; 2) a Hg-bed chlor-alkali plant; and 3) a smaller (465 MW) coal-burning electric utility. Monitoring sites, showing sporadic elevation of RGM, Hg?? and Hg-PM 2.5, were positioned at distances of 25, 50 and 100 km northward of the larger electric utility. A series of RGM events were recorded at each site. The largest, on 23 September, occurred under prevailing southerly winds, with a maximum RGM value (56.8 pg m-3) measured at the 100 km site, and corresponding elevated SO2 (10.41 ppbv; measured at 50 km site). The finding that RGM, Hg??, and Hg-PM2.5 are not always highest at the 25 km site, closest to the large generating station, contradicts the idea that RGM decreases with distance from a large point source. This may be explained if: 1) the 100 km site was influenced by emissions from the chlor-alkali facility or by RGM from regional urban sources; 2) the emission stack height of the larger power plant promoted plume transport at an elevation where the Hg is carried over the closest site; or 3) RGM was being generated in the plume through oxidation of Hg??. Operational changes at each emitter since 2007 should reduce their Hg output, potentially allowing quantification of the environmental benefit in future studies.

Assessing the spatial and temporal variability of fine particulate matter components in Israeli, Jordanian, and Palestinian cities

NASA Astrophysics Data System (ADS)

Sarnat, Jeremy A.; Moise, Tamar; Shpund, Jacob; Liu, Yang; Pachon, Jorge E.; Qasrawi, Radwan; Abdeen, Ziad; Brenner, Shmuel; Nassar, Khaled; Saleh, Rami; Schauer, James J.

2010-07-01

This manuscript presents results from an extensive, multi-country comparative monitoring study of fine particulate matter (PM 2.5) and its primary chemical components in Israeli, Jordanian and Palestinian cities. This study represented the first time that researchers from these countries have worked together to examine spatial and temporal relationships for PM 2.5 and its major components among the study sites. The findings indicated that total PM 2.5 mass was relatively homogenous among many of the 11 sites as shown from strong between-site correlations. Mean annual concentrations ranged from 19.9 to 34.9 μg m -3 in Haifa and Amman, respectively, and exceeded accepted international air quality standards for annual PM 2.5 mass. Similarity of total mass was largely driven by SO 42- and crustal PM 2.5 components. Despite the close proximity of the seven, well correlated sites with respect to PM 2.5, there were pronounced differences among the cities for EC and, to a lesser degree, OC. EC, in particular, exhibited spatiotemporal trends that were indicative of strong local source contributions. Interestingly, there were moderate to strong EC correlations ( r > 0.65) among the large metropolitan cities, West Jerusalem, Tel Aviv and Amman. For these relatively large cities, (i.e., West Jerusalem, Tel Aviv and Amman), EC sources from the fleet of buses and cars typical for many urban areas predominate and likely drive spatiotemporal EC distributions. As new airshed management strategies and public health interventions are implemented throughout the Middle East, our findings support regulatory strategies that target integrated regional and local control strategies to reduce PM 2.5 mass and specific components suspected to drive adverse health effects of particulate matter exposure.

Modeling Guru: Knowledge Base for NASA Modelers

NASA Astrophysics Data System (ADS)

Seablom, M. S.; Wojcik, G. S.; van Aartsen, B. H.

2009-05-01

Modeling Guru is an on-line knowledge-sharing resource for anyone involved with or interested in NASA's scientific models or High End Computing (HEC) systems. Developed and maintained by the NASA's Software Integration and Visualization Office (SIVO) and the NASA Center for Computational Sciences (NCCS), Modeling Guru's combined forums and knowledge base for research and collaboration is becoming a repository for the accumulated expertise of NASA's scientific modeling and HEC communities. All NASA modelers and associates are encouraged to participate and provide knowledge about the models and systems so that other users may benefit from their experience. Modeling Guru is divided into a hierarchy of communities, each with its own set forums and knowledge base documents. Current modeling communities include those for space science, land and atmospheric dynamics, atmospheric chemistry, and oceanography. In addition, there are communities focused on NCCS systems, HEC tools and libraries, and programming and scripting languages. Anyone may view most of the content on Modeling Guru (available at http://modelingguru.nasa.gov/), but you must log in to post messages and subscribe to community postings. The site offers a full range of "Web 2.0" features, including discussion forums, "wiki" document generation, document uploading, RSS feeds, search tools, blogs, email notification, and "breadcrumb" links. A discussion (a.k.a. forum "thread") is used to post comments, solicit feedback, or ask questions. If marked as a question, SIVO will monitor the thread, and normally respond within a day. Discussions can include embedded images, tables, and formatting through the use of the Rich Text Editor. Also, the user can add "Tags" to their thread to facilitate later searches. The "knowledge base" is comprised of documents that are used to capture and share expertise with others. The default "wiki" document lets users edit within the browser so others can easily collaborate on the

Predictive QSAR modeling workflow, model applicability domains, and virtual screening.

PubMed

Tropsha, Alexander; Golbraikh, Alexander

2007-01-01

Quantitative Structure Activity Relationship (QSAR) modeling has been traditionally applied as an evaluative approach, i.e., with the focus on developing retrospective and explanatory models of existing data. Model extrapolation was considered if only in hypothetical sense in terms of potential modifications of known biologically active chemicals that could improve compounds' activity. This critical review re-examines the strategy and the output of the modern QSAR modeling approaches. We provide examples and arguments suggesting that current methodologies may afford robust and validated models capable of accurate prediction of compound properties for molecules not included in the training sets. We discuss a data-analytical modeling workflow developed in our laboratory that incorporates modules for combinatorial QSAR model development (i.e., using all possible binary combinations of available descriptor sets and statistical data modeling techniques), rigorous model validation, and virtual screening of available chemical databases to identify novel biologically active compounds. Our approach places particular emphasis on model validation as well as the need to define model applicability domains in the chemistry space. We present examples of studies where the application of rigorously validated QSAR models to virtual screening identified computational hits that were confirmed by subsequent experimental investigations. The emerging focus of QSAR modeling on target property forecasting brings it forward as predictive, as opposed to evaluative, modeling approach.

Benchmarking an Unstructured-Grid Model for Tsunami Current Modeling

NASA Astrophysics Data System (ADS)

Zhang, Yinglong J.; Priest, George; Allan, Jonathan; Stimely, Laura

2016-12-01

We present model results derived from a tsunami current benchmarking workshop held by the NTHMP (National Tsunami Hazard Mitigation Program) in February 2015. Modeling was undertaken using our own 3D unstructured-grid model that has been previously certified by the NTHMP for tsunami inundation. Results for two benchmark tests are described here, including: (1) vortex structure in the wake of a submerged shoal and (2) impact of tsunami waves on Hilo Harbor in the 2011 Tohoku event. The modeled current velocities are compared with available lab and field data. We demonstrate that the model is able to accurately capture the velocity field in the two benchmark tests; in particular, the 3D model gives a much more accurate wake structure than the 2D model for the first test, with the root-mean-square error and mean bias no more than 2 cm s-1 and 8 mm s-1, respectively, for the modeled velocity.

Modelling Students' Construction of Energy Models in Physics.

ERIC Educational Resources Information Center

Devi, Roshni; And Others

1996-01-01

Examines students' construction of experimentation models for physics theories in energy storage, transformation, and transfers involving electricity and mechanics. Student problem solving dialogs and artificial intelligence modeling of these processes is analyzed. Construction of models established relations between elements with linear causal…

An empirical model to forecast solar wind velocity through statistical modeling

NASA Astrophysics Data System (ADS)

Gao, Y.; Ridley, A. J.

2013-12-01

The accurate prediction of the solar wind velocity has been a major challenge in the space weather community. Previous studies proposed many empirical and semi-empirical models to forecast the solar wind velocity based on either the historical observations, e.g. the persistence model, or the instantaneous observations of the sun, e.g. the Wang-Sheeley-Arge model. In this study, we use the one-minute WIND data from January 1995 to August 2012 to investigate and compare the performances of 4 models often used in literature, here referred to as the null model, the persistence model, the one-solar-rotation-ago model, and the Wang-Sheeley-Arge model. It is found that, measured by root mean square error, the persistence model gives the most accurate predictions within two days. Beyond two days, the Wang-Sheeley-Arge model serves as the best model, though it only slightly outperforms the null model and the one-solar-rotation-ago model. Finally, we apply the least-square regression to linearly combine the null model, the persistence model, and the one-solar-rotation-ago model to propose a 'general persistence model'. By comparing its performance against the 4 aforementioned models, it is found that the accuracy of the general persistence model outperforms the other 4 models within five days. Due to its great simplicity and superb performance, we believe that the general persistence model can serve as a benchmark in the forecast of solar wind velocity and has the potential to be modified to arrive at better models.

