Characteristics and source apportionment of PM2.5 during persistent extreme haze events in Chengdu, southwest China.

PubMed

Li, Lulu; Tan, Qinwen; Zhang, Yuanhang; Feng, Miao; Qu, Yu; An, Junling; Liu, Xingang

2017-11-01

Based on detailed data from Chengdu Plain (CP) from 6 January to 16 January, two typical haze episodes were analyzed to clarify the haze formation mechanism in winter. Weather conditions, chemical compositions, secondary pollutant transformation, optical properties of aerosols, the potential source contribution function (PSCF) and source apportionment were studied. The planetary boundary layer (PBL) height decreased distinctly during the haze episodes and restrained air pollutant vertical dispersion. As the haze worsened, the value of PBL × PM 2.5 increased notably. The [NO 3 - ]/[SO 4 2- ] ratio was 0.61, 0.76 and 0.88 during a non-haze period, episode 1 and episode 2, respectively, indicating that the mobile source of the air pollution is increasingly predominant in Chengdu. Water vapor also played a vital role in the formation of haze by accelerating the chemical transformation of secondary pollutants, leading to the hygroscopic growth of aerosols. The PSCF and backward trajectories of the air masses indicated that the pollution mainly came from the south. The secondary inorganic aerosols, vehicle emissions, coal combustion, biomass burning, industry, and dust contributed 34.1%, 24.1%, 12.7%, 12.3%, 7.6%, and 7.2% to PM 2.5 masses in episode 1 and 28.9%, 23.1%, 9.4%, 9.5%, 20.3% and 7.5% in episode 2. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ambient PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) in Changhua County, central Taiwan: Seasonal variation, source apportionment and cancer risk assessment.

PubMed

Chen, Yu-Cheng; Chiang, Hung-Che; Hsu, Chin-Yu; Yang, Tzu-Ting; Lin, Tzu-Yu; Chen, Mu-Jean; Chen, Nai-Tzu; Wu, Yuh-Shen

2016-11-01

This study investigates PM 2.5 -bound PAHs for rural sites (Dacheng and Fangyuan) positioned close to heavy air-polluting industries in Changhua County, central Taiwan. A total of 113 PM 2.5 samples with 22 PAHs collected from 2014 to 2015 were analyzed, and Positive Matrix Factorization (PMF) and diagnostic ratios of PAHs were applied to quantify potential PAH sources. The influences of local and regional sources were also explored using the conditional probability function (CPF) and potential source contribution function (PSCF) with PMF-modeled results, respectively. Annual mean concentrations of total PAHs were 2.91 ± 1.34 and 3.04 ± 1.40 ng/m 3 for Dacheng and Fangyuan, respectively, and their corresponding BaP eq were measured at 0.534 ± 0.255 and 0.563 ± 0.273 ng/m 3 in concentration. Seasonal variations with higher PAHs found for the winter than for the spring and summer were observed for both sites. The lifetime excess cancer risk (ECR) from inhalation exposure to PAHs was recorded as 4.7 × 10 -5 overall. Potential sources of PM 2.5 -bound PAHs include unburned petroleum and traffic emissions (42%), steel industry and coal combustion (31%), and petroleum and oil burning (27%), and unburned petroleum and traffic emission could contribute the highest ECR (2.4 × 10 -5 ). The CPF results show that directional apportionment patterns were consistent with the actual locations of local PAH sources. The PSCF results indicate that mainly northeastern regions of China have contributed elevated PM 2.5 -bound PAHs from long-range transports. Copyright © 2016 Elsevier Ltd. All rights reserved.

Disentangling the major source areas for an intense aerosol advection in the Central Mediterranean on the basis of Potential Source Contribution Function modeling of chemical and size distribution measurements

NASA Astrophysics Data System (ADS)

Petroselli, Chiara; Crocchianti, Stefano; Moroni, Beatrice; Castellini, Silvia; Selvaggi, Roberta; Nava, Silvia; Calzolai, Giulia; Lucarelli, Franco; Cappelletti, David

2018-05-01

In this paper, we combined a Potential Source Contribution Function (PSCF) analysis of daily chemical aerosol composition data with hourly aerosol size distributions with the aim to disentangle the major source areas during a complex and fast modulating advection event impacting on Central Italy in 2013. Chemical data include an ample set of metals obtained by Proton Induced X-ray Emission (PIXE), main soluble ions from ionic chromatography and elemental and organic carbon (EC, OC) obtained by thermo-optical measurements. Size distributions have been recorded with an optical particle counter for eight calibrated size classes in the 0.27-10 μm range. We demonstrated the usefulness of the approach by the positive identification of two very different source areas impacting during the transport event. In particular, biomass burning from Eastern Europe and desert dust from Sahara sources have been discriminated based on both chemistry and size distribution time evolution. Hourly BT provided the best results in comparison to 6 h or 24 h based calculations.

Indicators reflecting local and transboundary sources of PM2.5 and PMCOARSE in Rome - Impacts in air quality

NASA Astrophysics Data System (ADS)

Dimitriou, Konstantinos; Kassomenos, Pavlos

2014-10-01

The keystone of this paper was to calculate and interpret indicators reflecting sources and air quality impacts of PM2.5 and PMCOARSE (PM10-PM2.5) in Rome (Italy), focusing on potential exogenous influences. A backward atmospheric trajectory cluster analysis was implemented. The likelihood of daily PM10 exceedances was studied in conjunction with atmospheric patterns, whereas a Potential Source Contribution Function (PSCF) based on air mass residence time was deployed on a grid of a 0.5° × 0.5° resolution. Higher PM2.5 concentrations were associated with short/medium range airflows originated from Balkan Peninsula, whereas potential PMCOARSE sources were localized across the Mediterranean and coastal North Africa, due to dust and sea spray transportation. According to the outcome of a daily Pollution Index (PI), a slightly increased degradation of air quality is induced due to the additional quantity of exogenous PM but nevertheless, average levels of PI in all trajectory clusters belong in the low pollution category. Gaseous and particulate pollutants were also elaborated by a Principal Component Analysis (PCA), which produced 4 components: [Traffic], [photochemical], [residential] and [Secondary Coarse Aerosol], reflecting local sources of air pollution. PM2.5 levels were strongly associated with traffic, whereas PMCOARSE were produced autonomously by secondary sources.

Source regions and transport pathways of PM2.5 at a regional background site in East China

NASA Astrophysics Data System (ADS)

Zhang, Yanru; Zhang, Hongliang; Deng, Junjun; Du, Wenjiao; Hong, Youwei; Xu, Lingling; Qiu, Yuqing; Hong, Zhenyu; Wu, Xin; Ma, Qianli; Yao, Jie; Chen, Jinsheng

2017-10-01

PM2.5 samples were collected daily at the Lin'an regional background station (LA) in Zhejiang, China during 2014-2015 and the major chemical components including organic carbon (OC), elemental carbon (EC) and water-soluble inorganic ions (WSII) were determined. Backward trajectory clustering and potential source contribution function (PSCF) were adopted for identifying the transport pathways and potential source regions of PM2.5 at LA. The annual mean concentration was 68.9 ± 28.3 μg m-3, indicating severe pollution in East China. Obvious seasonal variations were found, with highest level in winter and lowest in summer. Carbonaceous aerosols and WSII were the predominant compositions, accounting for 30.7% and 53.5% of PM2.5, respectively. Secondary inorganic ions (SO42-, NO3-, and NH4+) made a total contribution of 45.2% to PM2.5. Heterogeneous formation played a dominant role in SO42- formation and NH4+ formation promoted NO3- formation. Stationary sources played a more important role than mobile sources based on NO3-/SO42- ratio of 0.53. Aerosol environment at LA was ammonium-poor and SO42- was only neutralized sufficiently by NH4+ with the predominant production of (NH4)2SO4 in winter. Four major transport pathways of air masses at LA were found based on trajectory clustering. Air masses from the northwest Gobi areas passing over the heavily polluted regions in North and Central China had the highest levels of PM2.5, followed by the air masses from Central China. PSCF results suggested that surrounding areas in the Yangtze River Delta region were major regional origins of PM2.5 and its major components. Northern region was an important origin for carbonaceous components, and southwestern region was significant for secondary inorganic ions. This study helps understand PM2.5 characteristics, identify potential source regions and effectively control PM2.5 in East China.

Atmospheric mercury (Hg) in the Adirondacks: Concentrations and sources

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

Hyun-Deok Choi; Thomas M. Holsen; Philip K. Hopke

2008-08-15

Hourly averaged gaseous elemental Hg (GEM) concentrations and hourly integrated reactive gaseous Hg (RGM), and particulate Hg (HgP) concentrations in the ambient air were measured at Huntington Forest in the Adirondacks, New York from June 2006 to May 2007. The average concentrations of GEM, RGM, and HgP were 1.4 {+-} 0.4 ng m{sup -3}, 1.8 {+-} 2.2 pg m{sup -3}, and 3.2 {+-} 3.7 pg m{sup -3}, respectively. RGM represents <3.5% of total atmospheric Hg or total gaseous Hg (TGM: GEM + RGM) and HgP represents <3.0% of the total atmospheric Hg. The highest mean concentrations of GEM, RGM, andmore » HgP were measured during winter and summer whereas the lowest mean concentrations were measured during spring and fall. Significant diurnal patterns were apparent in warm seasons for all species whereas diurnal patterns were weak in cold seasons. RGM was better correlated with ozone concentration and temperature in both warm than the other species. Potential source contribution function (PSCF) analysis was applied to identify possible Hg sources. This method identified areas in Pennsylvania, West Virginia, Ohio, Kentucky, Texas, Indiana, and Missouri, which coincided well with sources reported in a 2002 U.S. mercury emissions inventory. 51 refs., 7 figs., 1 tab.« less

Transport pathway and source area for Artemisia pollen in Beijing, China

NASA Astrophysics Data System (ADS)

Qin, Xiaoxin; Li, Yiyin; Sun, Xu; Meng, Ling; Wang, Xiaoke

2017-12-01

Artemisia pollen is an important allergen responsible for allergic rhinitis in Beijing, China. To explore the transport pathways and source areas of Artemisia pollen, we used Burkard 7-day traps to monitor daily pollen concentrations in 2016 in an urban and suburban locality. Backward trajectories of 24- and 96-h and their cluster analysis were performed to identify transport pathways of Artemisia pollen using the HYSPLIT model on 0.5° × 0.5° GADS meteorological data. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were calculated to further identify the major potential source areas at local, regional, and long-range scales. Our results showed significant differences in Artemisia pollen concentration between urban and suburban areas, attributed to differences in plant distribution and altitude of the sampling locality. Such differences arisen from both pollen emission and air mass movements, hence pollen dispersal. At local or regional scales, source area of northwestern parts of Beijing City, Hebei Province and northern and northwestern parts of Inner Mongolia influenced the major transport pathways of Artemisia pollen. Transport pathway at a long-range scale and its corresponding source area extended to northwestern parts of Mongolia. The regional-scale transport affected by wind and altitude is more profound for Artemisia pollen at the suburban than at the urban station.

Identification of source locations for atmospheric dry deposition of heavy metals during yellow-sand events in Seoul, Korea in 1998 using hybrid receptor models

NASA Astrophysics Data System (ADS)

Han, Young-Ji; Holsen, Thomas M.; Hopke, Philip K.; Cheong, Jang-Pyo; Kim, Ho; Yi, Seung-Muk

2004-10-01

Elemental dry deposition fluxes were measured using dry deposition plates from March to June 1998 in Seoul, Korea. During this spring sampling period several yellow-sand events characterized by long-range transport from China and Mongolia impacted the area. Understanding the impact of yellow-sand events on atmospheric dry deposition is critical to managing the heavy metal levels in the environment in Korea. In this study, the measured flux of a primarily crustal metal, Al and an anthropogenic metal, Pb was used with two hybrid receptor models, potential source contribution function (PSCF) and residence time weighted concentration (RTWC) for locating sources of heavy metals associated with atmospheric dry deposition fluxes during the yellow-sand events in Seoul, Korea. The PSCF using a criterion value of the 75th percentile of the measured dry deposition fluxes and RTWC results using the measured elemental dry deposition fluxes agreed well and consistently showed that there were large potential source areas in the Gobi Desert in China and Mongolia and industrial areas near Tianjin, Tangshan, and Shenyang in China. Major industrial areas of Shenyang, Fushun, and Anshan, the Central China loess plateau, the Gobi Desert, and the Alashan semi-desert in China were identified to be major source areas for the measured Pb flux in Seoul, Korea. For Al, the main industrial areas of Tangshan, Tianjin and Beijing, the Gobi Desert, the Alashan semi-desert, and the Central China loess plateau were found to be the major source areas. These results indicate that both anthropogenic sources such as industrial areas and natural sources such as deserts contribute to the high dry deposition fluxes of both Pb and Al in Seoul, Korea during yellow-sand events. RTWC resolved several high potential source areas. Modeling results indicated that the long-range transport of Al and Pb from China during yellow-sand events as well as non-yellow-sand spring daytimes increased atmospheric dry deposition of heavy metals in Korea.

Distribution and sources of particulate mercury and other trace elements in PM2.5 and PM10 atop Mount Tai, China.