A Primer for Model Selection: The Decisive Role of Model Complexity

NASA Astrophysics Data System (ADS)

Höge, Marvin; Wöhling, Thomas; Nowak, Wolfgang

2018-03-01

Selecting a "best" model among several competing candidate models poses an often encountered problem in water resources modeling (and other disciplines which employ models). For a modeler, the best model fulfills a certain purpose best (e.g., flood prediction), which is typically assessed by comparing model simulations to data (e.g., stream flow). Model selection methods find the "best" trade-off between good fit with data and model complexity. In this context, the interpretations of model complexity implied by different model selection methods are crucial, because they represent different underlying goals of modeling. Over the last decades, numerous model selection criteria have been proposed, but modelers who primarily want to apply a model selection criterion often face a lack of guidance for choosing the right criterion that matches their goal. We propose a classification scheme for model selection criteria that helps to find the right criterion for a specific goal, i.e., which employs the correct complexity interpretation. We identify four model selection classes which seek to achieve high predictive density, low predictive error, high model probability, or shortest compression of data. These goals can be achieved by following either nonconsistent or consistent model selection and by either incorporating a Bayesian parameter prior or not. We allocate commonly used criteria to these four classes, analyze how they represent model complexity and what this means for the model selection task. Finally, we provide guidance on choosing the right type of criteria for specific model selection tasks. (A quick guide through all key points is given at the end of the introduction.)

Model-free and model-based reward prediction errors in EEG.

PubMed

Sambrook, Thomas D; Hardwick, Ben; Wills, Andy J; Goslin, Jeremy

2018-05-24

Learning theorists posit two reinforcement learning systems: model-free and model-based. Model-based learning incorporates knowledge about structure and contingencies in the world to assign candidate actions with an expected value. Model-free learning is ignorant of the world's structure; instead, actions hold a value based on prior reinforcement, with this value updated by expectancy violation in the form of a reward prediction error. Because they use such different learning mechanisms, it has been previously assumed that model-based and model-free learning are computationally dissociated in the brain. However, recent fMRI evidence suggests that the brain may compute reward prediction errors to both model-free and model-based estimates of value, signalling the possibility that these systems interact. Because of its poor temporal resolution, fMRI risks confounding reward prediction errors with other feedback-related neural activity. In the present study, EEG was used to show the presence of both model-based and model-free reward prediction errors and their place in a temporal sequence of events including state prediction errors and action value updates. This demonstration of model-based prediction errors questions a long-held assumption that model-free and model-based learning are dissociated in the brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Spin-Up and Tuning of the Global Carbon Cycle Model Inside the GISS ModelE2 GCM

NASA Technical Reports Server (NTRS)

Aleinov, Igor; Kiang, Nancy Y.; Romanou, Anastasia

2015-01-01

Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.

Culturicon model: A new model for cultural-based emoticon

NASA Astrophysics Data System (ADS)

Zukhi, Mohd Zhafri Bin Mohd; Hussain, Azham

2017-10-01

Emoticons are popular among distributed collective interaction user in expressing their emotion, gestures and actions. Emoticons have been proved to be able to avoid misunderstanding of the message, attention saving and improved the communications among different native speakers. However, beside the benefits that emoticons can provide, the study regarding emoticons in cultural perspective is still lacking. As emoticons are crucial in global communication, culture should be one of the extensively research aspect in distributed collective interaction. Therefore, this study attempt to explore and develop model for cultural-based emoticon. Three cultural models that have been used in Human-Computer Interaction were studied which are the Hall Culture Model, Trompenaars and Hampden Culture Model and Hofstede Culture Model. The dimensions from these three models will be used in developing the proposed cultural-based emoticon model.

Determining Reduced Order Models for Optimal Stochastic Reduced Order Models

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

Bonney, Matthew S.; Brake, Matthew R.W.

2015-08-01

The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a Taylor series using finite difference, a proper orthogonal decomposition of the the output, a Craig-Bampton representation of the model, a method that uses Hyper-Dual numbers to determine the sensitivities, and a Meta-Model method that uses the Hyper-Dual results and constructs a polynomial curve to better representmore » the output data. The methods are compared against a parameter sweep and a distribution propagation where the first four statistical moments are used as a comparison. Each method produces very accurate results with the Craig-Bampton reduction having the least accurate results. The models are also compared based on time requirements for the evaluation of each model where the Meta- Model requires the least amount of time for computation by a significant amount. Each of the five models provided accurate results in a reasonable time frame. The determination of which model to use is dependent on the availability of the high-fidelity model and how many evaluations can be performed. Analysis of the output distribution is examined by using a large Monte-Carlo simulation along with a reduced simulation using Latin Hypercube and the stochastic reduced order model sampling technique. Both techniques produced accurate results. The stochastic reduced order modeling technique produced less error when compared to an exhaustive sampling for the majority of methods.« less

On temporal stochastic modeling of precipitation, nesting models across scales

NASA Astrophysics Data System (ADS)

Paschalis, Athanasios; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

2014-01-01

We analyze the performance of composite stochastic models of temporal precipitation which can satisfactorily reproduce precipitation properties across a wide range of temporal scales. The rationale is that a combination of stochastic precipitation models which are most appropriate for specific limited temporal scales leads to better overall performance across a wider range of scales than single models alone. We investigate different model combinations. For the coarse (daily) scale these are models based on Alternating renewal processes, Markov chains, and Poisson cluster models, which are then combined with a microcanonical Multiplicative Random Cascade model to disaggregate precipitation to finer (minute) scales. The composite models were tested on data at four sites in different climates. The results show that model combinations improve the performance in key statistics such as probability distributions of precipitation depth, autocorrelation structure, intermittency, reproduction of extremes, compared to single models. At the same time they remain reasonably parsimonious. No model combination was found to outperform the others at all sites and for all statistics, however we provide insight on the capabilities of specific model combinations. The results for the four different climates are similar, which suggests a degree of generality and wider applicability of the approach.

Model Selection Methods for Mixture Dichotomous IRT Models

ERIC Educational Resources Information Center

Li, Feiming; Cohen, Allan S.; Kim, Seock-Ho; Cho, Sun-Joo

2009-01-01

This study examines model selection indices for use with dichotomous mixture item response theory (IRT) models. Five indices are considered: Akaike's information coefficient (AIC), Bayesian information coefficient (BIC), deviance information coefficient (DIC), pseudo-Bayes factor (PsBF), and posterior predictive model checks (PPMC). The five…

Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models.

PubMed

Gomes, Anna; van der Wijk, Lars; Proost, Johannes H; Sinha, Bhanu; Touw, Daan J

2017-01-01

Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid

Pharmacokinetic modeling of gentamicin in treatment of infective endocarditis: Model development and validation of existing models

PubMed Central

van der Wijk, Lars; Proost, Johannes H.; Sinha, Bhanu; Touw, Daan J.

2017-01-01

Gentamicin shows large variations in half-life and volume of distribution (Vd) within and between individuals. Thus, monitoring and accurately predicting serum levels are required to optimize effectiveness and minimize toxicity. Currently, two population pharmacokinetic models are applied for predicting gentamicin doses in adults. For endocarditis patients the optimal model is unknown. We aimed at: 1) creating an optimal model for endocarditis patients; and 2) assessing whether the endocarditis and existing models can accurately predict serum levels. We performed a retrospective observational two-cohort study: one cohort to parameterize the endocarditis model by iterative two-stage Bayesian analysis, and a second cohort to validate and compare all three models. The Akaike Information Criterion and the weighted sum of squares of the residuals divided by the degrees of freedom were used to select the endocarditis model. Median Prediction Error (MDPE) and Median Absolute Prediction Error (MDAPE) were used to test all models with the validation dataset. We built the endocarditis model based on data from the modeling cohort (65 patients) with a fixed 0.277 L/h/70kg metabolic clearance, 0.698 (±0.358) renal clearance as fraction of creatinine clearance, and Vd 0.312 (±0.076) L/kg corrected lean body mass. External validation with data from 14 validation cohort patients showed a similar predictive power of the endocarditis model (MDPE -1.77%, MDAPE 4.68%) as compared to the intensive-care (MDPE -1.33%, MDAPE 4.37%) and standard (MDPE -0.90%, MDAPE 4.82%) models. All models acceptably predicted pharmacokinetic parameters for gentamicin in endocarditis patients. However, these patients appear to have an increased Vd, similar to intensive care patients. Vd mainly determines the height of peak serum levels, which in turn correlate with bactericidal activity. In order to maintain simplicity, we advise to use the existing intensive-care model in clinical practice to avoid

Agent-based modeling: case study in cleavage furrow models

PubMed Central

Mogilner, Alex; Manhart, Angelika

2016-01-01

The number of studies in cell biology in which quantitative models accompany experiments has been growing steadily. Roughly, mathematical and computational techniques of these models can be classified as “differential equation based” (DE) or “agent based” (AB). Recently AB models have started to outnumber DE models, but understanding of AB philosophy and methodology is much less widespread than familiarity with DE techniques. Here we use the history of modeling a fundamental biological problem—positioning of the cleavage furrow in dividing cells—to explain how and why DE and AB models are used. We discuss differences, advantages, and shortcomings of these two approaches. PMID:27811328

A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models

NASA Technical Reports Server (NTRS)

Giunta, Anthony A.; Watson, Layne T.

1998-01-01

Two methods of creating approximation models are compared through the calculation of the modeling accuracy on test problems involving one, five, and ten independent variables. Here, the test problems are representative of the modeling challenges typically encountered in realistic engineering optimization problems. The first approximation model is a quadratic polynomial created using the method of least squares. This type of polynomial model has seen considerable use in recent engineering optimization studies due to its computational simplicity and ease of use. However, quadratic polynomial models may be of limited accuracy when the response data to be modeled have multiple local extrema. The second approximation model employs an interpolation scheme known as kriging developed in the fields of spatial statistics and geostatistics. This class of interpolating model has the flexibility to model response data with multiple local extrema. However, this flexibility is obtained at an increase in computational expense and a decrease in ease of use. The intent of this study is to provide an initial exploration of the accuracy and modeling capabilities of these two approximation methods.

Groundwater modelling in conceptual hydrological models - introducing space

NASA Astrophysics Data System (ADS)

Boje, Søren; Skaugen, Thomas; Møen, Knut; Myrabø, Steinar

2017-04-01

The tiny Sæternbekken Minifelt (Muren) catchment (7500 m2) in Bærumsmarka, Norway, was during the 1990s, densely instrumented with more than a 100 observation points for measuring groundwater levels. The aim was to investigate the link between shallow groundwater dynamics and runoff. The DDD (Distance Distribution Dynamics) model is a newly developed rainfall-runoff model used operationally by the Norwegian Flood-Forecasting service at NVE. The model estimates the capacity of the subsurface reservoir at different levels of saturation and predicts overland flow. The subsurface in the DDD model has a 2-D representation that calculates the saturated and unsaturated soil moisture along a hillslope representing the entire catchment in question. The groundwater observations from more than two decades ago are used to verify assumptions of the subsurface reservoir in the DDD model and to validate its spatial representation of the subsurface reservoir. The Muren catchment will, during 2017, be re-instrumented in order to continue the work to bridge the gap between conceptual hydrological models, with typically single value or 0-dimension representation of the subsurface, and models with more realistic 2- or 3-dimension representation of the subsurface.

Model Comparison of Bayesian Semiparametric and Parametric Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Xia, Ye-Mao; Pan, Jun-Hao; Lee, Sik-Yum

2011-01-01

Structural equation models have wide applications. One of the most important issues in analyzing structural equation models is model comparison. This article proposes a Bayesian model comparison statistic, namely the "L[subscript nu]"-measure for both semiparametric and parametric structural equation models. For illustration purposes, we consider…

BioModels: expanding horizons to include more modelling approaches and formats

PubMed Central

Nguyen, Tung V N; Graesslin, Martin; Hälke, Robert; Ali, Raza; Schramm, Jochen; Wimalaratne, Sarala M; Kothamachu, Varun B; Rodriguez, Nicolas; Swat, Maciej J; Eils, Jurgen; Eils, Roland; Laibe, Camille; Chelliah, Vijayalakshmi

2018-01-01

Abstract BioModels serves as a central repository of mathematical models representing biological processes. It offers a platform to make mathematical models easily shareable across the systems modelling community, thereby supporting model reuse. To facilitate hosting a broader range of model formats derived from diverse modelling approaches and tools, a new infrastructure for BioModels has been developed that is available at http://www.ebi.ac.uk/biomodels. This new system allows submitting and sharing of a wide range of models with improved support for formats other than SBML. It also offers a version-control backed environment in which authors and curators can work collaboratively to curate models. This article summarises the features available in the current system and discusses the potential benefit they offer to the users over the previous system. In summary, the new portal broadens the scope of models accepted in BioModels and supports collaborative model curation which is crucial for model reproducibility and sharing. PMID:29106614

Is the Voter Model a Model for Voters?

NASA Astrophysics Data System (ADS)

Fernández-Gracia, Juan; Suchecki, Krzysztof; Ramasco, José J.; San Miguel, Maxi; Eguíluz, Víctor M.

2014-04-01

The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability to model real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with recurrent mobility of agents (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model. We show that the dynamics can be described as a noisy diffusive process that contains the proper anisotropic coupling topology given by population and mobility heterogeneity. The model captures statistical features of U.S. presidential elections as the stationary vote-share fluctuations across counties and the long-range spatial correlations that decay logarithmically with the distance. Furthermore, it recovers the behavior of these properties when the geographical space is coarse grained at different scales—from the county level through congressional districts, and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making, which are consistent with the empirical observations.

Sequence modelling and an extensible data model for genomic database

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

Li, Peter Wei-Der

1992-01-01

The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS's do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data modelmore » that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the Extensible Object Model'', to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.« less

Sequence modelling and an extensible data model for genomic database

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

Li, Peter Wei-Der

1992-01-01

The Human Genome Project (HGP) plans to sequence the human genome by the beginning of the next century. It will generate DNA sequences of more than 10 billion bases and complex marker sequences (maps) of more than 100 million markers. All of these information will be stored in database management systems (DBMSs). However, existing data models do not have the abstraction mechanism for modelling sequences and existing DBMS`s do not have operations for complex sequences. This work addresses the problem of sequence modelling in the context of the HGP and the more general problem of an extensible object data modelmore » that can incorporate the sequence model as well as existing and future data constructs and operators. First, we proposed a general sequence model that is application and implementation independent. This model is used to capture the sequence information found in the HGP at the conceptual level. In addition, abstract and biological sequence operators are defined for manipulating the modelled sequences. Second, we combined many features of semantic and object oriented data models into an extensible framework, which we called the ``Extensible Object Model``, to address the need of a modelling framework for incorporating the sequence data model with other types of data constructs and operators. This framework is based on the conceptual separation between constructors and constraints. We then used this modelling framework to integrate the constructs for the conceptual sequence model. The Extensible Object Model is also defined with a graphical representation, which is useful as a tool for database designers. Finally, we defined a query language to support this model and implement the query processor to demonstrate the feasibility of the extensible framework and the usefulness of the conceptual sequence model.« less

Log-Multiplicative Association Models as Item Response Models

ERIC Educational Resources Information Center

Anderson, Carolyn J.; Yu, Hsiu-Ting

2007-01-01

Log-multiplicative association (LMA) models, which are special cases of log-linear models, have interpretations in terms of latent continuous variables. Two theoretical derivations of LMA models based on item response theory (IRT) arguments are presented. First, we show that Anderson and colleagues (Anderson & Vermunt, 2000; Anderson & Bockenholt,…

The Use of Modeling-Based Text to Improve Students' Modeling Competencies

ERIC Educational Resources Information Center

Jong, Jing-Ping; Chiu, Mei-Hung; Chung, Shiao-Lan

2015-01-01

This study investigated the effects of a modeling-based text on 10th graders' modeling competencies. Fifteen 10th graders read a researcher-developed modeling-based science text on the ideal gas law that included explicit descriptions and representations of modeling processes (i.e., model selection, model construction, model validation, model…

Model documentation Natural Gas Transmission and Distribution Model of the National Energy Modeling System. Volume 1

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

NONE

1996-02-26

The Natural Gas Transmission and Distribution Model (NGTDM) of the National Energy Modeling System is developed and maintained by the Energy Information Administration (EIA), Office of Integrated Analysis and Forecasting. This report documents the archived version of the NGTDM that was used to produce the natural gas forecasts presented in the Annual Energy Outlook 1996, (DOE/EIA-0383(96)). The purpose of this report is to provide a reference document for model analysts, users, and the public that defines the objectives of the model, describes its basic approach, and provides detail on the methodology employed. Previously this report represented Volume I of amore » two-volume set. Volume II reported on model performance, detailing convergence criteria and properties, results of sensitivity testing, comparison of model outputs with the literature and/or other model results, and major unresolved issues.« less

Dynamic Emulation Modelling (DEMo) of large physically-based environmental models

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.