PubMed

Qie, Guanghao; Wang, Yan; Wu, Chen; Mao, Huiting; Zhang, Ping; Li, Tao; Li, Yaxin; Talbot, Robert; Hou, Chenxiao; Yue, Taixing

2018-06-01

The concentrations of particulate mercury (PHg) and other trace elements in PM 2.5 and PM 10 in the atmosphere were measured at the summit of Mount Tai during the time period of 15 June - 11 August 2015. The average PHg concentrations were 83.33 ± 119.1 pg/m 3 for PM 2.5 and 174.92 ± 210.5 pg/m 3 for PM 10 . Average concentrations for other trace elements, including Al, Ca, Fe, K, Mg, Na, Pb, As, Se, Cu, Cd, Cr, V, Mo, Co, Ag, Ba, Mn, Zn and Ni ranged from 0.06 ng/m 3 (Ag) to 354.33 ng/m 3 (Ca) in PM 2.5 and 0.11 ng/m 3 (Co) to 592.66 ng/m 3 (Ca) in PM 10 . The average concentrations of PHg were higher than those at other domestic mountain sites and cities in other counties, lower than those at domestic city sites. Other trace elements showed concentrations lower than those at the domestic mountain sites. Due possibly to increased control of emissions and the proportion of new energy, the PHg and trace element concentrations decreased, but the PHg showed concentrations higher than those at the Mountain sites, this showed that the reasons was not only severely affected by anthropogenic emissions, but also associated with other sources. The concentration changed trend of the main trace elements indicated that PHg, trace elements and particle matters present positive correlation and fine particulate matter has a greater surface area which was conductive to adsorption of Hg and trace elements to particles. On June 19, June 27 and July 6, according to the peak of mercury and trace elements, we can predict the potential sources of these three days. The results of principal component analysis (PCA) suggested that, crustal dust, coal combustion, and vehicle emissions were the main emission sources of PHg and other trace elements in Mount Tai. The 24-h backward trajectories and potential source contribution function (PSCF) analysis revealed that air masses arriving at Mount Tai were mainly affected by Shandong province. Mount Tai was subjected to five main airflow trajectories. Clusters 1, 2, 3, and 5 represented four pathways for local and regional sources and cluster 4 originated long-distance transportation. Central Shandong was the main source regions of PHg, Pb, Se, As, Cu and Cd. Southeastern and northwestern Shandong province and northern Jiangsu province were the most polluted source regions of Mn, Zn, and Ni. The crustal elements Fe and Ca had similar distributions of potential source regions, suggested by the highest PSCF values in southeastern Shandong and northern Jiangsu. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sources and geographic origin of particulate matter in urban areas of the Danube macro-region: The cases of Zagreb (Croatia), Budapest (Hungary) and Sofia (Bulgaria).

PubMed

Perrone, M G; Vratolis, S; Georgieva, E; Török, S; Šega, K; Veleva, B; Osán, J; Bešlić, I; Kertész, Z; Pernigotti, D; Eleftheriadis, K; Belis, C A

2018-04-01

The contribution of main PM pollution sources and their geographic origin in three urban sites of the Danube macro-region (Zagreb, Budapest and Sofia) were determined by combining receptor and Lagrangian models. The source contribution estimates were obtained with the Positive Matrix Factorization (PMF) receptor model and the results were further examined using local wind data and backward trajectories obtained with FLEXPART. Potential Source Contribution Function (PSCF) analysis was applied to identify the geographical source areas for the PM sources subject to long-range transport. Gas-to-particle transformation processes and primary emissions from biomass burning are the most important contributors to PM in the studied sites followed by re-suspension of soil (crustal material) and traffic. These four sources can be considered typical of the Danube macro-region because they were identified in all the studied locations. Long-range transport was observed of: a) sulphate-enriched aged aerosols, deriving from SO 2 emissions in combustion processes in the Balkans and Eastern Europe and b) dust from the Saharan and Karakum deserts. The study highlights that PM pollution in the studied urban areas of the Danube macro-region is the result of both local sources and long-range transport from both EU and no-EU areas. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

PM2.5 and Black carbon enhancement at Socheongcho Ocean Research Station in the Yellow Sea

NASA Astrophysics Data System (ADS)

Jeon, H.; Rhee, H.; Lee, M.; JinYong, J.; Min, I.; Shim, J.

2017-12-01

Socheongcho Ocean Research Station (SORS) has been established in northern Yellow Sea by the Korea Institute of Ocean Science and Technology (KIOST). At SORS, PM2.5 and Black carbon (BC) were measured every 10 minutes during October 2014 June 2017 using beta-ray absorption method (FH62C14, Thermo. Inc, USA) and Multi Angle Absorption Photometer (MAAP; Model 5012, Thermo. Inc, USA), respectively. In addition, CO, CO2 and CH4 were determined by Cavity Ring Down Spectroscopy (CRDS; Model G2401, Picarro. Inc, USA). Measurements were intermittently interrupted for SORS maintenance reasons. For BC and PM2.5, the mean, 90th %tile and maximum concentrations were 1.16, 2.29, and 20.07 ug/m3 and 25, 48, and 177 ug/m3, respectively. There was no clear diurnal variation observed for both species. PM2.5 and BC concentrations were higher in cold seasons than in warm seasons. The highest PM2.5 and BC concentrations (>99th %tile) were more frequently observed in winter. Particularly, the extremely high BC were sporadically observed and lasted for no longer than 1 hour. The possible sources of PM2.5 and BC were examined using Conditional Probability Function (CPF), Potential Source Contribution (PSCF), and Concentration Weighted Trajectory (CWT) analysis. The results suggest the dominant influence from China, particularly for high concentrations.

Application of meteorology-based methods to determine local and external contributions to particulate matter pollution: A case study in Venice (Italy)

NASA Astrophysics Data System (ADS)

Squizzato, Stefania; Masiol, Mauro

2015-10-01

The air quality is influenced by the potential effects of meteorology at meso- and synoptic scales. While local weather and mixing layer dynamics mainly drive the dispersion of sources at small scales, long-range transports affect the movements of air masses over regional, transboundary and even continental scales. Long-range transport may advect polluted air masses from hot-spots by increasing the levels of pollution at nearby or remote locations or may further raise air pollution levels where external air masses originate from other hot-spots. Therefore, the knowledge of ground-wind circulation and potential long-range transports is fundamental not only to evaluate how local or external sources may affect the air quality at a receptor site but also to quantify it. This review is focussed on establishing the relationships among PM2.5 sources, meteorological condition and air mass origin in the Po Valley, which is one of the most polluted areas in Europe. We have chosen the results from a recent study carried out in Venice (Eastern Po Valley) and have analysed them using different statistical approaches to understand the influence of external and local contribution of PM2.5 sources. External contributions were evaluated by applying Trajectory Statistical Methods (TSMs) based on back-trajectory analysis including (i) back-trajectories cluster analysis, (ii) potential source contribution function (PSCF) and (iii) concentration weighted trajectory (CWT). Furthermore, the relationships between the source contributions and ground-wind circulation patterns were investigated by using (iv) cluster analysis on wind data and (v) conditional probability function (CPF). Finally, local source contribution have been estimated by applying the Lenschow' approach. In summary, the integrated approach of different techniques has successfully identified both local and external sources of particulate matter pollution in a European hot-spot affected by the worst air quality.

Characteristics of aerosol pollution during heavy haze events in Suzhou, China

NASA Astrophysics Data System (ADS)

Tian, M.; Wang, H. B.; Chen, Y.; Yang, F. M.; Zhang, X. H.; Zou, Q.; Zhang, R. Q.; Ma, Y. L.; He, K. B.

2015-11-01

A comprehensive measurement was carried out to analyze the heavy haze events in Suzhou in January 2013 when extremely severe haze pollution occurred in many cities in China especially in the East. Hourly concentrations of PM2.5, chemical composition (including water-soluble inorganic ions, OC, and EC), and gas-phase precursors were obtained via on-line monitoring system. Based on these data, detailed aerosol composition, light extinction and gas-phase precursors were analyzed to understand the characteristics of the haze events, moreover, the formation mechanism of nitrate and sulfate in PM2.5 and the regional sources deduced from trajectory and PSCF were discussed to explore the origin of the heavy aerosol pollution. The results showed that frequent haze events were occurred on January 2013 and the concentrations of PM2.5 often exceeded 150 μg m-3 during the haze occurrence, with a maximum concentration of 324 μg m-3 on 14 January 2013. Unfavorable weather conditions (high RH, and low rainfall, wind speed and atmospheric pressure), high concentration of secondary aerosol species (including SO42-, NO3-, NH4+, and SOC) and precursors were observed during the haze events. Additionally, OM, (NH4)2SO4, NH4NO3 were demonstrated to be the major contributors to the visibility impairment but the share differed from haze events. This study also found that the high concentration of sulfate might be explained by the heterogeneous reactions in the aqueous surface layer of pre-existing particles or in cloud processes while nitrate might be mainly formed through homogeneous gas-phase reactions. The results of trajectory clustering and the PSCF method manifested that aerosol pollutions in the studied areas were mainly affected by local activities and surrounding sources transported from nearby cities.

Source apportionment of fine particulate matter measured in an industrialized coastal urban area of South Texas

NASA Astrophysics Data System (ADS)

Karnae, Saritha; John, Kuruvilla

2011-07-01

Corpus Christi is a growing industrialized urban airshed in South Texas impacted by local emissions and regional transport of fine particulate matter (PM 2.5). Positive matrix factorization (PMF2) technique was used to evaluate particulate matter pollution in the urban airshed by estimating the types of sources and its corresponding mass contributions affecting the measured ambient PM 2.5 levels. Fine particulate matter concentrations by species measured during July 2003 through December 2008 at a PM 2.5 speciation site were used in this study. PMF2 identified eight source categories, of which secondary sulfates were the dominant source category accounting for 30.4% of the apportioned mass. The other sources identified included aged sea salt (18.5%), biomass burns (12.7%), crustal dust (10.1%), traffic (9.7%), fresh sea salt (8.1%), industrial sources (6%), and a co-mingled source of oil combustion & diesel emissions (4.6%). The apportioned PM mass showed distinct seasonal variability between source categories. The PM levels in Corpus Christi were affected by biomass burns in Mexico and Central America during April and May, sub-Saharan dust storms from Africa during the summer months, and a continental haze episode during August and September with significant transport from the highly industrialized areas of Texas and the neighboring states. Potential source contribution function (PSCF) analysis was performed and it identified source regions and the influence of long-range transport of fine particulate matter affecting this urban area.

High Contributions of Secondary Inorganic Aerosols to PM2.5 under Polluted Levels at a Regional Station in Northern China.

PubMed

Li, Yang; Tao, Jun; Zhang, Leiming; Jia, Xiaofang; Wu, Yunfei

2016-12-15

Daily PM 2.5 samples were collected at Shangdianzi (SDZ) regional site in Beijing-Tianjin-Hebei (BTH) region in 2015. Samples were subject to chemical analysis for organic carbon (OC), elemental carbon (EC), and major water-soluble inorganic ions. The annual average PM 2.5 mass concentration was 53 ± 36 μg·m -3 with the highest seasonal average concentration in spring and the lowest in summer. Water-soluble inorganic ions and carbonaceous aerosols accounted for 34% ± 15% and 33% ± 9%, respectively, of PM 2.5 mass on annual average. The excellent, good, lightly polluted, moderately polluted, and heavily polluted days based on the Air Quality Index (AQI) of PM 2.5 accounted for 40%, 42%, 11%, 4%, and 3%, respectively, of the year. The sum of the average concentration of sulfate, nitrate, and ammonium (SNA) increased from 4.2 ± 2.9 μg·m -3 during excellent days to 85.9 ± 22.4 μg·m -3 during heavily polluted days, and their contributions to PM 2.5 increased from 15% ± 8% to 49% ± 10% accordingly. In contrast, the average concentration of carbonaceous aerosols increased from 9.2 ± 2.8 μg·m -3 to 51.2 ± 14.1 μg·m -3 , and their contributions to PM 2.5 decreased from 34% ± 6% to 29% ± 7%. Potential source contribution function (PSCF) analysis revealed that the major sources for high PM 2.5 and its dominant chemical components were within the area mainly covering Shandong, Henan, and Hebei provinces. Regional pollutant transport from Shanxi province and Inner Mongolia autonomous region located in the west direction of SDZ was also important during the heating season.

Monitoring of volatile organic compounds (VOCs) from an oil and gas station in northwest China for 1 year

NASA Astrophysics Data System (ADS)

Zheng, Huang; Kong, Shaofei; Xing, Xinli; Mao, Yao; Hu, Tianpeng; Ding, Yang; Li, Gang; Liu, Dantong; Li, Shuanglin; Qi, Shihua

2018-04-01

Oil and natural gas are important for energy supply around the world. The exploring, drilling, transportation and processing in oil and gas regions can release a lot of volatile organic compounds (VOCs). To understand the VOC levels, compositions and sources in such regions, an oil and gas station in northwest China was chosen as the research site and 57 VOCs designated as the photochemical precursors were continuously measured for an entire year (September 2014-August 2015) using an online monitoring system. The average concentration of total VOCs was 297 ± 372 ppbv and the main contributor was alkanes, accounting for 87.5 % of the total VOCs. According to the propylene-equivalent concentration and maximum incremental reactivity methods, alkanes were identified as the most important VOC groups for the ozone formation potential. Positive matrix factorization (PMF) analysis showed that the annual average contributions from natural gas, fuel evaporation, combustion sources, oil refining processes and asphalt (anthropogenic and natural sources) to the total VOCs were 62.6 ± 3.04, 21.5 ± .99, 10.9 ± 1.57, 3.8 ± 0.50 and 1.3 ± 0.69 %, respectively. The five identified VOC sources exhibited various diurnal patterns due to their different emission patterns and the impact of meteorological parameters. Potential source contribution function (PSCF) and concentration-weighted trajectory (CWT) models based on backward trajectory analysis indicated that the five identified sources had similar geographic origins. Raster analysis based on CWT analysis indicated that the local emissions contributed 48.4-74.6 % to the total VOCs. Based on the high-resolution observation data, this study clearly described and analyzed the temporal variation in VOC emission characteristics at a typical oil and gas field, which exhibited different VOC levels, compositions and origins compared with those in urban and industrial areas.