2012-12-01

In environmental modelling large, spatially-distributed, physically-based models are widely adopted to describe the dynamics of physical, social and economic processes. Such an accurate process characterization comes, however, to a price: the computational requirements of these models are considerably high and prevent their use in any problem requiring hundreds or thousands of model runs to be satisfactory solved. Typical examples include optimal planning and management, data assimilation, inverse modelling and sensitivity analysis. An effective approach to overcome this limitation is to perform a top-down reduction of the physically-based model by identifying a simplified, computationally efficient emulator, constructed from and then used in place of the original model in highly resource-demanding tasks. The underlying idea is that not all the process details in the original model are equally important and relevant to the dynamics of the outputs of interest for the type of problem considered. Emulation modelling has been successfully applied in many environmental applications, however most of the literature considers non-dynamic emulators (e.g. metamodels, response surfaces and surrogate models), where the original dynamical model is reduced to a static map between input and the output of interest. In this study we focus on Dynamic Emulation Modelling (DEMo), a methodological approach that preserves the dynamic nature of the original physically-based model, with consequent advantages in a wide variety of problem areas. In particular, we propose a new data-driven DEMo approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is both particularly effective in some applications (e.g. optimal management and data assimilation) and facilitates the ex-post physical interpretation of the emulator structure, thus enhancing the

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Models of ovarian cancer metastasis: Murine models

PubMed Central

Šale, Sanja; Orsulic, Sandra

2008-01-01

Mice have mainly been used in ovarian cancer research as immunodeficient hosts for cell lines derived from the primary tumors and ascites of ovarian cancer patients. These xenograft models have provided a valuable system for pre-clinical trials, however, the genetic complexity of human tumors has precluded the understanding of key events that drive metastatic dissemination. Recently developed immunocompetent, genetically defined mouse models of epithelial ovarian cancer represent significant improvements in the modeling of metastatic disease. PMID:19337569

Addressing Hydro-economic Modeling Limitations - A Limited Foresight Sacramento Valley Model and an Open-source Modeling Platform

NASA Astrophysics Data System (ADS)

Harou, J. J.; Hansen, K. M.

2008-12-01

Increased scarcity of world water resources is inevitable given the limited supply and increased human pressures. The idea that "some scarcity is optimal" must be accepted for rational resource use and infrastructure management decisions to be made. Hydro-economic systems models are unique at representing the overlap of economic drivers, socio-political forces and distributed water resource systems. They demonstrate the tangible benefits of cooperation and integrated flexible system management. Further improvement of models, quality control practices and software will be needed for these academic policy tools to become accepted into mainstream water resource practice. Promising features include: calibration methods, limited foresight optimization formulations, linked simulation-optimization approaches (e.g. embedding pre-existing calibrated simulation models), spatial groundwater models, stream-aquifer interactions and stream routing, etc.. Conventional user-friendly decision support systems helped spread simulation models on a massive scale. Hydro-economic models must also find a means to facilitate construction, distribution and use. Some of these issues and model features are illustrated with a hydro-economic optimization model of the Sacramento Valley. Carry-over storage value functions are used to limit hydrologic foresight of the multi- period optimization model. Pumping costs are included in the formulation by tracking regional piezometric head of groundwater sub-basins. To help build and maintain this type of network model, an open-source water management modeling software platform is described and initial project work is discussed. The objective is to generically facilitate the connection of models, such as those developed in a modeling environment (GAMS, MatLab, Octave, "), to a geographic user interface (drag and drop node-link network) and a database (topology, parameters and time series). These features aim to incrementally move hydro- economic models

JEDI International Model | Jobs and Economic Development Impact Models |

Science.gov Websites

NREL International Model JEDI International Model The Jobs and Economic Development Impacts (JEDI) International Model allows users to estimate economic development impacts from international

Modeling of the Global Water Cycle - Analytical Models

Treesearch

Yongqiang Liu; Roni Avissar

2005-01-01

Both numerical and analytical models of coupled atmosphere and its underlying ground components (land, ocean, ice) are useful tools for modeling the global and regional water cycle. Unlike complex three-dimensional climate models, which need very large computing resources and involve a large number of complicated interactions often difficult to interpret, analytical...

Seven challenges for metapopulation models of epidemics, including households models.

PubMed

Ball, Frank; Britton, Tom; House, Thomas; Isham, Valerie; Mollison, Denis; Pellis, Lorenzo; Scalia Tomba, Gianpaolo

2015-03-01

This paper considers metapopulation models in the general sense, i.e. where the population is partitioned into sub-populations (groups, patches,...), irrespective of the biological interpretation they have, e.g. spatially segregated large sub-populations, small households or hosts themselves modelled as populations of pathogens. This framework has traditionally provided an attractive approach to incorporating more realistic contact structure into epidemic models, since it often preserves analytic tractability (in stochastic as well as deterministic models) but also captures the most salient structural inhomogeneity in contact patterns in many applied contexts. Despite the progress that has been made in both the theory and application of such metapopulation models, we present here several major challenges that remain for future work, focusing on models that, in contrast to agent-based ones, are amenable to mathematical analysis. The challenges range from clarifying the usefulness of systems of weakly-coupled large sub-populations in modelling the spread of specific diseases to developing a theory for endemic models with household structure. They include also developing inferential methods for data on the emerging phase of epidemics, extending metapopulation models to more complex forms of human social structure, developing metapopulation models to reflect spatial population structure, developing computationally efficient methods for calculating key epidemiological model quantities, and integrating within- and between-host dynamics in models. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

A High Precision Prediction Model Using Hybrid Grey Dynamic Model

ERIC Educational Resources Information Center

Li, Guo-Dong; Yamaguchi, Daisuke; Nagai, Masatake; Masuda, Shiro

2008-01-01

In this paper, we propose a new prediction analysis model which combines the first order one variable Grey differential equation Model (abbreviated as GM(1,1) model) from grey system theory and time series Autoregressive Integrated Moving Average (ARIMA) model from statistics theory. We abbreviate the combined GM(1,1) ARIMA model as ARGM(1,1)…

Model Error Estimation for the CPTEC Eta Model

NASA Technical Reports Server (NTRS)

Tippett, Michael K.; daSilva, Arlindo

1999-01-01

Statistical data assimilation systems require the specification of forecast and observation error statistics. Forecast error is due to model imperfections and differences between the initial condition and the actual state of the atmosphere. Practical four-dimensional variational (4D-Var) methods try to fit the forecast state to the observations and assume that the model error is negligible. Here with a number of simplifying assumption, a framework is developed for isolating the model error given the forecast error at two lead-times. Two definitions are proposed for the Talagrand ratio tau, the fraction of the forecast error due to model error rather than initial condition error. Data from the CPTEC Eta Model running operationally over South America are used to calculate forecast error statistics and lower bounds for tau.

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

PubMed Central

Sager, Jennifer E.; Yu, Jingjing; Ragueneau-Majlessi, Isabelle

2015-01-01

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms “PBPK” and “physiologically based pharmacokinetic model” to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines. PMID:26296709

Bayesian Modeling of Exposure and Airflow Using Two-Zone Models

PubMed Central

Zhang, Yufen; Banerjee, Sudipto; Yang, Rui; Lungu, Claudiu; Ramachandran, Gurumurthy

2009-01-01

Mathematical modeling is being increasingly used as a means for assessing occupational exposures. However, predicting exposure in real settings is constrained by lack of quantitative knowledge of exposure determinants. Validation of models in occupational settings is, therefore, a challenge. Not only do the model parameters need to be known, the models also need to predict the output with some degree of accuracy. In this paper, a Bayesian statistical framework is used for estimating model parameters and exposure concentrations for a two-zone model. The model predicts concentrations in a zone near the source and far away from the source as functions of the toluene generation rate, air ventilation rate through the chamber, and the airflow between near and far fields. The framework combines prior or expert information on the physical model along with the observed data. The framework is applied to simulated data as well as data obtained from the experiments conducted in a chamber. Toluene vapors are generated from a source under different conditions of airflow direction, the presence of a mannequin, and simulated body heat of the mannequin. The Bayesian framework accounts for uncertainty in measurement as well as in the unknown rate of airflow between the near and far fields. The results show that estimates of the interzonal airflow are always close to the estimated equilibrium solutions, which implies that the method works efficiently. The predictions of near-field concentration for both the simulated and real data show nice concordance with the true values, indicating that the two-zone model assumptions agree with the reality to a large extent and the model is suitable for predicting the contaminant concentration. Comparison of the estimated model and its margin of error with the experimental data thus enables validation of the physical model assumptions. The approach illustrates how exposure models and information on model parameters together with the knowledge of

Comparison of chiller models for use in model-based fault detection

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

Sreedharan, Priya; Haves, Philip

Selecting the model is an important and essential step in model based fault detection and diagnosis (FDD). Factors that are considered in evaluating a model include accuracy, training data requirements, calibration effort, generality, and computational requirements. The objective of this study was to evaluate different modeling approaches for their applicability to model based FDD of vapor compression chillers. Three different models were studied: the Gordon and Ng Universal Chiller model (2nd generation) and a modified version of the ASHRAE Primary Toolkit model, which are both based on first principles, and the DOE-2 chiller model, as implemented in CoolTools{trademark}, which ismore » empirical. The models were compared in terms of their ability to reproduce the observed performance of an older, centrifugal chiller operating in a commercial office building and a newer centrifugal chiller in a laboratory. All three models displayed similar levels of accuracy. Of the first principles models, the Gordon-Ng model has the advantage of being linear in the parameters, which allows more robust parameter estimation methods to be used and facilitates estimation of the uncertainty in the parameter values. The ASHRAE Toolkit Model may have advantages when refrigerant temperature measurements are also available. The DOE-2 model can be expected to have advantages when very limited data are available to calibrate the model, as long as one of the previously identified models in the CoolTools library matches the performance of the chiller in question.« less

Equivalent Dynamic Models.

PubMed

Molenaar, Peter C M

2017-01-01

Equivalences of two classes of dynamic models for weakly stationary multivariate time series are discussed: dynamic factor models and autoregressive models. It is shown that exploratory dynamic factor models can be rotated, yielding an infinite set of equivalent solutions for any observed series. It also is shown that dynamic factor models with lagged factor loadings are not equivalent to the currently popular state-space models, and that restriction of attention to the latter type of models may yield invalid results. The known equivalent vector autoregressive model types, standard and structural, are given a new interpretation in which they are conceived of as the extremes of an innovating type of hybrid vector autoregressive models. It is shown that consideration of hybrid models solves many problems, in particular with Granger causality testing.

From Spiking Neuron Models to Linear-Nonlinear Models

PubMed Central

Ostojic, Srdjan; Brunel, Nicolas

2011-01-01

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates. PMID:21283777

From spiking neuron models to linear-nonlinear models.

PubMed

Ostojic, Srdjan; Brunel, Nicolas

2011-01-20

Neurons transform time-varying inputs into action potentials emitted stochastically at a time dependent rate. The mapping from current input to output firing rate is often represented with the help of phenomenological models such as the linear-nonlinear (LN) cascade, in which the output firing rate is estimated by applying to the input successively a linear temporal filter and a static non-linear transformation. These simplified models leave out the biophysical details of action potential generation. It is not a priori clear to which extent the input-output mapping of biophysically more realistic, spiking neuron models can be reduced to a simple linear-nonlinear cascade. Here we investigate this question for the leaky integrate-and-fire (LIF), exponential integrate-and-fire (EIF) and conductance-based Wang-Buzsáki models in presence of background synaptic activity. We exploit available analytic results for these models to determine the corresponding linear filter and static non-linearity in a parameter-free form. We show that the obtained functions are identical to the linear filter and static non-linearity determined using standard reverse correlation analysis. We then quantitatively compare the output of the corresponding linear-nonlinear cascade with numerical simulations of spiking neurons, systematically varying the parameters of input signal and background noise. We find that the LN cascade provides accurate estimates of the firing rates of spiking neurons in most of parameter space. For the EIF and Wang-Buzsáki models, we show that the LN cascade can be reduced to a firing rate model, the timescale of which we determine analytically. Finally we introduce an adaptive timescale rate model in which the timescale of the linear filter depends on the instantaneous firing rate. This model leads to highly accurate estimates of instantaneous firing rates.

Evaluation of Model Fit in Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Hu, Jinxiang; Miller, M. David; Huggins-Manley, Anne Corinne; Chen, Yi-Hsin

2016-01-01

Cognitive diagnosis models (CDMs) estimate student ability profiles using latent attributes. Model fit to the data needs to be ascertained in order to determine whether inferences from CDMs are valid. This study investigated the usefulness of some popular model fit statistics to detect CDM fit including relative fit indices (AIC, BIC, and CAIC),…

IHY Modeling Support at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Chulaki, A.; Hesse, Michael; Kuznetsova, Masha; MacNeice, P.; Rastaetter, L.

2005-01-01

The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. In particular, the CCMC provides to the research community the execution of "runs-onrequest" for specific events of interest to space science researchers. Through this activity and the concurrent development of advanced visualization tools, CCMC provides, to the general science community, unprecedented access to a large number of state-of-the-art research models. CCMC houses models that cover the entire domain from the Sun to the Earth. In this presentation, we will provide an overview of CCMC modeling services that are available to support activities during the International Heliospheric Year. In order to tailor CCMC activities to IHY needs, we will also invite community input into our IHY planning activities.

Energy modeling. Volume 2: Inventory and details of state energy models

NASA Astrophysics Data System (ADS)

Melcher, A. G.; Underwood, R. G.; Weber, J. C.; Gist, R. L.; Holman, R. P.; Donald, D. W.

1981-05-01

An inventory of energy models developed by or for state governments is presented, and certain models are discussed in depth. These models address a variety of purposes such as: supply or demand of energy or of certain types of energy; emergency management of energy; and energy economics. Ten models are described. The purpose, use, and history of the model is discussed, and information is given on the outputs, inputs, and mathematical structure of the model. The models include five models dealing with energy demand, one of which is econometric and four of which are econometric-engineering end-use models.

Resource utilization model for the algorithm to architecture mapping model

NASA Technical Reports Server (NTRS)

Stoughton, John W.; Patel, Rakesh R.

1993-01-01

The analytical model for resource utilization and the variable node time and conditional node model for the enhanced ATAMM model for a real-time data flow architecture are presented in this research. The Algorithm To Architecture Mapping Model, ATAMM, is a Petri net based graph theoretic model developed at Old Dominion University, and is capable of modeling the execution of large-grained algorithms on a real-time data flow architecture. Using the resource utilization model, the resource envelope may be obtained directly from a given graph and, consequently, the maximum number of required resources may be evaluated. The node timing diagram for one iteration period may be obtained using the analytical resource envelope. The variable node time model, which describes the change in resource requirement for the execution of an algorithm under node time variation, is useful to expand the applicability of the ATAMM model to heterogeneous architectures. The model also describes a method of detecting the presence of resource limited mode and its subsequent prevention. Graphs with conditional nodes are shown to be reduced to equivalent graphs with time varying nodes and, subsequently, may be analyzed using the variable node time model to determine resource requirements. Case studies are performed on three graphs for the illustration of applicability of the analytical theories.

Modeling of batch sorber system: kinetic, mechanistic, and thermodynamic modeling

NASA Astrophysics Data System (ADS)

Mishra, Vishal

2017-10-01

The present investigation has dealt with the biosorption of copper and zinc ions on the surface of egg-shell particles in the liquid phase. Various rate models were evaluated to elucidate the kinetics of copper and zinc biosorptions, and the results indicated that the pseudo-second-order model was more appropriate than the pseudo-first-order model. The curve of the initial sorption rate versus the initial concentration of copper and zinc ions also complemented the results of the pseudo-second-order model. Models used for the mechanistic modeling were the intra-particle model of pore diffusion and Bangham's model of film diffusion. The results of the mechanistic modeling together with the values of pore and film diffusivities indicated that the preferential mode of the biosorption of copper and zinc ions on the surface of egg-shell particles in the liquid phase was film diffusion. The results of the intra-particle model showed that the biosorption of the copper and zinc ions was not dominated by the pore diffusion, which was due to macro-pores with open-void spaces present on the surface of egg-shell particles. The thermodynamic modeling reproduced the fact that the sorption of copper and zinc was spontaneous, exothermic with the increased order of the randomness at the solid-liquid interface.

SWIFT MODELLER: a Java based GUI for molecular modeling.

PubMed

Mathur, Abhinav; Shankaracharya; Vidyarthi, Ambarish S

2011-10-01

MODELLER is command line argument based software which requires tedious formatting of inputs and writing of Python scripts which most people are not comfortable with. Also the visualization of output becomes cumbersome due to verbose files. This makes the whole software protocol very complex and requires extensive study of MODELLER manuals and tutorials. Here we describe SWIFT MODELLER, a GUI that automates formatting, scripting and data extraction processes and present it in an interactive way making MODELLER much easier to use than before. The screens in SWIFT MODELLER are designed keeping homology modeling in mind and their flow is a depiction of its steps. It eliminates the formatting of inputs, scripting processes and analysis of verbose output files through automation and makes pasting of the target sequence as the only prerequisite. Jmol (3D structure visualization tool) has been integrated into the GUI which opens and demonstrates the protein data bank files created by the MODELLER software. All files required and created by the software are saved in a folder named after the work instance's date and time of execution. SWIFT MODELLER lowers the skill level required for the software through automation of many of the steps in the original software protocol, thus saving an enormous amount of time per instance and making MODELLER very easy to work with.