Characteristics of fine particulate matter and its sources in an industrialized coastal city, Ningbo, Yangtze River Delta, China

NASA Astrophysics Data System (ADS)

Wang, Weifeng; Yu, Jie; Cui, Yang; He, Jun; Xue, Peng; Cao, Wan; Ying, Hongmei; Gao, Wenkang; Yan, Yingchao; Hu, Bo; Xin, Jinyuan; Wang, Lili; Liu, Zirui; Sun, Yang; Ji, Dongsheng; Wang, Yuesi

2018-05-01

Chemical information is essential in understanding the characteristics of airborne particles, and effectively controlling airborne particulate matter pollution, but it remains unclear in some regions due to the scarcity of measurement data. In the present study, 92 daily PM2.5 (particulate matter with an aerodynamic diameter ≤ 2.5 μm) samples as well as historical observation data of air pollutants were collected in urban Ningbo, one of important industrial cities in the coastal area of the Yangtze River Delta, China in autumn and winter (from Nov. 2014 to Feb. 2015). Various chemical species in PM2.5 were determined including water soluble ions, organic and elemental carbon and elements. Positive matrix factorization model, cluster analysis of back trajectories, potential source contribution function (PSCF) model and concentration-weighted trajectory (CWT) model were used for identifying sources, apportioning contributions from each source and tracking potential areas of sources. The results showed the PM2.5 concentration has been reducing; nonetheless, the concentrations of PM2.5 are still much higher than the World Health Organization guideline with high PM2.5 concentrations observed in autumn and winter for the past few years. During the sampling period, the average PM2.5 mass concentration was 77 μg/m3 with the major components of OC, NO3-, SO42 -, NH4+ and EC, accounting for 24.7, 18.8, 14.5, 11.8 and 6.4% in the total mass concentration, respectively. When the aerosol pollution got worse during the sampling period, the NO3-, SO42 - and NH4+ concentrations increased accordingly and NO3- appeared to increase at fastest rate. SO42 - transported from industrial areas led to slight difference in spatial distribution of SO42 - in Ningbo. More secondary organic carbon was formed and the enrichment factor values of Cu, Ag, Cd, Sn and Pb increased with the degradation of air quality. Ten types of sources were identified for PM2.5 in the autumn and winter of Ningbo, which are metallurgical industry, biomass burning and waste incineration, manufacturing related with Mo, chlor-alkli chemical industry, oil combustion, vehicular emission, secondary source, soil dust, road dust and manufacturing related with Cr, accounting for 9.4, 4.8, 9.4, 7.6, 8.1, 18.7, 27.6, 2, 7.1 and 5.2% of the total sources, respectively. There were five groups of air parcels arriving in Ningbo, of which inland air masses originating from Shandong province were associated with the highest PM2.5 concentrations. Despite the slight differences, it was obvious that the north of Jiangxi, east of Anhui, west of Jiangsu, south of Shandong were identified as major potential sources-areas of SO42 -, NO3-, NH4+, Cl-, OC and EC by both PSCF and CWT models.

LOW TEMPERATURE CATHODE SUPPORTED ELECTROLYTES

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

Harlan U. Anderson; Fatih Dogan; Vladimir Petrovsky

2002-03-31

This project has three main goals: Thin Films Studies, Preparation of Graded Porous Substrates and Basic Electrical Characterization and testing of Planar Single Cells. This period has continued to address the problem of making dense 1/2 to 5 {micro}m thick dense layers on porous substrates (the cathode LSM). Our current status is that we are making structures of 2-5 cm{sup 2} in area, which consist of either dense YSZ or CGO infiltrated into a 2-5 {micro}m thick 50% porous layer made of either nanoncrystalline CGO or YSZ powder. This composite structure coats a macroporous cathode or anode; which serves asmore » the structural element of the bi-layer structure. These structures are being tested as SOFC elements. A number of structures have been evaluated both as symmetrical and as button cell configuration. Results of this testing indicates that the cathodes contribute the most to cell losses for temperatures below 750 C. In this investigation different cathode materials were studied using impedance spectroscopy of symmetric cells and IV characteristics of anode supported fuel cells. Cathode materials studied included La{sub 0.8}Sr{sub 0.2}Co{sub 0.2}Fe{sub 0.8}O{sub 3} (LSCF), La{sub 0.7}Sr{sub 0.2}MnO{sub 3} (LSM), Pr{sub 0.8}Sr{sub 0.2}Fe{sub 0.8}O{sub 3} (PSCF), Sm{sub 0.8}Sr{sub 0.2}Co{sub 0.2}Fe{sub 0.8}O{sub 3} (SSCF), and Yb{sub .8}Sr{sub 0.2}Co{sub 0.2}Fe{sub 0.8}O{sub 3} (SSCF). A new technique for filtering the Fourier transform of impedance data was used to increase the sensitivity of impedance analysis. By creating a filter specifically for impedance spectroscopy the resolution was increased. The filter was tailored to look for specific circuit elements like R//C, Warburg, or constant phase elements. As many as four peaks can be resolved using the filtering technique on symmetric cells. It may be possible to relate the different peaks to material parameters, like the oxygen exchange coefficient. The cathode grouped in order from lowest to highest ASR is LSCF < PSCF < SSCF < YSCF < LSM. The button cell results agree with this ordering indicating that this is an important tool for use in developing our understanding of electrode behavior in fuel cells.« less

Radiocarbon-based impact assessment of open biomass burning on regional carbonaceous aerosols in North China.

PubMed

Zong, Zheng; Chen, Yingjun; Tian, Chongguo; Fang, Yin; Wang, Xiaoping; Huang, Guopei; Zhang, Fan; Li, Jun; Zhang, Gan

2015-06-15

Samples of total suspended particulates (TSPs) and fine particulate matter (PM2.5) were collected from 29th May to 1st July, 2013 at a regional background site in Bohai Rim, North China. Mass concentrations of particulate matter and carbonaceous species showed a total of 50% and 97% of the measured TSP and PM2.5 levels exceeded the first grade national standard of China, respectively. Daily concentrations of organic carbon (OC) and elemental carbon (EC) were detected 7.3 and 2.5 μg m(-3) in TSP and 5.2 and 2.0 μg m(-3) in PM2.5, which accounted 5.8% and 2.0% of TSP while 5.6% and 2.2% for PM2.5, respectively. The concentrations of OC, EC, TSP and PM2.5 were observed higher in the day time than those in the night time. The observations were associated with the emission variations from anthropogenic activities. Two merged samples representing from south and north source areas were selected for radiocarbon analysis. The radiocarbon measurements showed 74% of water-insoluble OC (WINSOC) and 59% of EC in PM2.5 derived from biomass burning and biogenic sources when the air masses were from south region, and 63% and 48% for the air masses from north, respectively. Combined with backward trajectories and daily burned area, open burning of agricultural wastes was found to be predominating, which was confirmed by the potential source contribution function (PSCF). Copyright © 2015 Elsevier B.V. All rights reserved.

Wet deposition of mercury at a New York state rural site: Concentrations, fluxes, and source areas

NASA Astrophysics Data System (ADS)

Lai, Soon-onn; Holsen, Thomas M.; Hopke, Philip K.; Liu, Peng

Event-based mercury (Hg) precipitation samples were collected with a modified MIC-B sampler between September 2003 and April 2005 at Potsdam, NY to investigate Hg in wet deposition and identify potential source areas using the potential source contribution function (PCSF) and residence time weighted concentration (RTWC) models. The volume-weighted mean (VWM) concentration and wet deposition flux were 5.5ngL-1 and 7.6μgm-2 during the study period, and 5.5ngL-1 and 5.9μgm-2 in 2004, respectively, and show seasonal trends with larger values in the spring and summer. The PSCF model results matched known source areas based on an emission inventory better than did the RTWC results based on the spatial correlation index. Both modeling results identified large Hg source areas that contain a number of coal-fired power plants located in the Upper Ohio River Valley and in southeastern Michigan, as well as in Quebec and Ontario where there are metal production facilities, waste incinerators and paper mills. Emissions from the Atlantic Ocean were also determined to be a potential source.

Taking potential probability function maps to the local scale and matching them with land use maps

NASA Astrophysics Data System (ADS)

Garg, Saryu; Sinha, Vinayak; Sinha, Baerbel

2013-04-01

Source-Receptor models have been developed using different methods. Residence-time weighted concentration back trajectory analysis and Potential Source Contribution Function (PSCF) are the two most popular techniques for identification of potential sources of a substance in a defined geographical area. Both techniques use back trajectories calculated using global models and assign values of probability/concentration to various locations in an area. These values represent the probability of threshold exceedances / the average concentration measured at the receptor in air masses with a certain residence time over a source area. Both techniques, however, have only been applied to regional and long-range transport phenomena due to inherent limitation with respect to both spatial accuracy and temporal resolution of the of back trajectory calculations. Employing the above mentioned concepts of residence time weighted concentration back-trajectory analysis and PSCF, we developed a source-receptor model capable of identifying local and regional sources of air pollutants like Particulate Matter (PM), NOx, SO2 and VOCs. We use 1 to 30 minute averages of concentration values and wind direction and speed from a single receptor site or from multiple receptor sites to trace the air mass back in time. The model code assumes all the atmospheric transport to be Lagrangian and linearly extrapolates air masses reaching the receptor location, backwards in time for a fixed number of steps. We restrict the model run to the lifetime of the chemical species under consideration. For long lived species the model run is limited to < 4 hrs as spatial uncertainty increases the longer an air mass is linearly extrapolated back in time. The final model output is a map, which can be compared with the local land use map to pinpoint sources of different chemical substances and estimate their source strength. Our model has flexible space- time grid extrapolation steps of 1-5 minutes and 1-5 km grid resolution. By making use of high temporal resolution data, our model can produce maps for different times of the day, thus accounting for temporal changes and activity profiles of different sources. The main advantage of our approach compared to geostationary numerical methods that interpolate measured concentration values of multiple measurement sites to produce maps (gridding) is that the maps produced are more accurate in terms of spatial identification of sources. The model was applied to isoprene and meteorological data recorded during clean post-monsoon season (1 October- 7 October, 2012) between 11 am and 4 pm at a receptor site in the North-West Indo-Gangetic Plains (IISER Mohali, 30.665° N, 76.729°E, 300 m asl), near the foothills of the Himalayan range. Considering the lifetime of isoprene, the model was run only 2 hours backward in time. The map shows highest residence time weighted concentration of isoprene (up to 3.5 ppbv) over agricultural land with high number of trees (>180 trees/gridsquare); moderate concentrations for agricultural lands with low tree density (1.5-2.5 ppbv for 250 μg/m3 for traffic hotspots in Chandigarh City are observed. Based on the validation against the land use maps, the model appears to do an excellent job in source apportionment and identifying emission hotspots. Acknowledgement: We thank the IISER Mohali Atmospheric Chemistry Facility for data and the Ministry of Human Resource Development (MHRD), India and IISER Mohali for funding the facility. Chinmoy Sarkar is acknowledged for technical support, Saryu Garg thanks the Max Planck-DST India Partner Group on Tropospheric OH reactivity and VOCs for funding the research.

Seasonal characteristics, formation mechanisms and source origins of PM2.5 in two megacities in Sichuan Basin, China

NASA Astrophysics Data System (ADS)

Wang, Huanbo; Tian, Mi; Chen, Yang; Shi, Guangming; Liu, Yuan; Yang, Fumo; Zhang, Leiming; Deng, Liqun; Yu, Jiayan; Peng, Chao; Cao, Xuyao

2018-01-01

To investigate the characteristics of PM2.5 and its major chemical components, formation mechanisms, and geographical origins in the two megacities, Chengdu (CD) and Chongqing (CQ), in Sichuan Basin of southwest China, daily PM2.5 samples were collected simultaneously at one urban site in each city for four consecutive seasons from autumn 2014 to summer 2015. Annual mean concentrations of PM2.5 were 67.0 ± 43.4 and 70.9 ± 41.4 µg m-3 at CD and CQ, respectively. Secondary inorganic aerosol (SNA) and organic matter (OM) accounted for 41.1 and 26.1 % of PM2.5 mass at CD, and 37.4 and 29.6 % at CQ, respectively. Seasonal variations of PM2.5 and major chemical components were significant, usually with the highest mass concentration in winter and the lowest in summer. Daily PM2.5 concentration exceeded the national air quality standard on 30 % of the sampling days at both sites, and most of the pollution events were at the regional scale within the basin formed under stagnant meteorological conditions. The concentrations of carbonaceous components were higher at CQ than CD, likely partially caused by emissions from the large number of motorcycles and the spraying processes used during automobile production in CQ. Heterogeneous reactions probably played an important role in the formation of SO42-, while both homogeneous and heterogeneous reactions contributed to the formation of NO3-. Geographical origins of emissions sources contributing to high PM2.5 masses at both sites were identified to be mainly distributed within the basin based on potential source contribution function (PSCF) analysis.

Short-term dynamics of indoor and outdoor endotoxin exposure: Case of Santiago, Chile, 2012.

PubMed

Barraza, Francisco; Jorquera, Héctor; Heyer, Johanna; Palma, Wilfredo; Edwards, Ana María; Muñoz, Marcelo; Valdivia, Gonzalo; Montoya, Lupita D

2016-01-01

Indoor and outdoor endotoxin in PM2.5 was measured for the very first time in Santiago, Chile, in spring 2012. Average endotoxin concentrations were 0.099 and 0.094 [EU/m(3)] for indoor (N=44) and outdoor (N=41) samples, respectively; the indoor-outdoor correlation (log-transformed concentrations) was low: R=-0.06, 95% CI: (-0.35 to 0.24), likely owing to outdoor spatial variability. A linear regression model explained 68% of variability in outdoor endotoxins, using as predictors elemental carbon (a proxy of traffic emissions), chlorine (a tracer of marine air masses reaching the city) and relative humidity (a modulator of surface emissions of dust, vegetation and garbage debris). In this study, for the first time a potential source contribution function (PSCF) was applied to outdoor endotoxin measurements. Wind trajectory analysis identified upwind agricultural sources as contributors to the short-term, outdoor endotoxin variability. Our results confirm an association between combustion particles from traffic and outdoor endotoxin concentrations. For indoor endotoxins, a predictive model was developed but it only explained 44% of endotoxin variability; the significant predictors were tracers of indoor PM2.5 dust (Si, Ca), number of external windows and number of hours with internal doors open. Results suggest that short-term indoor endotoxin variability may be driven by household dust/garbage production and handling. This would explain the modest predictive performance of published models that use answers to household surveys as predictors. One feasible alternative is to increase the sampling period so that household features would arise as significant predictors of long-term airborne endotoxin levels. Copyright © 2016 Elsevier Ltd. All rights reserved.

Potential sources of the air masses leading to warm and cold anomalies in Moscow in summer

NASA Astrophysics Data System (ADS)

Shukurov, K. A.; Semenov, V. A.