Petroleum Market Model of the National Energy Modeling System

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

NONE

1997-01-01

The purpose of this report is to define the objectives of the Petroleum Market Model (PMM), describe its basic approach, and provide detail on how it works. This report is intended as a reference document for model analysts, users, and the public. The PMM models petroleum refining activities, the marketing of petroleum products to consumption regions. The production of natural gas liquids in gas processing plants, and domestic methanol production. The PMM projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil, both domestic and imported; other inputs including alcoholsmore » and ethers; natural gas plant liquids production; petroleum product imports; and refinery processing gain. In addition, the PMM estimates domestic refinery capacity expansion and fuel consumption. Product prices are estimated at the Census division level and much of the refining activity information is at the Petroleum Administration for Defense (PAD) District level. This report is organized as follows: Chapter 2, Model Purpose; Chapter 3, Model Overview and Rationale; Chapter 4, Model Structure; Appendix A, Inventory of Input Data, Parameter Estimates, and Model Outputs; Appendix B, Detailed Mathematical Description of the Model; Appendix C, Bibliography; Appendix D, Model Abstract; Appendix E, Data Quality; Appendix F, Estimation methodologies; Appendix G, Matrix Generator documentation; Appendix H, Historical Data Processing; and Appendix I, Biofuels Supply Submodule.« less

Model Hierarchies in Edge-Based Compartmental Modeling for Infectious Disease Spread

PubMed Central

Miller, Joel C.; Volz, Erik M.

2012-01-01

We consider the family of edge-based compartmental models for epidemic spread developed in [11]. These models allow for a range of complex behaviors, and in particular allow us to explicitly incorporate duration of a contact into our mathematical models. Our focus here is to identify conditions under which simpler models may be substituted for more detailed models, and in so doing we define a hierarchy of epidemic models. In particular we provide conditions under which it is appropriate to use the standard mass action SIR model, and we show what happens when these conditions fail. Using our hierarchy, we provide a procedure leading to the choice of the appropriate model for a given population. Our result about the convergence of models to the Mass Action model gives clear, rigorous conditions under which the Mass Action model is accurate. PMID:22911242

The Relationships between Modelling and Argumentation from the Perspective of the Model of Modelling Diagram

ERIC Educational Resources Information Center

Mendonça, Paula Cristina Cardoso; Justi, Rosária

2013-01-01

Some studies related to the nature of scientific knowledge demonstrate that modelling is an inherently argumentative process. This study aims at discussing the relationship between modelling and argumentation by analysing data collected during the modelling-based teaching of ionic bonding and intermolecular interactions. The teaching activities…

Multiscale Modeling of Structurally-Graded Materials Using Discrete Dislocation Plasticity Models and Continuum Crystal Plasticity Models

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.

2012-01-01

A multiscale modeling methodology that combines the predictive capability of discrete dislocation plasticity and the computational efficiency of continuum crystal plasticity is developed. Single crystal configurations of different grain sizes modeled with periodic boundary conditions are analyzed using discrete dislocation plasticity (DD) to obtain grain size-dependent stress-strain predictions. These relationships are mapped into crystal plasticity parameters to develop a multiscale DD/CP model for continuum level simulations. A polycrystal model of a structurally-graded microstructure is developed, analyzed and used as a benchmark for comparison between the multiscale DD/CP model and the DD predictions. The multiscale DD/CP model follows the DD predictions closely up to an initial peak stress and then follows a strain hardening path that is parallel but somewhat offset from the DD predictions. The difference is believed to be from a combination of the strain rate in the DD simulation and the inability of the DD/CP model to represent non-monotonic material response.

Modeling influenza-like illnesses through composite compartmental models

NASA Astrophysics Data System (ADS)

Levy, Nir; , Michael, Iv; Yom-Tov, Elad

2018-03-01

Epidemiological models for the spread of pathogens in a population are usually only able to describe a single pathogen. This makes their application unrealistic in cases where multiple pathogens with similar symptoms are spreading concurrently within the same population. Here we describe a method which makes possible the application of multiple single-strain models under minimal conditions. As such, our method provides a bridge between theoretical models of epidemiology and data-driven approaches for modeling of influenza and other similar viruses. Our model extends the Susceptible-Infected-Recovered model to higher dimensions, allowing the modeling of a population infected by multiple viruses. We further provide a method, based on an overcomplete dictionary of feasible realizations of SIR solutions, to blindly partition the time series representing the number of infected people in a population into individual components, each representing the effect of a single pathogen. We demonstrate the applicability of our proposed method on five years of seasonal influenza-like illness (ILI) rates, estimated from Twitter data. We demonstrate that our method describes, on average, 44% of the variance in the ILI time series. The individual infectious components derived from our model are matched to known viral profiles in the populations, which we demonstrate matches that of independently collected epidemiological data. We further show that the basic reproductive numbers (R 0) of the matched components are in range known for these pathogens. Our results suggest that the proposed method can be applied to other pathogens and geographies, providing a simple method for estimating the parameters of epidemics in a population.

Continuous system modeling

NASA Technical Reports Server (NTRS)

Cellier, Francois E.

1991-01-01

A comprehensive and systematic introduction is presented for the concepts associated with 'modeling', involving the transition from a physical system down to an abstract description of that system in the form of a set of differential and/or difference equations, and basing its treatment of modeling on the mathematics of dynamical systems. Attention is given to the principles of passive electrical circuit modeling, planar mechanical systems modeling, hierarchical modular modeling of continuous systems, and bond-graph modeling. Also discussed are modeling in equilibrium thermodynamics, population dynamics, and system dynamics, inductive reasoning, artificial neural networks, and automated model synthesis.

Agent-based modeling and systems dynamics model reproduction.

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

North, M. J.; Macal, C. M.

2009-01-01

Reproducibility is a pillar of the scientific endeavour. We view computer simulations as laboratories for electronic experimentation and therefore as tools for science. Recent studies have addressed model reproduction and found it to be surprisingly difficult to replicate published findings. There have been enough failed simulation replications to raise the question, 'can computer models be fully replicated?' This paper answers in the affirmative by reporting on a successful reproduction study using Mathematica, Repast and Swarm for the Beer Game supply chain model. The reproduction process was valuable because it demonstrated the original result's robustness across modelling methodologies and implementation environments.

National Transonic Facility model and model support vibration problems

NASA Technical Reports Server (NTRS)

Young, Clarence P., Jr.; Popernack, Thomas G., Jr.; Gloss, Blair B.

1990-01-01

Vibrations of models and model support system were encountered during testing in the National Transonic Facility. Model support system yaw plane vibrations have resulted in model strain gage balance design load limits being reached. These high levels of vibrations resulted in limited aerodynamic testing for several wind tunnel models. The yaw vibration problem was the subject of an intensive experimental and analytical investigation which identified the primary source of the yaw excitation and resulted in attenuation of the yaw oscillations to acceptable levels. This paper presents the principal results of analyses and experimental investigation of the yaw plane vibration problems. Also, an overview of plans for development and installation of a permanent model system dynamic and aeroelastic response measurement and monitoring system for the National Transonic Facility is presented.

An improved interfacial bonding model for material interface modeling

PubMed Central

Lin, Liqiang; Wang, Xiaodu; Zeng, Xiaowei

2016-01-01

An improved interfacial bonding model was proposed from potential function point of view to investigate interfacial interactions in polycrystalline materials. It characterizes both attractive and repulsive interfacial interactions and can be applied to model different material interfaces. The path dependence of work-of-separation study indicates that the transformation of separation work is smooth in normal and tangential direction and the proposed model guarantees the consistency of the cohesive constitutive model. The improved interfacial bonding model was verified through a simple compression test in a standard hexagonal structure. The error between analytical solutions and numerical results from the proposed model is reasonable in linear elastic region. Ultimately, we investigated the mechanical behavior of extrafibrillar matrix in bone and the simulation results agreed well with experimental observations of bone fracture. PMID:28584343

A multi-model assessment of terrestrial biosphere model data needs

NASA Astrophysics Data System (ADS)

Gardella, A.; Cowdery, E.; De Kauwe, M. G.; Desai, A. R.; Duveneck, M.; Fer, I.; Fisher, R.; Knox, R. G.; Kooper, R.; LeBauer, D.; McCabe, T.; Minunno, F.; Raiho, A.; Serbin, S.; Shiklomanov, A. N.; Thomas, A.; Walker, A.; Dietze, M.