2017-11-01

For summer (June-July-August) days in 1949-2016, using the NOAA trajectory model HYSPLIT_4, the 5-day backward trajectories of the air parcels (elementary air particles) were calculated. Using the daily surface air temperatures (SAT) in summer in Moscow in 1949-2016 and the results of the backward trajectories modeling by PSCF (potential source contribution function) and CWT (concentration weighted trajectories) methods the regions where the air masses most probably hit to before its arrive into the Moscow region at the days of 20%, 10%, 5% and 2% of the strongest positive and negative anomalies of SAT in summer in Moscow. For composites of days with SAT in summer in Moscow above 90th and below the 10th percentile of the distribution function of the SAT, the field of the anomaly of atmospheric pressure at sea level relative to 1981-2010 climatology and the field of average SAT in Eurasia north of 30° N are calculated. The peculiarities of the fields associated with the strong positive and negative anomalies of SAT in summer seasons in Moscow are identified. The fields of potential sources of air parcels, mean air temperature on the path of the movement of air parcels and the average height of the backward trajectory for days with strong anomalies of SAT in summer in Moscow are compared. Possible atmospheric circulation drivers of the highest and lowest anomalies of SAT in winter in Moscow are found out.

High Contributions of Secondary Inorganic Aerosols to PM2.5 under Polluted Levels at a Regional Station in Northern China

PubMed Central

Li, Yang; Tao, Jun; Zhang, Leiming; Jia, Xiaofang; Wu, Yunfei

2016-01-01

Daily PM2.5 samples were collected at Shangdianzi (SDZ) regional site in Beijing–Tianjin–Hebei (BTH) region in 2015. Samples were subject to chemical analysis for organic carbon (OC), elemental carbon (EC), and major water-soluble inorganic ions. The annual average PM2.5 mass concentration was 53 ± 36 μg·m−3 with the highest seasonal average concentration in spring and the lowest in summer. Water-soluble inorganic ions and carbonaceous aerosols accounted for 34% ± 15% and 33% ± 9%, respectively, of PM2.5 mass on annual average. The excellent, good, lightly polluted, moderately polluted, and heavily polluted days based on the Air Quality Index (AQI) of PM2.5 accounted for 40%, 42%, 11%, 4%, and 3%, respectively, of the year. The sum of the average concentration of sulfate, nitrate, and ammonium (SNA) increased from 4.2 ± 2.9 μg·m−3 during excellent days to 85.9 ± 22.4 μg·m−3 during heavily polluted days, and their contributions to PM2.5 increased from 15% ± 8% to 49% ± 10% accordingly. In contrast, the average concentration of carbonaceous aerosols increased from 9.2 ± 2.8 μg·m−3 to 51.2 ± 14.1 μg·m−3, and their contributions to PM2.5 decreased from 34% ± 6% to 29% ± 7%. Potential source contribution function (PSCF) analysis revealed that the major sources for high PM2.5 and its dominant chemical components were within the area mainly covering Shandong, Henan, and Hebei provinces. Regional pollutant transport from Shanxi province and Inner Mongolia autonomous region located in the west direction of SDZ was also important during the heating season. PMID:27983711

Correlation of the level of full-length CFTR transcript with pulmonary phenotype in patients carrying R117H and 1342-1,-2delAG mutations

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

Hamosh, A.; Cutting, G.R.; Oates, R.

The R117H mutation occurs on two chromosome backgrounds, one associated with a 7 thymidine tract (7T-R11H) in the splice-acceptor site of intron 8, the other with a 5 thymidine tract (5T-R117H). We examined exon 9 splicing efficiency in 5 patients of genotype R117H/{delta}F508 and one carrying 1342-1,-2delAG{delta}F508, an obligate exon 9 slice site mutation. Four patients carried R117H on a 7T background -- three adult men with congenital bilateral absence of the vas deferens and one adolescent female with pancreatitis and borderline sweat chloride concentration. The patient with R117H on a 5T background had pancreatic sufficient CF (PS-CF). The 1342-1,-2delAGmore » patient has classic pancreatic insufficient CF (PI-CF). cDNA was synthesized from total RNA extracted from nasal epithlial cells and analyzed for CFTR splicing by 35 cycle PCR using primers in exon 7 and 11. The quantity of full length transcript derived from the R117H or {delta}F508 alleles was assessed by allele-specific oligonucleotide hybridization. While 91.4% of transcript from the 5T-R117H allele was full-length, only 42.2% of CFTR transcript from the 5T-R117H allele was full length. Since CBAVD patients have no lung disease and PS-CF patients do, this indicates that the threshold of developing CF lung disease is crossed when the amount of CFTR transcript bearing R117H is reduced by half. Interestingly, 17.1% of transcript derived from the 1342-1,-2delAG allele (or 8.6% of total CFTR transcript) was normal and full length. This suggests that up to 9% of full length wild-type CFTR transcript may be inadequate to escape the lung disease of CF and that a 9 thymidine tract followed by AAC (the result of the AG deletion) can be used as a splice donor with 2-9% efficiency.« less

Simultaneous Saccharification and Fermentation and Partial Saccharification and Co-Fermentation of Lignocellulosic Biomass for Ethanol Production

NASA Astrophysics Data System (ADS)

Doran-Peterson, Joy; Jangid, Amruta; Brandon, Sarah K.; Decrescenzo-Henriksen, Emily; Dien, Bruce; Ingram, Lonnie O.

Ethanol production by fermentation of lignocellulosic biomass-derived sugars involves a fairly ancient art and an ever-evolving science. Production of ethanol from lignocellulosic biomass is not avant-garde, and wood ethanol plants have been in existence since at least 1915. Most current ethanol production relies on starch- and sugar-based crops as the substrate; however, limitations of these materials and competing value for human and animal feeds is renewing interest in lignocellulose conversion. Herein, we describe methods for both simultaneous saccharification and fermentation (SSF) and a similar but separate process for partial saccharification and cofermentation (PSCF) of lignocellulosic biomass for ethanol production using yeasts or pentose-fermenting engineered bacteria. These methods are applicable for small-scale preliminary evaluations of ethanol production from a variety of biomass sources.

Multiyear Measurements of Flame Retardants and Organochlorine Pesticides in Air in Canada's Western Sub-Arctic.

PubMed

Yu, Yong; Hung, Hayley; Alexandrou, Nick; Roach, Pat; Nordin, Ken

2015-07-21

Fourteen polybrominated diphenyl ethers (PBDEs), 14 non-BDE flame retardants (FRs), and 25 organochlorine pesticides (OCPs) were analyzed in air samples collected at Little Fox Lake (LFL) in Canada's Yukon Territory from August 2011 to December 2014. LFL is a long-term monitoring station operated under the Northern Contaminants Program (NCP) and one of only a few stations that contribute to the assessment of air pollution levels and pathways to the sub-Arctic region. BDE-47 was the most abundant congener among the 14 PBDEs, followed by BDE-99. Non-BDE FRs pentabromotoluene (PBT) and dechlorane plus (DP) were detected in all the samples. Dechlorane 602, 2,3-dibromopropyl-2,4,6-tribromophenyl ether (DPTE), hexabromobenzene (HBB), and 2-ethylhexyl-2,3,4,5-tetrabromobenzoate (EH-TBB) were also detected in >75% of all samples. PBDEs have shown a decreasing tendency as of 2013, which may reflect the phase-out of penta- and octa-BDE mixtures has led to significant decline in the atmosphere. The highest concentrations of OCPs were observed for hexachlorobenzene (HCB), with a median concentration of 61 pg/m(3), followed by α-hexachlorocyclohexane (α-HCH) and α-endosulfan. Potential source contribution function (PSCF) highlights Northern Canada, Pacific, and East Asia as potential sources in warm seasons; whereas in cold seasons, the chemicals mainly came from the Pacific Rim.

Determination of mixing state and sources of wintertime organic aerosol in Paris using single particle mass spectrometry

NASA Astrophysics Data System (ADS)

Healy, R. M.; Sciare, J.; Poulain, L.; Wiedensohler, A.; Jeong, C.; McGuire, M.; Evans, G. J.; McGillicuddy, E.; O'Connor, I. P.; Sodeau, J. R.; Wenger, J.

2012-12-01

The size-resolved chemical composition of single particles at an urban background site in Paris, France, was determined using an Aerosol Time-Of-Flight Mass Spectrometer (ATOFMS) as part of the MEGAPOLI winter campaign in January/February 2010. A variety of mixing states were identified for organic aerosol by mass spectral clustering and apportioned to both fossil fuel and biomass burning sources. The ATOFMS data were scaled in order to produce mass concentration estimates for each organic aerosol particle type identified. Potassium-containing organic aerosol internally mixed with nitrate, associated with local wood burning, was observed to dominate during periods characterised by marine air masses. Sulfate-rich potassium-containing organic aerosol, associated with transboundary transport of biomass burning emissions, dominated during periods influenced by continental air masses. The scaled total mass concentration for potassium-containing particles was well correlated (R2 = 0.79) with concurrent measurements of potassium mass concentration measured with a Particle-Into-Liquid-Sampler (PILS). Another organic particle type, also containing potassium but rich in trimethylamine and sulfate, was detected exclusively during continental air mass events. These particles are postulated to have accumulated gas phase trimethylamine through heterogeneous reaction before arriving at the sampling site. Potential source regions for transboundary organic aerosols have been investigated using the potential source contribution function (PSCF). Comparison with aerosol mass spectrometer (AMS) measurements will also be discussed.

Characteristics of size-resolved atmospheric inorganic and carbonaceous aerosols in urban Shanghai

NASA Astrophysics Data System (ADS)

Ding, X. X.; Kong, L. D.; Du, C. T.; Zhanzakova, A.; Fu, H. B.; Tang, X. F.; Wang, L.; Yang, X.; Chen, J. M.; Cheng, T. T.

2017-10-01

Size-segregated aerosol particles were collected with a 10-stage Micro-Orifice Uniform Deposit Impactor (MOUDI) at an urban site in Shanghai, China for four non-consecutive months representing four seasons from 2015 to 2016. Chemical composition, including water-soluble ions as well as organic carbon (OC), elemental carbon (EC) and secondary organic carbon (SOC) of size-resolved (0.056-18 μm) atmospheric aerosols in four seasons and in different polluted cases were studied. The size distributions of sulfate, nitrate and ammonium (SNA) and carbonaceous aerosol (OC, EC and SOC) were discussed and the potential sources of PM1.8-associated secondary species (SO42-, NO3-, SNA and SOC) in different seasons were identified by potential source contribution function (PSCF) model. Results showed that atmospheric ultrafine and fine particle pollution in Shanghai were very serious during the study period. Most of the water-soluble ions tended to be enriched in fine particles, especially being abundant in the droplet mode in polluted cases. Compared with sulfate, size distributions of nitrate and ammonium presented more significant seasonal variations and showed distinctive characteristics in polluted days. Abundant nitrate was concentrated in fine particles in cold seasons (spring and winter), whereas it was enriched in coarse mode during summer and autumn. The droplet mode sulfate with high concentration did not result in the aggravation of air pollution, while the nucleation mode sulfate may have made a great contribution to the air pollution in urban Shanghai. It was also found that the formation of air pollution in urban Shanghai had a significant link with nitrate and ammonium, especially with nitrate and ammonium in condensation mode and droplet mode, and the contribution of sulfate to the pollution formation in Shanghai would somehow be surpassed by the increasing nitrate and ammonium. OC and EC concentrations from spring to winter were found to be 11.10, 7.10, 12.30, 20.16, and 3.73, 2.84, 4.63, 7.10 μg m-3, respectively, distinctly presenting the summer minima and winter maxima in this study. The maximum OC/EC was in the droplet mode and the minimum was in the nucleation mode for both clean and polluted days. The great contribution of SOC to OC in droplet mode and the occurrence of PM pollution necessarily had an important bearing on the SOC formation in droplet mode particles. Particle acidity may play a key role in secondary organic aerosol formation and the particles with the size of 0.056-0.1 μm was the most sensitive particles to acid catalysis in SOA formation. The similar PSCF results of PM1.8-associated SOC to those of SO42-, NO3- and SNA indicated possible connections between the formation of SOC and secondary inorganic species in PM.

Characterization of aerosol composition, concentrations, and sources at Baengnyeong Island, Korea using an aerosol mass spectrometer

NASA Astrophysics Data System (ADS)

Lee, Taehyoung; Choi, Jinsoo; Lee, Gangwoong; Ahn, Junyoung; Park, Jin Soo; Atwood, Samuel A.; Schurman, Misha; Choi, Yongjoo; Chung, Yoomi; Collett, Jeffrey L.

2015-11-01

To improve understanding of the sources and chemical properties of particulate pollutants on the western side of the Korean Peninsula, an Aerodyne High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS) measured non-refractory fine (PM1) particles from May to November, 2011 at Baengnyeong Island, South Korea. Organic matter and sulfate were generally the most abundant species and exhibited maximum concentrations of 36 μg/m3 and 39 μg/m3, respectively. Nitrate concentrations peaked at 32 μg/m3 but were typically much lower than sulfate and organic matter concentrations. May, September, October, and November featured the highest monthly average concentrations, with lower concentrations typically observed from June through August. Potential source contribution function (PSCF) analysis and individual case studies revealed that transport from eastern China, an area with high SO2 emissions, was associated with high particulate sulfate concentrations at the measurement site. Observed sulfate aerosol sometimes was fully neutralized by ammonium but often was acidic; the average ammonium to sulfate molar ratio was 1.49. Measured species size distributions revealed a range of sulfate particle size distributions with modes between 100 and 600 nm. Organic aerosol source regions were widespread, including contributions from eastern China and South Korea. Positive matrix factorization (PMF) analysis indicated three "factors," or types of organic aerosol, comprising one primary, hydrocarbon-like organic aerosol (HOA) and two oxidized organic aerosol (OOA) components, including a more oxidized (MO-OOA) and a less oxidized (LO-OOA) oxidized organic aerosol. On average, HOA and OOA contributed 21% and 79% of the organic mass (OM), respectively, with the MO-OOA fraction nearly three times as abundant as the LO-OOA fraction. Biomass burning contributions to observed OM were low during the late spring/early summer agricultural burning season in eastern China, since airflow into eastern China during the Asian Monsoon generally prevents transport of emissions eastward to the Korean Peninsula. Concentrations of the m/z 60 AMS biomass burning marker were more abundant in autumn, when transport patterns appeared to bring some smoke from fires in northern Asia to the island.