2017-12-01

Terrestrial biosphere models provide us with the means to simulate the impacts of climate change and their uncertainties. Going beyond direct observation and experimentation, models synthesize our current understanding of ecosystem processes and can give us insight on data needed to constrain model parameters. In previous work, we leveraged the Predictive Ecosystem Analyzer (PEcAn) to assess the contribution of different parameters to the uncertainty of the Ecosystem Demography model v2 (ED) model outputs across various North American biomes (Dietze et al., JGR-G, 2014). While this analysis identified key research priorities, the extent to which these priorities were model- and/or biome-specific was unclear. Furthermore, because the analysis only studied one model, we were unable to comment on the effect of variability in model structure to overall predictive uncertainty. Here, we expand this analysis to all biomes globally and a wide sample of models that vary in complexity: BioCro, CABLE, CLM, DALEC, ED2, FATES, G'DAY, JULES, LANDIS, LINKAGES, LPJ-GUESS, MAESPA, PRELES, SDGVM, SIPNET, and TEM. Prior to performing uncertainty analyses, model parameter uncertainties were assessed by assimilating all available trait data from the combination of the BETYdb and TRY trait databases, using an updated multivariate version of PEcAn's Hierarchical Bayesian meta-analysis. Next, sensitivity analyses were performed for all models across a range of sites globally to assess sensitivities for a range of different outputs (GPP, ET, SH, Ra, NPP, Rh, NEE, LAI) at multiple time scales from the sub-annual to the decadal. Finally, parameter uncertainties and model sensitivities were combined to evaluate the fractional contribution of each parameter to the predictive uncertainty for a specific variable at a specific site and timescale. Facilitated by PEcAn's automated workflows, this analysis represents the broadest assessment of the sensitivities and uncertainties in terrestrial

Coupled atmosphere-biophysics-hydrology models for environmental modeling

USGS Publications Warehouse

Walko, R.L.; Band, L.E.; Baron, Jill S.; Kittel, T.G.F.; Lammers, R.; Lee, T.J.; Ojima, D.; Pielke, R.A.; Taylor, C.; Tague, C.; Tremback, C.J.; Vidale, P.L.

2000-01-01

The formulation and implementation of LEAF-2, the Land Ecosystem–Atmosphere Feedback model, which comprises the representation of land–surface processes in the Regional Atmospheric Modeling System (RAMS), is described. LEAF-2 is a prognostic model for the temperature and water content of soil, snow cover, vegetation, and canopy air, and includes turbulent and radiative exchanges between these components and with the atmosphere. Subdivision of a RAMS surface grid cell into multiple areas of distinct land-use types is allowed, with each subgrid area, or patch, containing its own LEAF-2 model, and each patch interacts with the overlying atmospheric column with a weight proportional to its fractional area in the grid cell. A description is also given of TOPMODEL, a land hydrology model that represents surface and subsurface downslope lateral transport of groundwater. Details of the incorporation of a modified form of TOPMODEL into LEAF-2 are presented. Sensitivity tests of the coupled system are presented that demonstrate the potential importance of the patch representation and of lateral water transport in idealized model simulations. Independent studies that have applied LEAF-2 and verified its performance against observational data are cited. Linkage of RAMS and TOPMODEL through LEAF-2 creates a modeling system that can be used to explore the coupled atmosphere–biophysical–hydrologic response to altered climate forcing at local watershed and regional basin scales.

Modeling fractal cities using the correlated percolation model.

NASA Astrophysics Data System (ADS)

Makse, Hernán A.; Havlin, Shlomo; Stanley, H. Eugene

1996-03-01

Cities grow in a way that might be expected to resemble the growth of two-dimensional aggregates of particles, and this has led to recent attempts to model urban growth using ideas from the statistical physics of clusters. In particular, the model of diffusion limited aggregation (DLA) has been invoked to rationalize the apparently fractal nature of urban morphologies(M. Batty and P. Longley, Fractal Cities) (Academic, San Diego, 1994). The DLA model predicts that there should exist only one large fractal cluster, which is almost perfectly screened from incoming 'development units' (representing, for example, people, capital or resources), so that almost all of the cluster growth takes place at the tips of the cluster's branches. We show that an alternative model(H. A. Makse, S. Havlin, H. E. Stanley, Nature 377), 608 (1995), in which development units are correlated rather than being added to the cluster at random, is better able to reproduce the observed morphology of cities and the area distribution of sub-clusters ('towns') in an urban system, and can also describe urban growth dynamics. Our physical model, which corresponds to the correlated percolation model in the presence of a density gradient, is motivated by the fact that in urban areas development attracts further development. The model offers the possibility of predicting the global properties (such as scaling behavior) of urban morphologies.

Competency Modeling in Extension Education: Integrating an Academic Extension Education Model with an Extension Human Resource Management Model

ERIC Educational Resources Information Center

Scheer, Scott D.; Cochran, Graham R.; Harder, Amy; Place, Nick T.

2011-01-01

The purpose of this study was to compare and contrast an academic extension education model with an Extension human resource management model. The academic model of 19 competencies was similar across the 22 competencies of the Extension human resource management model. There were seven unique competencies for the human resource management model.…

Phoenix model

EPA Science Inventory

Phoenix (formerly referred to as the Second Generation Model or SGM) is a global general equilibrium model designed to analyze energy-economy-climate related questions and policy implications in the medium- to long-term. This model disaggregates the global economy into 26 industr...

BioModels Database: a repository of mathematical models of biological processes.

PubMed

Chelliah, Vijayalakshmi; Laibe, Camille; Le Novère, Nicolas

2013-01-01

BioModels Database is a public online resource that allows storing and sharing of published, peer-reviewed quantitative, dynamic models of biological processes. The model components and behaviour are thoroughly checked to correspond the original publication and manually curated to ensure reliability. Furthermore, the model elements are annotated with terms from controlled vocabularies as well as linked to relevant external data resources. This greatly helps in model interpretation and reuse. Models are stored in SBML format, accepted in SBML and CellML formats, and are available for download in various other common formats such as BioPAX, Octave, SciLab, VCML, XPP and PDF, in addition to SBML. The reaction network diagram of the models is also available in several formats. BioModels Database features a search engine, which provides simple and more advanced searches. Features such as online simulation and creation of smaller models (submodels) from the selected model elements of a larger one are provided. BioModels Database can be accessed both via a web interface and programmatically via web services. New models are available in BioModels Database at regular releases, about every 4 months.

A Smart Modeling Framework for Integrating BMI-enabled Models as Web Services

NASA Astrophysics Data System (ADS)

Jiang, P.; Elag, M.; Kumar, P.; Peckham, S. D.; Liu, R.; Marini, L.; Hsu, L.

2015-12-01

Serviced-oriented computing provides an opportunity to couple web service models using semantic web technology. Through this approach, models that are exposed as web services can be conserved in their own local environment, thus making it easy for modelers to maintain and update the models. In integrated modeling, the serviced-oriented loose-coupling approach requires (1) a set of models as web services, (2) the model metadata describing the external features of a model (e.g., variable name, unit, computational grid, etc.) and (3) a model integration framework. We present the architecture of coupling web service models that are self-describing by utilizing a smart modeling framework. We expose models that are encapsulated with CSDMS (Community Surface Dynamics Modeling System) Basic Model Interfaces (BMI) as web services. The BMI-enabled models are self-describing by uncovering models' metadata through BMI functions. After a BMI-enabled model is serviced, a client can initialize, execute and retrieve the meta-information of the model by calling its BMI functions over the web. Furthermore, a revised version of EMELI (Peckham, 2015), an Experimental Modeling Environment for Linking and Interoperability, is chosen as the framework for coupling BMI-enabled web service models. EMELI allows users to combine a set of component models into a complex model by standardizing model interface using BMI as well as providing a set of utilities smoothing the integration process (e.g., temporal interpolation). We modify the original EMELI so that the revised modeling framework is able to initialize, execute and find the dependencies of the BMI-enabled web service models. By using the revised EMELI, an example will be presented on integrating a set of topoflow model components that are BMI-enabled and exposed as web services. Reference: Peckham, S.D. (2014) EMELI 1.0: An experimental smart modeling framework for automatic coupling of self-describing models, Proceedings of HIC 2014

Orbital Debris Modeling

NASA Technical Reports Server (NTRS)

Liou, J. C.

2012-01-01

Presentation outlne: (1) The NASA Orbital Debris (OD) Engineering Model -- A mathematical model capable of predicting OD impact risks for the ISS and other critical space assets (2) The NASA OD Evolutionary Model -- A physical model capable of predicting future debris environment based on user-specified scenarios (3) The NASA Standard Satellite Breakup Model -- A model describing the outcome of a satellite breakup (explosion or collision)

Combining abiotic and biotic models - Hydraulical modeling to fill the gap between catchment and hydro-dynamic models

NASA Astrophysics Data System (ADS)

Guse, B.; Sulc, D.; Schmalz, B.; Fohrer, N.