Transported vs. local contributions from secondary and biomass burning sources to PM2.5

NASA Astrophysics Data System (ADS)

Kim, Bong Mann; Seo, Jihoon; Kim, Jin Young; Lee, Ji Yi; Kim, Yumi

2016-11-01

The concentration of fine particulates in Seoul, Korea has been lowered over the past 10 years, as a result of the city's efforts in implementing environmental control measures. Yet, the particulate concentration level in Seoul remains high as compared to other urban areas globally. In order to further improve fine particulate air quality in the Korea region and design a more effective control strategy, enhanced understanding of the sources and contribution of fine particulates along with their chemical compositions is necessary. In turn, relative contributions from local and transported sources on Seoul need to be established, as this city is particularly influenced by sources from upwind geographic areas. In this study, PM2.5 monitoring was conducted in Seoul from October 2012 to September 2013. PM2.5 mass concentrations, ions, metals, organic carbon (OC), elemental carbon (EC), water soluble OC (WSOC), humic-like substances of carbon (HULIS-C), and 85 organic compounds were chemically analyzed. The multivariate receptor model SMP was applied to the PM2.5 data, which then identified nine sources and estimated their source compositions as well as source contributions. Prior studies have identified and quantified the transported and local sources. However, no prior studies have distinguished contributions of an individual source between transported contribution and locally produced contribution. We differentiated transported secondary and biomass burning sources from the locally produced secondary and biomass burning sources, which was supported with potential source contribution function (PSCF) analysis. Of the total secondary source contribution, 32% was attributed to transported secondary sources, and 68% was attributed to locally formed secondary sources. Meanwhile, the contribution from the transported biomass burning source was revealed as 59% of the total biomass burning contribution, which was 1.5 times higher than that of the local biomass burning source. Four-season average source contributions from the transported and the local sources were 28% and 72%, respectively.

An integrated approach using high time-resolved tools to study the origin of aerosols.

PubMed

Di Gilio, A; de Gennaro, G; Dambruoso, P; Ventrella, G

2015-10-15

Long-range transport of natural and/or anthropogenic particles can contribute significantly to PM10 and PM2.5 concentrations and some European cities often fail to comply with PM daily limit values due to the additional impact of particles from remote sources. For this reason, reliable methodologies to identify long-range transport (LRT) events would be useful to better understand air pollution phenomena and support proper decision-making. This study explores the potential of an integrated and high time-resolved monitoring approach for the identification and characterization of local, regional and long-range transport events of high PM. In particular, the goal of this work was also the identification of time-limited event. For this purpose, a high time-resolved monitoring campaign was carried out at an urban background site in Bari (southern Italy) for about 20 days (1st-20th October 2011). The integration of collected data as the hourly measurements of inorganic ions in PM2.5 and their gas precursors and of the natural radioactivity, in addition to the analyses of aerosol maps and hourly back trajectories (BT), provided useful information for the identification and chemical characterization of local sources and trans-boundary intrusions. Non-sea salt (nss) sulfate levels were found to increase when air masses came from northeastern Europe and higher dispersive conditions of the atmosphere were detected. Instead, higher nitrate and lower nss-sulfate concentrations were registered in correspondence with air mass stagnation and attributed to local traffic source. In some cases, combinations of local and trans-boundary sources were observed. Finally, statistical investigations such as the principal component analysis (PCA) applied on hourly ion concentrations and the cluster analyses, the Potential Source Contribution Function (PSCF) and the Concentration Weighted Trajectory (CWT) models computed on hourly back-trajectories enabled to complete a cognitive framework and confirm the influence of aerosol transported from heavily polluted areas on the receptor site. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of background soil and air polychlorinated biphenyl (PCB) concentrations on a hill at the outskirts of a metropolitan city.

PubMed

Kuzu, S Levent; Saral, Arslan; Güneş, Gülten; Karadeniz, Aykut

2016-07-01

Air and soil sampling was conducted inside a forested area for 22 months. The sampling location is situated to the north of a metropolitan city. Average atmospheric gas and particle concentrations were found to be 180 and 28 pg m(-3) respectively, while that of soil phase was detected to be 3.2 ng g(-1) on dry matter, The congener pairs of PCB#4-10 had the highest contribution to each medium. TEQ concentration was 0.10 pg m(-3), 0.07 pg m(-3), 21.92 pg g(-1), for gas, particle and soil phases, respectively. PCB#126 and PCB#169 contributed to over 99% of the entire TEQ concentrations for each medium. Local sources were investigated by conditional probability function (CPF) and soil/air fugacity. Landfilling area and medical waste incinerator, located to the 8 km northeast, contributed to ambient concentrations, especially in terms of dioxin-like congeners. The industrial settlement (called Dilovasi being to the east southeast of 60 km distant) contributed from southeast direction. Further sources were identified by potential source contribution function (PSCF). Sources at close proximity had high contribution. Air mass transportation from Aliaga industrial region (being to the southwest of 300 km distant) moderately contributed to ambient concentrations. Low molecular weight congeners were released from soil body. 5-CBs and 6-CBs were close to equilibrium state between soil/air interfaces. PCB#171 was close to equilibrium and PCB#180 was likely to evaporate from soil, which constitute 7-CBs. PCB#199, representing 8-CBs deposited to soil. 9-CB (PCB#207) was in equilibrium between soil and air phases. Copyright © 2016 Elsevier Ltd. All rights reserved.

Arctic Black Carbon Initiative: Reducing Emissions of Black Carbon from Power & Industry in Russia

NASA Astrophysics Data System (ADS)

Cresko, J.; Hodson, E. L.; Cheng, M.; Fu, J. S.; Huang, K.; Storey, J.

2012-12-01

Deposition of black carbon (BC) on snow and ice is widely considered to have a climate warming effect by reducing the surface albedo and promoting snowmelt. Such positive climate feedbacks in the Arctic are especially problematic because rising surface temperatures may trigger the release of large Arctic stores of terrestrial carbon, further amplifying current warming trends. Recognizing the Arctic as a vulnerable region, the U.S. government committed funds in Copenhagen in 2009 for international cooperation targeting Arctic BC emissions reductions. As a result, the U.S. Department of State has funded three research and demonstration projects with the goal to better understand and mitigate BC deposition in the Russian Arctic from a range of sources. The U.S. Department of Energy's (DOE) Arctic BC initiative presented here is focused on mitigating BC emissions resulting from heat and power generation as well as industrial applications. A detailed understanding of BC sources and its transport and fate is required to prioritize efforts to reduce BC emissions from sources that deposit in the Russian Arctic. Sources of BC include the combustion of fossil fuels (e.g. coal, fuel oil, diesel) and the combustion of biomass (e.g. wildfires, agricultural burning, residential heating and cooking). Information on fuel use and associated emissions from the industrial and heat & power sectors in Russia is scarce and difficult to obtain from the open literature. Hence, our project includes a research component designed to locate Arctic BC emissions sources in Russia and determine associated BC transport patterns. We use results from the research phase to inform a subsequent assessment/demonstration phase. We use a back-trajectory modeling method (potential source contribution function - PSCF), which combines multi-year, high-frequency measurements with knowledge about atmospheric transport patterns. The PSCF modeling allows us to map the probability (by season and year) at course resolution (2.5° x 2.5° spatial resolution) that a particular region emits BC which deposits in the Russian Arctic. We utilize data from three Arctic measurement stations during the most recent decade: Alert, Northwest Territories, Canada; Barrow, Alaska; and Tiksi Bay, Russia. To understand more about individual Arctic BC sources, we conduct further research to improve inventory estimates of Russian industrial and energy sector BC emissions. By comparing inventory data on power plant locations and emissions from two publically-available databases (EDGAR-HTAP and CARMA databases) to each other and to additional observations from satellites and the AERONET observation network in Russia, we assess the accuracy of the Russian BC emission inventory in EDGAR-HTAP, a commonly used database for atmospheric transport modeling. We then use a global (GEOS-CHEM) atmospheric transport model to quantify the finer spatial distribution of BC within the Arctic. Lastly, we use data on Russian fuel use combined with published emissions factors to build a national-scale model of energy use and associated emissions from critical industrial and heat & power sources of BC. We use this model to estimate the technical potential of reducing BC emissions through proven mitigation efforts such as improvements in energy efficiency and in emission control technologies.

Sources and geographical origins of fine aerosols in Paris (France)

NASA Astrophysics Data System (ADS)

Bressi, M.; Sciare, J.; Ghersi, V.; Mihalopoulos, N.; Petit, J.-E.; Nicolas, J. B.; Moukhtar, S.; Rosso, A.; Féron, A.; Bonnaire, N.; Poulakis, E.; Theodosi, C.

2013-12-01

The present study aims at identifying and apportioning the major sources of fine aerosols in Paris (France) - the second largest megacity in Europe -, and determining their geographical origins. It is based on the daily chemical composition of PM2.5 characterised during one year at an urban background site of Paris (Bressi et al., 2013). Positive Matrix Factorization (EPA PMF3.0) was used to identify and apportion the sources of fine aerosols; bootstrapping was performed to determine the adequate number of PMF factors, and statistics (root mean square error, coefficient of determination, etc.) were examined to better model PM2.5 mass and chemical components. Potential Source Contribution Function (PSCF) and Conditional Probability Function (CPF) allowed the geographical origins of the sources to be assessed; special attention was paid to implement suitable weighting functions. Seven factors named ammonium sulfate (A.S.) rich factor, ammonium nitrate (A.N.) rich factor, heavy oil combustion, road traffic, biomass burning, marine aerosols and metals industry were identified; a detailed discussion of their chemical characteristics is reported. They respectively contribute 27, 24, 17, 14, 12, 6 and 1% of PM2.5 mass (14.7 μg m-3) on the annual average; their seasonal variability is discussed. The A.S. and A.N. rich factors have undergone north-eastward mid- or long-range transport from Continental Europe, heavy oil combustion mainly stems from northern France and the English Channel, whereas road traffic and biomass burning are primarily locally emitted. Therefore, on average more than half of PM2.5 mass measured in the city of Paris is due to mid- or long-range transport of secondary aerosols stemming from continental Europe, whereas local sources only contribute a quarter of the annual averaged mass. These results imply that fine aerosols abatement policies conducted at the local scale may not be sufficient to notably reduce PM2.5 levels at urban background sites in Paris, suggesting instead more coordinated strategies amongst neighbouring countries. Similar conclusions might be drawn in other continental urban background sites given the transboundary nature of PM2.5 pollution.

Sources and geographical origins of fine aerosols in Paris (France)

NASA Astrophysics Data System (ADS)

Bressi, M.; Sciare, J.; Ghersi, V.; Mihalopoulos, N.; Petit, J.-E.; Nicolas, J. B.; Moukhtar, S.; Rosso, A.; Féron, A.; Bonnaire, N.; Poulakis, E.; Theodosi, C.

2014-08-01

The present study aims at identifying and apportioning fine aerosols to their major sources in Paris (France) - the second most populated "larger urban zone" in Europe - and determining their geographical origins. It is based on the daily chemical composition of PM2.5 examined over 1 year at an urban background site of Paris (Bressi et al., 2013). Positive matrix factorization (EPA PMF3.0) was used to identify and apportion fine aerosols to their sources; bootstrapping was performed to determine the adequate number of PMF factors, and statistics (root mean square error, coefficient of determination, etc.) were examined to better model PM2.5 mass and chemical components. Potential source contribution function (PSCF) and conditional probability function (CPF) allowed the geographical origins of the sources to be assessed; special attention was paid to implement suitable weighting functions. Seven factors, namely ammonium sulfate (A.S.)-rich factor, ammonium nitrate (A.N.)-rich factor, heavy oil combustion, road traffic, biomass burning, marine aerosols and metal industry, were identified; a detailed discussion of their chemical characteristics is reported. They contribute 27, 24, 17, 14, 12, 6 and 1% of PM2.5 mass (14.7 μg m-3) respectively on the annual average; their seasonal variability is discussed. The A.S.- and A.N.-rich factors have undergone mid- or long-range transport from continental Europe; heavy oil combustion mainly stems from northern France and the English Channel, whereas road traffic and biomass burning are primarily locally emitted. Therefore, on average more than half of PM2.5 mass measured in the city of Paris is due to mid- or long-range transport of secondary aerosols stemming from continental Europe, whereas local sources only contribute a quarter of the annual averaged mass. These results imply that fine-aerosol abatement policies conducted at the local scale may not be sufficient to notably reduce PM2.5 levels at urban background sites in Paris, suggesting instead more coordinated strategies amongst neighbouring countries. Similar conclusions might be drawn in other continental urban background sites given the transboundary nature of PM2.5 pollution.

Estimation of local and external contributions of biomass burning to PM2.5 in an industrial zone included in a large urban settlement.

PubMed

Benetello, Francesca; Squizzato, Stefania; Hofer, Angelika; Masiol, Mauro; Khan, Md Badiuzzaman; Piazzalunga, Andrea; Fermo, Paola; Formenton, Gian Maria; Rampazzo, Giancarlo; Pavoni, Bruno

2017-01-01

A total of 85 PM 2.5 samples were collected at a site located in a large industrial zone (Porto Marghera, Venice, Italy) during a 1-year-long sampling campaign. Samples were analyzed to determine water-soluble inorganic ions, elemental and organic carbon, and levoglucosan, and results were processed to investigate the seasonal patterns, the relationship between the analyzed species, and the most probable sources by using a set of tools, including (i) conditional probability function (CPF), (ii) conditional bivariate probability function (CBPF), (iii) concentration weighted trajectory (CWT), and (iv) potential source contribution function (PSCF) analyses. Furthermore, the importance of biomass combustions to PM 2.5 was also estimated. Average PM 2.5 concentrations ranged between 54 and 16 μg m -3 in the cold and warm period, respectively. The mean value of total ions was 11 μg m -3 (range 1-46 μg m -3 ): The most abundant ion was nitrate with a share of 44 % followed by sulfate (29 %), ammonium (14 %), potassium (4 %), and chloride (4 %). Levoglucosan accounted for 1.2 % of the PM 2.5 mass, and its concentration ranged from few ng m -3 in warm periods to 2.66 μg m -3 during winter. Average concentrations of levoglucosan during the cold period were higher than those found in other European urban sites. This result may indicate a great influence of biomass combustions on particulate matter pollution. Elemental and organic carbon (EC, OC) showed similar behavior, with the highest contributions during cold periods and lower during summer. The ratios between biomass burning indicators (K + , Cl - , NO 3 - , SO 4 2- , levoglucosan, EC, and OC) were used as proxy for the biomass burning estimation, and the contribution to the OC and PM 2.5 was also calculated by using the levoglucosan (LG)/OC and LG/PM 2.5 ratios and was estimated to be 29 and 18 %, respectively.