2012-04-01

The European Water Framework Directive (WFD) requires a catchment-based approach, which is assessed in the IMPACT project by combining abiotic and biotic models. The core point of IMPACT is a model chain (catchment model -> 1-D-hydraulic model -> 3-D-hydro-morphodynamic model -> biotic habitat model) with the aim to estimate the occurrence of the target species of the WFD. Firstly, the model chain is developed for the current land use and climate conditions. Secondly, land use and climate change scenarios are developed at the catchment scale. The outputs of the catchment model for the scenarios are used as input for the next models within the model chain to estimate the effect of these changes on the target species. The eco-hydrological catchment model SWAT is applied for the Treene catchment in Northern Germany and delivers discharge and water quality parameters as a spatial explicit output for each subbasin. There is no water level information given by SWAT. However, water level values are needed as lower boundary condition for the hydro-dynamic and habitat models which are applied for the 300 m candidate reference reach. In order to fill the gap between the catchment and the hydro-morphodynamic model, the 1-D hydraulic model HEC-RAS is applied for a 3 km long reach transect from the next upstream hydrological station until the upper bound of the candidate study reach. The channel geometry for HEC-RAS was estimated based on 96 cross-sections which were measured in the IMPACT project. By using available discharge and water level measurements from the hydrological station and own flow velocity measurements, the channel resistence was estimated. HEC-RAS was run with different statistical indices (mean annual drought, mean discharge, …) for steady flow conditions. The rating curve was then constructed for the target cross-section, i.e. the lower bound of the candidate study reach, to fulfill the combining with the hydro- and morphodynamic models. These statistical

Multilevel Model Prediction

ERIC Educational Resources Information Center

Frees, Edward W.; Kim, Jee-Seon

2006-01-01

Multilevel models are proven tools in social research for modeling complex, hierarchical systems. In multilevel modeling, statistical inference is based largely on quantification of random variables. This paper distinguishes among three types of random variables in multilevel modeling--model disturbances, random coefficients, and future response…

Model verification of large structural systems. [space shuttle model response

NASA Technical Reports Server (NTRS)

Lee, L. T.; Hasselman, T. K.

1978-01-01

A computer program for the application of parameter identification on the structural dynamic models of space shuttle and other large models with hundreds of degrees of freedom is described. Finite element, dynamic, analytic, and modal models are used to represent the structural system. The interface with math models is such that output from any structural analysis program applied to any structural configuration can be used directly. Processed data from either sine-sweep tests or resonant dwell tests are directly usable. The program uses measured modal data to condition the prior analystic model so as to improve the frequency match between model and test. A Bayesian estimator generates an improved analytical model and a linear estimator is used in an iterative fashion on highly nonlinear equations. Mass and stiffness scaling parameters are generated for an improved finite element model, and the optimum set of parameters is obtained in one step.

Modeling Operations Other Than War: Non-Combatants in Combat Modeling

DTIC Science & Technology

1994-09-01

supposition that non-combatants are an essential feature in OOTW. The model proposal includes a methodology for civilian unit decision making . The model...combatants are an essential feature in OOTW. The model proposal includes a methodology for civilian unit decision making . Thi- model also includes...numerical example demonstrated that the model appeared to perform in an acceptable manner, in that it produced output within a reasonable range. During the

Dynamic Metabolic Model Building Based on the Ensemble Modeling Approach

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

Liao, James C.

2016-10-01

Ensemble modeling of kinetic systems addresses the challenges of kinetic model construction, with respect to parameter value selection, and still allows for the rich insights possible from kinetic models. This project aimed to show that constructing, implementing, and analyzing such models is a useful tool for the metabolic engineering toolkit, and that they can result in actionable insights from models. Key concepts are developed and deliverable publications and results are presented.

Inverse models: A necessary next step in ground-water modeling

USGS Publications Warehouse

Poeter, E.P.; Hill, M.C.

1997-01-01

Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares repression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.Inverse models using, for example, nonlinear least-squares regression, provide capabilities that help modelers take full advantage of the insight available from ground-water models. However, lack of information about the requirements and benefits of inverse models is an obstacle to their widespread use. This paper presents a simple ground-water flow problem to illustrate the requirements and benefits of the nonlinear least-squares regression method of inverse modeling and discusses how these attributes apply to field problems. The benefits of inverse modeling include: (1) expedited determination of best fit parameter values; (2) quantification of the (a) quality of calibration, (b) data shortcomings and needs, and (c) confidence limits on parameter estimates and predictions; and (3) identification of issues that are easily overlooked during nonautomated calibration.

Volcanic ash modeling with the NMMB-MONARCH-ASH model: quantification of offline modeling errors

NASA Astrophysics Data System (ADS)

Marti, Alejandro; Folch, Arnau

2018-03-01

Volcanic ash modeling systems are used to simulate the atmospheric dispersion of volcanic ash and to generate forecasts that quantify the impacts from volcanic eruptions on infrastructures, air quality, aviation, and climate. The efficiency of response and mitigation actions is directly associated with the accuracy of the volcanic ash cloud detection and modeling systems. Operational forecasts build on offline coupled modeling systems in which meteorological variables are updated at the specified coupling intervals. Despite the concerns from other communities regarding the accuracy of this strategy, the quantification of the systematic errors and shortcomings associated with the offline modeling systems has received no attention. This paper employs the NMMB-MONARCH-ASH model to quantify these errors by employing different quantitative and categorical evaluation scores. The skills of the offline coupling strategy are compared against those from an online forecast considered to be the best estimate of the true outcome. Case studies are considered for a synthetic eruption with constant eruption source parameters and for two historical events, which suitably illustrate the severe aviation disruptive effects of European (2010 Eyjafjallajökull) and South American (2011 Cordón Caulle) volcanic eruptions. Evaluation scores indicate that systematic errors due to the offline modeling are of the same order of magnitude as those associated with the source term uncertainties. In particular, traditional offline forecasts employed in operational model setups can result in significant uncertainties, failing to reproduce, in the worst cases, up to 45-70 % of the ash cloud of an online forecast. These inconsistencies are anticipated to be even more relevant in scenarios in which the meteorological conditions change rapidly in time. The outcome of this paper encourages operational groups responsible for real-time advisories for aviation to consider employing computationally

Pharmacokinetic modeling in aquatic animals. 1. Models and concepts

USGS Publications Warehouse

Barron, M.G.; Stehly, Guy R.; Hayton, W.L.

1990-01-01

While clinical and toxicological applications of pharmacokinetics have continued to evolve both conceptually and experimentally, pharmacokinetics modeling in aquatic animals has not progressed accordingly. In this paper we present methods and concepts of pharmacokinetic modeling in aquatic animals using multicompartmental, clearance-based, non-compartmental and physiologically-based pharmacokinetic models. These models should be considered as alternatives to traditional approaches, which assume that the animal acts as a single homogeneous compartment based on apparent monoexponential elimination.

Bootstrap-after-bootstrap model averaging for reducing model uncertainty in model selection for air pollution mortality studies.

PubMed

Roberts, Steven; Martin, Michael A

2010-01-01

Concerns have been raised about findings of associations between particulate matter (PM) air pollution and mortality that have been based on a single "best" model arising from a model selection procedure, because such a strategy may ignore model uncertainty inherently involved in searching through a set of candidate models to find the best model. Model averaging has been proposed as a method of allowing for model uncertainty in this context. To propose an extension (double BOOT) to a previously described bootstrap model-averaging procedure (BOOT) for use in time series studies of the association between PM and mortality. We compared double BOOT and BOOT with Bayesian model averaging (BMA) and a standard method of model selection [standard Akaike's information criterion (AIC)]. Actual time series data from the United States are used to conduct a simulation study to compare and contrast the performance of double BOOT, BOOT, BMA, and standard AIC. Double BOOT produced estimates of the effect of PM on mortality that have had smaller root mean squared error than did those produced by BOOT, BMA, and standard AIC. This performance boost resulted from estimates produced by double BOOT having smaller variance than those produced by BOOT and BMA. Double BOOT is a viable alternative to BOOT and BMA for producing estimates of the mortality effect of PM.

A Generic Modeling Process to Support Functional Fault Model Development

NASA Technical Reports Server (NTRS)

Maul, William A.; Hemminger, Joseph A.; Oostdyk, Rebecca; Bis, Rachael A.

2016-01-01

Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

Global Analysis, Interpretation and Modelling: An Earth Systems Modelling Program

NASA Technical Reports Server (NTRS)

Moore, Berrien, III; Sahagian, Dork

1997-01-01

The Goal of the GAIM is: To advance the study of the coupled dynamics of the Earth system using as tools both data and models; to develop a strategy for the rapid development, evaluation, and application of comprehensive prognostic models of the Global Biogeochemical Subsystem which could eventually be linked with models of the Physical-Climate Subsystem; to propose, promote, and facilitate experiments with existing models or by linking subcomponent models, especially those associated with IGBP Core Projects and with WCRP efforts. Such experiments would be focused upon resolving interface issues and questions associated with developing an understanding of the prognostic behavior of key processes; to clarify key scientific issues facing the development of Global Biogeochemical Models and the coupling of these models to General Circulation Models; to assist the Intergovernmental Panel on Climate Change (IPCC) process by conducting timely studies that focus upon elucidating important unresolved scientific issues associated with the changing biogeochemical cycles of the planet and upon the role of the biosphere in the physical-climate subsystem, particularly its role in the global hydrological cycle; and to advise the SC-IGBP on progress in developing comprehensive Global Biogeochemical Models and to maintain scientific liaison with the WCRP Steering Group on Global Climate Modelling.