Temporal trend and sources of speciated atmospheric mercury at Waliguan GAW station, northwestern China

NASA Astrophysics Data System (ADS)

Fu, X. W.; Feng, X.; Liang, P.; Deli-Geer; Zhang, H.; Ji, J.; Liu, P.

2011-11-01

Measurements of speciated atmospheric mercury were conducted at a remote mountain-top station (WLG) at the edge of northeastern part of the Qinghai-Xizang Plateau, western China. Mean concentrations of total gaseous mercury (TGM), particulate mercury (PHg), and reactive gaseous mercury (RGM) during the whole sampling campaign were 1.98 ± 0.98 ng m-3, 19.4 ± 18.1 pg m-3, and 7.4 ± 4.8 pg m-3, respectively. Levels of speciated Hg at WLG were slightly higher than those reported from remote areas of North America and Europe. Both regional emissions and long-rang transport played a remarkable role in the distribution of TGM and PHg in ambient air at WLG, whereas RGM showed major links to the regional sources, likely as well as the in-situ productions by photochemical processes. Regional sources for speciated Hg were mostly located to the east of WLG, which is the most developed areas of Qinghai province and accounted for most of the province's anthropogenic Hg emissions. Potential source contribution function (PSCF) results showed a strong impact of long-range transport from eastern Gansu, western Ningxia and Shanxi Province, with good accordance with locations of urban areas and industrial centers. Moreover, we found that northern India was also an important source region of WLG during the sampling campaign, and this is the first time of direct evidence of long-range transport of atmospheric Hg from India to northeastern Tibetan Plateau. Seasonal and diurnal variations of TGM were in contrast with most of the previous studies in China, with relatively higher levels in warm seasons and night, respectively. The temporal trend of TGM also highlighted the impact of long-range transport on the distribution of TGM in ambient air at WLG.

Impact of anthropogenic emission on air quality over a megacity - revealed from an intensive atmospheric campaign during the Chinese Spring Festival

NASA Astrophysics Data System (ADS)

Huang, K.; Zhuang, G.; Lin, Y.; Wang, Q.; Fu, J. S.; Zhang, R.; Li, J.; Deng, C.; Fu, Q.

2012-12-01

The Chinese Spring Festival is one of the most important traditional festivals in China. The peak transport in the Spring Festival season (spring travel rush) provides a unique opportunity for investigating the impact of human activity on air quality in the Chinese megacities. Emission sources are varied and fluctuate greatly before, during and after the Festival. Increased vehicular emissions during the "spring travel rush" before the 2009 Festival resulted in high level pollutants of NOx (270 μg m-3), CO (2572 μg m-3), black carbon (BC) (8.5 μg m-3) and extremely low single scattering albedo of 0.76 in Shanghai, indicating strong, fresh combustion. Organics contributed most to PM2.5, followed by NO3-, NH4+, and SO42-. During the Chinese Lunar New Year's Eve and Day, widespread usage of fireworks caused heavy pollution of extremely high aerosol concentration, scattering coefficient, SO2, and NOx. Due to the "spring travel rush" after the festival, anthropogenic emissions gradually climbed and mirrored corresponding increases in the aerosol components and gaseous pollutants. Secondary inorganic aerosol (SO42-, NO3-, and NH4+) accounted for a dominant fraction of 74% in PM2.5 due to an increase in human activity. There was a greater demand for energy as vast numbers of people using public transportation or driving their own vehicles returned home after the Festival. Factories and constructions sites were operating again. The potential source contribution function (PSCF) analysis illustrated the possible source areas for air pollutants of Shanghai. The effects of regional and long-range transport were both revealed. Five major sources, i.e. natural sources, vehicular emissions, burning of fireworks, industrial and metallurgical emissions, and coal burning were identified using the principle component analysis. The average visibility during the whole study period was less than 6 km. It had been estimated that 50% of the total light extinction was due to the high water vapor in the atmosphere. This study demonstrates that organic aerosol was the largest contributor to aerosol extinction at 47%, followed by sulfate ammonium, nitrate ammonium, and EC at 22%, 14%, and 12%, respectively. Our results indicated the dominant role of traffic-related aerosol species (i.e. organic aerosol, nitrate and EC) on the formation of air pollution, and suggested the importance of controlling vehicle numbers and emissions in mega-cities of China as its population and economy continue to grow.

Structure of the heterotrimeric complex that regulates type III secretion needle formation

PubMed Central

Quinaud, Manuelle; Plé, Sophie; Job, Viviana; Contreras-Martel, Carlos; Simorre, Jean-Pierre; Attree, Ina; Dessen, Andréa

2007-01-01

Type III secretion systems (T3SS), found in several Gram-negative pathogens, are nanomachines involved in the transport of virulence effectors directly into the cytoplasm of target cells. T3SS are essentially composed of basal membrane-embedded ring-like structures and a hollow needle formed by a single polymerized protein. Within the bacterial cytoplasm, the T3SS needle protein requires two distinct chaperones for stabilization before its secretion, without which the entire T3SS is nonfunctional. The 2.0-Å x-ray crystal structure of the PscE-PscF55–85-PscG heterotrimeric complex from Pseudomonas aeruginosa reveals that the C terminus of the needle protein PscF is engulfed within the hydrophobic groove of the tetratricopeptide-like molecule PscG, indicating that the macromolecular scaffold necessary to stabilize the T3SS needle is totally distinct from chaperoned complexes between pilus- or flagellum-forming molecules. Disruption of specific PscG–PscF interactions leads to impairment of bacterial cytotoxicity toward macrophages, indicating that this essential heterotrimer, which possesses homologs in a wide variety of pathogens, is a unique attractive target for the development of novel antibacterials. PMID:17470796

Assessment of carbonaceous aerosols in Shanghai, China - Part 1: long-term evolution, seasonal variations, and meteorological effects

NASA Astrophysics Data System (ADS)

Chang, Yunhua; Deng, Congrui; Cao, Fang; Cao, Chang; Zou, Zhong; Liu, Shoudong; Lee, Xuhui; Li, Jun; Zhang, Gan; Zhang, Yanlin

2017-08-01

Carbonaceous aerosols are major chemical components of fine particulate matter (PM2. 5) with major impacts on air quality, climate change, and human health. Gateway to fast-rising China and home of over twenty million people, Shanghai throbs as the nation's largest mega city and the biggest industrial hub. From July 2010 to December 2014, hourly mass concentrations of ambient organic carbon (OC) and elemental carbon (EC) in the PM2. 5 fraction were quasi-continuously measured in Shanghai's urban center. The annual OC and EC concentrations (mean ±1σ) in 2013 (8.9 ± 6.2 and 2.6 ± 2.1 µg m-3, n = 5547) and 2014 (7.8 ± 4.6 and 2.1 ± 1.6 µg m-3, n = 6914) were higher than those of 2011 (6.3 ± 4.2 and 2.4 ± 1.8 µg m-3, n = 8039) and 2012 (5.7 ± 3.8 and 2.0 ± 1.6 µg m-3, n = 4459). We integrated the results from historical field measurements (1999-2012) and satellite observations (2003-2013), concluding that carbonaceous aerosol pollution in Shanghai has gradually reduced since 2006. In terms of monthly variations, average OC and EC concentrations ranged from 4.0 to 15.5 and from 1.4 to 4.7 µg m-3, accounting for 13.2-24.6 and 3.9-6.6 % of the seasonal PM2. 5 mass (38.8-94.1 µg m-3), respectively. The concentrations of EC (2.4, 2.0, 2.2, and 3.0 µg m-3 in spring, summer, fall, and winter, respectively) showed little seasonal variation (except in winter) and weekend-weekday dependence, indicating EC is a relatively stable constituent of PM2. 5 in the Shanghai urban atmosphere. In contrast to OC (7.3, 6.8, 6.7, and 8.1 µg m-3 in spring, summer, fall, and winter, respectively), EC showed marked diurnal cycles and correlated strongly with CO across all seasons, confirming vehicular emissions as the dominant source of EC at the targeted site. Our data also reveal that both OC and EC showed concentration gradients as a function of wind direction (WD) and wind speed (WS), generally with higher values associated with winds from the southwest, west, and northwest. This was consistent with their higher potential as source areas, as determined by the potential source contribution function (PSCF) analysis. A common high-potential source area, located along the middle and lower reaches of the Yangtze River instead of northern China, was pinpointed during all seasons. These results demonstrate that the measured carbonaceous aerosols were driven by the interplay of local emissions and regional transport.

Long-term monitoring of atmospheric PCDD/Fs at Mount Lulin during spring season: PCDD/F source apportionment through a simultaneous measurement in Southeast Asia.

PubMed

Hung, Ngo Tuan; Li, Chueh Ting; Wang, Sheng Hsiang; Ou-Yang, Chang-Feng; Lin, Chuan-Yao; Lee, Chung-Te; Lin, Neng-Huei; Chi, Kai Hsien

2017-10-01

A long term assessment of atmospheric polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) at Mt. Lulin, located in center of Taiwan was carried out from 2008 to 2013 (n = 81) assuming Mt. Lulin to be background area. During monitoring processes, PCDD/F samples collected in the field occasionally reached high concentration. To investigate this situation, simultaneous sample collection was carried out in Southeast Asia countries (i.e., Vietnam and Thailand) and Taiwan in 2013. The average concentration of atmospheric PCDD/Fs in biomass-burning source regions, namely Son La and Doi Ang Khang were 19.8 ± 12.1 fg I-TEQ m -3 (n = 19) and 17.8 ± 12.4 fg I-TEQ m -3 (n = 20), respectively. In the downwind area of Mt. Lulin, the average concentration of PCDD/Fs was found to be 4.64 ± 3.77 fg I-TEQ m -3 (n = 18). PCDD/F concentration in the source region was much higher than that in the downwind region. On March 19, 2013, the atmospheric PCDD/F concentrations increased dramatically from 7.71 to 484 fg I-TEQ m -3 at Mt. Lulin, which many times exceeded that of assumed source region in Southeast Asia. Moreover, mainland Southeast Asia and the southeast coast of China was suspected to be the main contributors of atmospheric PCDD/Fs and biomass markers, such as nonsea-salt K + and NH 4 + , during the spring. WRF-Chem and Potential Source Contribution Function (PSCF) simulations have confirmed this correlation. It can be concluded that atmospheric PCDD/Fs observed at Mt. Lulin during spring mostly derived from the air mass transport not only from Southeast Asia but also the southeast coast of China. Copyright © 2017 Elsevier Ltd. All rights reserved.

Contributions and source identification of biogenic and anthropogenic hydrocarbons to secondary organic aerosols at Mt. Tai in 2014.

PubMed

Zhu, Yanhong; Yang, Lingxiao; Kawamura, Kimitaka; Chen, Jianmin; Ono, Kaori; Wang, Xinfeng; Xue, Likun; Wang, Wenxing

2017-01-01

Ambient fine particulate matter (PM 2.5 ) and volatile organic compounds (VOCs) collected at Mt. Tai in summer 2014 were analysed and the data were used to identify the contribution of biogenic and anthropogenic hydrocarbons to secondary organic aerosols (SOA) and their sources and potential source areas in high mountain regions. Compared with those in 2006, the 2014 anthropogenic SOA tracers in PM 2.5 aerosols and VOC species related to vehicular emissions exhibited higher concentrations, whereas the levels of biogenic SOA tracers were lower, possibly due to decreased biomass burning. Using the SOA tracer and parameterisation method, we estimated the contributions from biogenic and anthropogenic VOCs, respectively. The results showed that the average concentration of biogenic SOA was 1.08 ± 0.51 μg m -3 , among which isoprene SOA tracers were dominant. The anthropogenic VOC-derived SOA were 7.03 ± 1.21 μg m -3 and 1.92 ± 1.34 μg m -3 under low- and high-NO x conditions, respectively, and aromatics made the greatest contribution. However, the sum of biogenic and anthropogenic SOA only contributed 18.1-49.1% of the total SOA. Source apportionment by positive matrix factorisation (PMF) revealed that secondary oxidation and biomass burning were the major sources of biogenic SOA tracers. Anthropogenic aromatics mainly came from solvent use, fuel and plastics combustion and vehicular emissions. However, for > C6 alkanes and cycloalkanes, vehicular emissions and fuel and plastics combustion were the most important contributors. The potential source contribution function (PSCF) identified the Bohai Sea Region (BSR) as the major source area for organic aerosol compounds and VOC species at Mt. Tai. Copyright © 2016 Elsevier Ltd. All rights reserved.

Characterization and source apportionment of PM2.5-bound polycyclic aromatic hydrocarbons from Shanghai city, China.

PubMed

Wang, Qing; Liu, Min; Yu, Yingpeng; Li, Ye

2016-11-01

Polycyclic aromatic hydrocarbons (PAHs) were studied in 230 daily fine particulate matter (PM2.5) samples collected in four seasons at urban and suburban sites of Shanghai, China. This study focused on the emission sources of PAHs and its dynamic results under different weather conditions and pollution levels and also emphasized on the spatial sources of PM2.5 and PAHs at a regional level. Annual concentrations of PM2.5 and 16 EPA priority PAHs were 53 μg/m 3 and 6.9 ng/m 3 , respectively, with highest levels in winter. Positive matrix factorization (PMF) modeling identified four sources of PAHs: coal combustion, traffic, volatilization and biomass combustion, and coking, with contributions of 34.9%, 27.5%, 21.1% and 16.5%, respectively. The contribution of traffic, a local-indicative source, increased from 17.4% to 28.7% when wind speed changed from >2m/s to <2m/s, and increased from 18.3% to 31.3% when daily PAH concentrations changed from below to above the annual mean values. This indicated that local sources may have larger contributions under stagnant weather when poorer dispersion conditions and lower wind speed led to the accumulation of local-emitted pollutants. The trajectory clustering and potential source contribution function (PSCF) and concentration weighted trajectory (CWT) models showed clearly that air parcels moved from west had highest concentrations of PM2.5, total PAHs and high molecular weight (HMW) PAHs. While small differences were found among all five clusters in low molecular weight (LMW) PAHs. Sector analyses determined that regional transport source contributed 39.8% to annual PM2.5 and 52.5% to PAHs, mainly from western regions and varying with seasons. This work may make contribution to a better understanding and control of the increasingly severe air pollution in China as well as other developing Asian countries. Copyright © 2016 Elsevier Ltd. All rights reserved.

Atmospheric mercury speciation in Shanghai, China.

PubMed

Duan, Lian; Wang, Xiaohao; Wang, Dongfang; Duan, Yusen; Cheng, Na; Xiu, Guangli

2017-02-01

GEM (Gaseous elemental mercury), fine fraction (<2.5μm) PBM (Particle-bound mercury) and GOM (Gaseous oxidized mercury) were continuously monitored from Jun 1 to Dec 31 2014 at a suburban site in Shanghai. The average concentrations of GEM, PBM and GOM were 4.19±9.13ng·m -3 , 197±877pg·m -3 , 21±100pg·m -3 , respectively, which were all much higher than those at urban sites in Europe and North America and rural areas of China, but lower than those at urban sites of China. The concentrations of the three mercury species were all found with the highest concentration in December than those in summer. Overall, GEM varied little and PBM exhibited higher level during the night, while GOM typically peaked in the noon and afternoon which is consistent with that of ozone, indicating that GOM may depend on the stronger photochemical reactions during the daytime. Despite of the weak correlations of GEM with SO 2 (r=0.14, p<0.0001) and NO X (r=0.17, p<0.0001), GEM, PBM, SO 2 and NO x exhibited similar diurnal trend, suggesting that coal combustion might be the important sources of mercury in Shanghai because there is no mercury mining companies and few mercuric manufacturers in Shanghai. The strong correlation of PBM with GEM and GOM showed that directly anthropogenic emission was an important source of GEM and PBM, but the gas-particle partitioning of GOM and GEM might be also another source of PBM. The lower GEM/CO ratio of 3.9 (ng·m -3 ·ppmv -1 ) in Shanghai than that for mainland China and non-ferrous smelting factories were related to the few non-ferrous smelting factories around Shanghai. The results from the potential source contribution function (PSCF) model furtherly illustrated that in Shanghai the concentration of GEM in summer and autumn might be highly impacted by the local and regional source but wasn't heavily affected by long-range transport. Copyright © 2016 Elsevier B.V. All rights reserved.

Aerosol optical characteristics and their vertical distributions under enhanced haze pollution events: effect of the regional transport of different aerosol types over eastern China

NASA Astrophysics Data System (ADS)

Sun, Tianze; Che, Huizheng; Qi, Bing; Wang, Yaqiang; Dong, Yunsheng; Xia, Xiangao; Wang, Hong; Gui, Ke; Zheng, Yu; Zhao, Hujia; Ma, Qianli; Du, Rongguang; Zhang, Xiaoye

2018-03-01

The climatological variation of aerosol properties and the planetary boundary layer (PBL) during 2013-2015 over the Yangtze River Delta (YRD) region were investigated by employing ground-based Micro Pulse Lidar (MPL) and CE-318 sun-photometer observations. Combining Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite products, enhanced haze pollution events affected by different types of aerosol over the YRD region were analyzed through vertical structures, spatial distributions, backward trajectories, and the potential source contribution function (PSCF) model. The results show that aerosols in the YRD are dominated by fine-mode particles, except in March. The aerosol optical depth (AOD) in June and September is higher due to high single scattering albedo (SSA) from hygroscopic growth, but it is lower in July and August due to wet deposition from precipitation. The PBL height (PBLH) is greater (means ranging from 1.23 to 1.84 km) and more variable in the warmer months of March to August, due to the stronger diurnal cycle and exchange of heat. Northern fine-mode pollutants are brought to the YRD at a height of 1.5 km. The SSA increases, blocking the radiation to the surface, and cooling the surface, thereby weakening turbulence, lowering the PBL, and in turn accelerating the accumulation of pollutants, creating a feedback to the cooling effect. Originated from the deserts in Xinjiang and Inner Mongolia, long-range transported dust masses are seen at heights of about 2 km over the YRD region with an SSA440 nm below 0.84, which heat air and raise the PBL, accelerating the diffusion of dust particles. Regional transport from biomass-burning spots to the south of the YRD region bring mixed aerosol particles at a height below 1.5 km, resulting in an SSA440 nm below 0.89. During the winter, the accumulation of the local emission layer is facilitated by stable weather conditions, staying within the PBL even below 0.5 km.

Characteristics and source distribution of air pollution in winter in Qingdao, eastern China.

PubMed

Li, Lingyu; Yan, Dongyun; Xu, Shaohui; Huang, Mingli; Wang, Xiaoxia; Xie, Shaodong

2017-05-01

To characterize air pollution and determine its source distribution in Qingdao, Shandong Province, we analyzed hourly national air quality monitoring network data of normal pollutants at nine sites from 1 November 2015 to 31 January 2016. The average hourly concentrations of particulate matter <2.5 μm (PM 2.5 ) and <10 μm (PM 10 ), SO 2 , NO 2 , 8-h O 3 , and CO in Qingdao were 83, 129, 39, 41, and 41 μg m -3 , and 1.243 mg m -3 , respectively. During the polluted period, 19-26 December 2015, 29 December 2015 to 4 January 2016, and 14-17 January 2016, the mean 24-h PM 2.5 concentration was 168 μg m -3 with maximum of 311 μg m -3 . PM 2.5 was the main pollutant to contribute to the pollution during the above time. Heavier pollution and higher contributions of secondary formation to PM 2.5 concentration were observed in December and January. Pollution pathways and source distribution were investigated using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and potential source contribution function (PSCF) and concentration weighted trajectory (CWT) analyses. A cluster from the west, originating in Shanxi, southern Hebei, and west Shandong Provinces, accounted for 44.1% of the total air masses, had a mean PM 2.5 concentration of 134.9 μg m -3 and 73.9% trajectories polluted. This area contributed the most to PM 2.5 and PM 10 levels, >160 and 300 μg m -3 , respectively. In addition, primary crustal aerosols from desert of Inner Mongolia, and coarse and fine marine aerosols from the Yellow Sea contributed to ambient PM. The ambient pollutant concentrations in Qingdao in winter could be attributed to local primary emissions (e.g., coal combustion, vehicular, domestic and industrial emissions), secondary formation, and long distance transmission of emissions. Copyright © 2016 Elsevier Ltd. All rights reserved.

PM2.5 in the Yangtze River Delta, China: Chemical compositions, seasonal variations, and regional pollution events.

PubMed

Ming, Lili; Jin, Ling; Li, Jun; Fu, Pingqing; Yang, Wenyi; Liu, Di; Zhang, Gan; Wang, Zifa; Li, Xiangdong

2017-04-01

Fine particle (PM 2.5 ) samples were collected simultaneously at three urban sites (Shanghai, Nanjing, and Hangzhou) and one rural site near Ningbo in the Yangtze River Delta (YRD) region, China, on a weekly basis from September 2013 to August 2014. In addition, high-frequency daily sampling was conducted in Shanghai and Nanjing for one month during each season. Severe regional PM 2.5 pollution episodes were frequently observed in the YRD, with annual mean concentrations of 94.6 ± 55.9, 97.8 ± 40.5, 134 ± 54.3, and 94.0 ± 57.6 μg m -3 in Shanghai, Nanjing, Hangzhou, and Ningbo, respectively. The concentrations of PM 2.5 and ambient trace metals at the four sites showed clear seasonal trends, with higher concentrations in winter and lower concentrations in summer. In Shanghai, similar seasonal patterns were found for organic carbon (OC), elemental carbon (EC), and water-soluble inorganic ions (K + , NH 4 + , Cl - , NO 3 - , and SO 4 2- ). Air mass backward trajectory and potential source contribution function (PSCF) analyses implied that areas of central and northern China contributed significantly to the concentration and chemical compositions of PM 2.5 in Shanghai during winter. Three heavy pollution events in Shanghai were observed during autumn and winter. The modelling results of the Nested Air Quality Prediction Modeling System (NAQPMS) showed the sources and transport of PM 2.5 in the YRD during the three pollution processes. The contribution of secondary species (SOC, NH 4 + , NO 3 - , and SO 4 2- ) in pollution event (PE) periods was much higher than in BPE (before pollution event) and APE (after pollution event) periods, suggesting the importance of secondary aerosol formation during the three pollution events. Furthermore, the bioavailability of Cu, and Zn in the wintertime PM 2.5 samples from Shanghai was much higher during the pollution days than during the non-pollution days. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterization of atmospheric trace gases and particulate matter in Hangzhou, China

NASA Astrophysics Data System (ADS)

Zhang, Gen; Xu, Honghui; Qi, Bing; Du, Rongguang; Gui, Ke; Wang, Hongli; Jiang, Wanting; Liang, Linlin; Xu, Wanyun

2018-02-01

The Yangtze River Delta (YRD) is one of the most densely populated regions in China with severe air quality issues that have not been fully understood. Thus, in this study, based on 1-year (2013) continuous measurement at a National Reference Climatological Station (NRCS, 30.22° N, 120.17° E; 41.7 m a.s.l.) in the center of Hangzhou in the YRD, we investigated the seasonal characteristics, interspecies relationships, and the local emissions and the regional potential source contributions of trace gases (including O3, NOx, NOy, SO2, and CO) and particulate matter (PM2.5 and PM10). Results revealed that severe two-tier air pollution (photochemical and haze pollution) occurred in this region, with frequent exceedances in O3 (38 days) and PM2.5 (62 days). O3 and PM2.5 both exhibited distinct seasonal variations with reversed patterns: O3 reaching a maximum in warm seasons (May and July) but PM2.5 reaching a maximum in cold seasons (November to January). The overall results from interspecies correlation indicated a strong local photochemistry favoring the O3 production under a volatile organic compound (VOC)-limited regime, whereas it moved towards an optimum O3 production zone during warm seasons, accompanied by the formation of secondary fine particulates under high O3. The emission maps of PM2.5, CO, NOx, and SO2 demonstrated that local emissions were significant for these species on a seasonal scale. The contributions from the regional transport among inland cities (Zhejiang, Jiangsu, Anhui, and Jiangxi Province) on a seasonal scale were further confirmed to be crucial to air pollution at the NRCS site by using backward trajectory simulations. Air masses transported from the offshore areas of the Yellow Sea, East Sea, and South Sea were also found to be highly relevant to the elevated O3 at the NRCS site through the analysis of potential source contribution function (PSCF). Case studies of photochemical pollution (O3) and haze (PM2.5) episodes both suggested the combined importance of local atmospheric photochemistry and synoptic conditions during the accumulation (related with anticyclones) and dilution process (related with cyclones). Apart from supplementing a general picture of the air pollution state in the city of Hangzhou in the YRD region, this study specifically elucidates the role of local emission and regional transport, and it interprets the physical and photochemical processes during haze and photochemical pollution episodes. Moreover, this work suggests that cross-regional control measures are crucial to improve air quality in the YRD region, and it further emphasizes the importance of local thermally induced circulation for air quality.

Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

NASA Astrophysics Data System (ADS)

Liu, Baoshuang; Cheng, Yuan; Zhou, Ming; Liang, Danni; Dai, Qili; Wang, Lu; Jin, Wei; Zhang, Lingzhi; Ren, Yibin; Zhou, Jingbo; Dai, Chunling; Xu, Jiao; Wang, Jiao; Feng, Yinchang; Zhang, Yufen

2018-05-01

To evaluate the environmental effectiveness of the control measures for atmospheric pollution in Shijiazhuang, China, a large-scale controlling experiment for emission sources of atmospheric pollutants (i.e. a temporary emission control action, TECA) was designed and implemented during 1 November 2016 to 9 January 2017. Compared to the no-control action and heating period (NCAHP), under unfavourable meteorological conditions, the mean concentrations of PM2.5, PM10, SO2, NO2, and chemical species (Si, Al, Ca2+, Mg2+) in PM2.5 during the control action and heating period (CAHP) still decreased by 8, 8, 5, 19, 30.3, 4.5, 47.0, and 45.2 %, respectively, indicating that the control measures for atmospheric pollution were effective. The effects of control measures in suburbs were better than those in urban area, especially for the control effects of particulate matter sources. The control effects for emission sources of carbon monoxide (CO) were not apparent during the TECA period, especially in suburbs, likely due to the increasing usage of domestic coal in suburbs along with the temperature decreasing.The results of positive matrix factorization (PMF) analysis showed that crustal dust, secondary sources, vehicle emissions, coal combustion and industrial emissions were main PM2.5 sources. Compared to the whole year (WY) and the no-control action and no-heating period (NCANHP), the contribution concentrations and proportions of coal combustion to PM2.5 increased significantly during other stages of the TECA period. The contribution concentrations and proportions of crustal dust and vehicle emissions to PM2.5 decreased noticeably during the CAHP compared to other stages of the TECA period. The contribution concentrations and proportions of industrial emissions to PM2.5 during the CAHP decreased noticeably compared to the NCAHP. The pollutants' emission sources during the CAHP were in effective control, especially for crustal dust and vehicles. However, the necessary coal heating for the cold winter and the unfavourable meteorological conditions had an offset effect on the control measures for emission sources to some degree. The results also illustrated that the discharge of pollutants might still be enormous even under such strict control measures.The backward trajectory and potential source contribution function (PSCF) analysis in the light of atmospheric pollutants suggested that the potential source areas mainly involved the surrounding regions of Shijiazhuang, i.e. south of Hebei and north of Henan and Shanxi. The regional nature of the atmospheric pollution in the North China Plain revealed that there is an urgent need for making cross-boundary control policies in addition to local control measures given the high background level of pollutants.The TECA is an important practical exercise but it cannot be advocated for as the normalized control measures for atmospheric pollution in China. The direct cause of atmospheric pollution in China is the emission of pollutants exceeding the air environment's self-purification capacity, which is caused by an unreasonable and unhealthy pattern for economic development in China.

Wintertime characteristic of peroxyacetyl nitrate in the Chengyu district of southwestern China.

PubMed

Zhu, Honglin; Gao, Tianyu; Zhang, Jianbo

2018-06-02

Atmospheric concentrations of peroxyacetyl nitrate (PAN) were measured in Ziyang in December 2012 to provide basic knowledge of PAN in the Chengyu district and offer recommendations for air pollution management. The PAN pollution was relatively severe in Ziyang in winter, with the maximum and average PAN concentrations of 1.61 and 0.55 ppbv, respectively, and a typical single-peak diurnal trend in PAN and theoretical PAN lost by thermal decomposition (TPAN) were observed. PAN and O 3 concentrations were correlated (R 2  = 0.52) and the ratios of daily maximum PAN to O 3 ([PAN]/[O 3 ] ratio) ranged from 0.013 to 0.108, with an average of 0.038. Both acetone and methyl ethyl ketone (MEK) were essential for producing the acetylperoxy radicals (PA) and subsequently PAN in Ziyang in winter, and PAN concentrations at the sampling site exhibited more sensitivity to volatile organic compound (VOC) concentrations than nitrogen oxide (NO x ) levels. Therefore, management should focus on reducing VOCs emissions, in particular those that produce acetone and MEK through photolysis and oxidizing reactions. In addition, the influence of relative humidity (RH) on the heterogeneous reactions between PAN and PM 2.5 in the atmospheric environment may have led to the strong correlation between observed PM 2.5 and PAN in Ziyang in winter. Furthermore, a typical air pollution event was observed on 17-18 December 2012, which Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and PSCF simulations suggest that it was caused by the local formation and the regional transport of polluted air masses from Hanzhong, Nanchong, and Chengdu.

Estimated Accuracy of Three Common Trajectory Statistical Methods

NASA Technical Reports Server (NTRS)

Kabashnikov, Vitaliy P.; Chaikovsky, Anatoli P.; Kucsera, Tom L.; Metelskaya, Natalia S.

2011-01-01

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Observation of regional air pollutant transport between the megacity Beijing and the North China Plain

NASA Astrophysics Data System (ADS)

Li, Yingruo; Ye, Chunxiang; Liu, Jun; Zhu, Yi; Wang, Junxia; Tan, Ziqiang; Lin, Weili; Zeng, Limin; Zhu, Tong

2016-11-01

Megacities have strong interactions with the surrounding regions through transport of air pollutants. It has been frequently addressed that the air quality of Beijing is influenced by the influx of air pollutants from the North China Plain (NCP). Estimations of air pollutant cross-boundary transport between Beijing and the NCP are important for air quality management. However, evaluation of cross-boundary transport using long-term observations is very limited. Using the observational results of the gaseous pollutants SO2, NO, NO2, O3, and CO from August 2006 to October 2008 at the Yufa site, a cross-boundary site between the megacity Beijing and the NCP, together with meteorological parameters, we explored a method for evaluating the transport flux intensities at Yufa, as part of the "Campaign of Air Quality Research in Beijing and Surrounding Region 2006-2008" (CAREBeijing 2006-2008). The hourly mean ± SD (median) concentration of SO2, NO, NO2, NOx, O3, Ox, and CO was 15 ± 16 (9) ppb, 12 ± 25 (3) ppb, 24 ± 19 (20) ppb, 36 ± 39 (23) ppb, 28 ± 27 (21) ppb, 52 ± 24 (45) ppb, and 1.6 ± 1.4 (1.2) ppm during the observation period, respectively. The bivariate polar plots showed the dependence of pollutant concentrations on both wind speed and wind direction, and thus inferred their dominant transport directions. Surface flux intensity calculations further demonstrated the regional transport influence of Beijing and the NCP on Yufa. The net surface transport flux intensity (mean ± SD) of SO2, NO, NO2, NOx, O3, Ox, and CO was 6.2 ± 89.5, -4.3 ± 29.5, -0.6 ± 72.3, -4.9 ± 93.0, 14.7 ± 187.8, 14.8 ± 234.9, and 70 ± 2830 µg s-1 m-2 during the observation period, respectively. For SO2, CO, O3, and Ox the surface flux intensities from the NCP to Yufa surpassed those from Beijing to Yufa in all seasons except winter, with the strongest net fluxes largely in summer, which were about 4-8 times those of other seasons. The surface transport flux intensity of NOx from Beijing to Yufa was stronger than that from the NCP to Yufa except in summer, with the strongest net flux in winter, which was about 1.3-8 times that of other seasons. The flux intensities were then assigned to the corresponding trajectories in the potential source contribution function analysis (PSCF), which confirmed the results of flux intensity calculations. Our study also suggested that various factors, such as the wind field, emission inventory, and photochemical reactions, could influence transport of air pollutants. The decrease of surface flux intensity during the Olympic Games implied the role of both local emission reduction and regional cooperation in successful air quality management. Three dimensional observations are needed for further comprehensive discussion of the regional transport between Beijing and the NCP.

Molecular distribution, seasonal variation, chemical transformation and sources of dicarboxylic acids and related compounds in atmospheric aerosols at remote marine Gosan site, Jeju Island

NASA Astrophysics Data System (ADS)

Kundu, S.; Kawamura, K.; Lee, M.

2009-12-01

: A homologous series of C2-C12 α, ω-dicarboxylic acids, ω-oxocarboxylic acids (C2-C9), pyruvic acid and α-dicarbonyls (C2-C3) were detected in atmospheric aerosols collected between April 2003 and April 2004 from remote marine Gosan site (33°29‧ N, 126°16‧ E) located in Jeju Island, South Korea. They were determined using a GC-FID and GC/MS. Total diacid concentration ranged from 130 to 1911 ng m-3 (av. 642 ng m-3), whereas total oxoacid concentration ranged from 7 to 155 ng m-3 (av. 43 ng m-3), and pyruvic acid and α-dicarbonyls ranged from 0.5 to 15 ng m-3 (av. 5 ng m-3) and 2-108 ng m-3 (av. 17.3 ng m-3), respectively. Oxalic (C2) acid was the most abundant in all seasons followed by malonic (C3) or succinic (C4) acid, and phthalic (Ph) acid. The concentration of diacids decreased with an increase in carbon number except for azelaic (C9) acid, which was more abundant than suberic (C8) acid. Glyoxylic acid was predominant ω-oxoacid contributing to 92% of total ω-oxoacid. Total diacids, oxoacids and dicarbonyls showed maximum concentrations in spring and occasionally in winter, while minimum concentrations were observed in summer. Air mass trajectory analysis suggests that either spring or winter maxima can be explained by strong continental outflow associated with cold front passages, while summer minima are associated with warm southerly flows, which transport clean marine air from low latitudes to Jeju Island. The comparison between total diacid concentration level of this study and other study results of urban and remote sites of East Asia reveals that Gosan site is more heavily influenced by the continental outflow from China. The seasonal variation of malonic/succinic (C3/C4), malic/succinic (hC4/C4), fumaric/maleic (F/M), oxalic/pyruvic (C2/Py) and oxalic/Glyoxal (C2/Gly) ratios showed maxima in summer due to an enhanced photo-production and degradation of diacids and related compounds. Throughout all seasons C3/C4 ratio at Gosan site, located between Chinese cities and Chichi-jima Island in Japan was observed higher than those in Chinese cities and lower than that of the Chichi-jima Island, pointing to the formation of diacid during long range transport. The lowest values of adipic/azelaic (C6/C9) and phthalic/azelaic (Ph/C9) were observed as a result of the overwhelming biogenic emission of the precursors (e.g., unsaturated fatty acids) of azelaic acid in summer.In this study, we will also discuss the sources and transport pathways of diacids and related compounds resolved using a hybrid receptor model, potential source contribution function (PSCF) and model results will be compared with available in-situ observations in East Asia.

Variations in particulate matter over Indo-Gangetic Plains and Indo-Himalayan Range during four field campaigns in winter monsoon and summer monsoon: Role of pollution pathways

NASA Astrophysics Data System (ADS)

Sen, A.; Abdelmaksoud, A. S.; Nazeer Ahammed, Y.; Alghamdi, Mansour ِA.; Banerjee, Tirthankar; Bhat, Mudasir Ahmad; Chatterjee, A.; Choudhuri, Anil K.; Das, Trupti; Dhir, Amit; Dhyani, Pitamber Prasad; Gadi, Ranu; Ghosh, Sanjay; Kumar, Kireet; Khan, A. H.; Khoder, M.; Maharaj Kumari, K.; Kuniyal, Jagdish Chandra; Kumar, Manish; Lakhani, Anita; Mahapatra, Parth Sarathi; Naja, Manish; Pal, Dharam; Pal, S.; Rafiq, Mahammad; Romshoo, Shakil Ahmad; Rashid, Irfan; Saikia, Prasenjit; Shenoy, D. M.; Sridhar, Vijay; Verma, Nidhi; Vyas, B. M.; Saxena, Mohit; Sharma, A.; Sharma, S. K.; Mandal, T. K.

2017-04-01

Both in-situ and space-borne observations reveal an extremely high loading of particulates over the Indo-Gangetic Plains (IGP), all year around. With a burgeoning population and combustion sources (fossil fuels (FFs) and biofuels (BFs)) in close proximity to each other, the IGP is widely regarded as a hotspot for anthropogenic aerosol emission in South Asia. The deteriorating air quality over this region, particularly during winters, is a cause of major concern, since the pollutants undergo long range transport from their source regions to the Indo-Himalayan Range (IHR), Bay of Bengal (BoB) and other remote areas, polluting their pristine atmospheric conditions. Seasonal reversal in winds over the Indian mainland leads to an outflow of continental pollutants into the BoB during winters and a net advection of desert dust aerosols into the IGP from southwest Asia (SW-Asia), northwest India (NW-India) and northern Africa (N-Africa) during summers. Through the course of this study, four observational campaigns were conducted for sampling the ambient PM2.5 and PM10 during winter and summer seasons of 2014-2015, at multiple locations (18 sites) in the IGP, IHR, and semi-arid/arid sites towards their south and west, in order to accurately determine the inter-seasonal and inter-annual changes in the aerosol loading at the sites. We have also utilized data from Moderate Resolution Imaging Spectroradiometer (MODIS) on-board Earth Observing System (EOS) Terra satellite for estimating the columnar Aerosol Optical Depth at 550 nm (AOD550) and data from EOS Terra and Aqua satellites for discovering openly burning fires in the vicinity of sampling sites. Determination of the major source regions and key transport pathways during both seasons have also been attempted, using back-trajectory cluster analyses, as well as receptor models such as PSCF and CWT.

Advances in the indirect, descriptive, and experimental approaches to the functional analysis of problem behavior.

PubMed

Wightman, Jade; Julio, Flávia; Virués-Ortega, Javier

2014-05-01

Experimental functional analysis is an assessment methodology to identify the environmental factors that maintain problem behavior in individuals with developmental disabilities and in other populations. Functional analysis provides the basis for the development of reinforcement-based approaches to treatment. This article reviews the procedures, validity, and clinical implementation of the methodological variations of functional analysis and function-based interventions. We present six variations of functional analysis methodology in addition to the typical functional analysis: brief functional analysis, single-function tests, latency-based functional analysis, functional analysis of precursors, and trial-based functional analysis. We also present the three general categories of function-based interventions: extinction, antecedent manipulation, and differential reinforcement. Functional analysis methodology is a valid and efficient approach to the assessment of problem behavior and the selection of treatment strategies.

Measurements of aerosol and CCN properties in the Mackenzie River delta (Canadian Arctic) during spring-summer transition in May 2014

NASA Astrophysics Data System (ADS)

Herenz, Paul; Wex, Heike; Henning, Silvia; Bjerring Kristensen, Thomas; Rubach, Florian; Roth, Anja; Borrmann, Stephan; Bozem, Heiko; Schulz, Hannes; Stratmann, Frank

2018-04-01

Within the framework of the RACEPAC (Radiation-Aerosol-Cloud Experiment in the Arctic Circle) project, the Arctic aerosol, arriving at a ground-based station in Tuktoyaktuk (Mackenzie River delta area, Canada), was characterized during a period of 3 weeks in May 2014. Basic meteorological parameters and particle number size distributions (PNSDs) were observed and two distinct types of air masses were found. One type were typical Arctic haze air masses, termed accumulation-type air masses, characterized by a monomodal PNSD with a pronounced accumulation mode at sizes above 100 nm. These air masses were observed during a period when back trajectories indicate an air mass origin in the north-east of Canada. The other air mass type is characterized by a bimodal PNSD with a clear minimum around 90 nm and with an Aitken mode consisting of freshly formed aerosol particles. Back trajectories indicate that these air masses, termed Aitken-type air masses, originated from the North Pacific. In addition, the application of the PSCF receptor model shows that air masses with their origin in active fire areas in central Canada and Siberia, in areas of industrial anthropogenic pollution (Norilsk and Prudhoe Bay Oil Field) and the north-west Pacific have enhanced total particle number concentrations (NCN). Generally, NCN ranged from 20 to 500 cm-3, while cloud condensation nuclei (CCN) number concentrations were found to cover a range from less than 10 up to 250 cm-3 for a supersaturation (SS) between 0.1 and 0.7 %. The hygroscopicity parameter κ of the CCN was determined to be 0.23 on average and variations in κ were largely attributed to measurement uncertainties. Furthermore, simultaneous PNSD measurements at the ground station and on the Polar 6 research aircraft were performed. We found a good agreement of ground-based PNSDs with those measured between 200 and 1200 m. During two of the four overflights, particle number concentrations at 3000 m were found to be up to 20 times higher than those measured below 2000 m; for one of these two flights, PNSDs measured above 2000 m showed a different shape than those measured at lower altitudes. This is indicative of long-range transport from lower latitudes into the Arctic that can advect aerosol from different regions in different heights.

FMAP: Functional Mapping and Analysis Pipeline for metagenomics and metatranscriptomics studies.

PubMed

Kim, Jiwoong; Kim, Min Soo; Koh, Andrew Y; Xie, Yang; Zhan, Xiaowei

2016-10-10

Given the lack of a complete and comprehensive library of microbial reference genomes, determining the functional profile of diverse microbial communities is challenging. The available functional analysis pipelines lack several key features: (i) an integrated alignment tool, (ii) operon-level analysis, and (iii) the ability to process large datasets. Here we introduce our open-sourced, stand-alone functional analysis pipeline for analyzing whole metagenomic and metatranscriptomic sequencing data, FMAP (Functional Mapping and Analysis Pipeline). FMAP performs alignment, gene family abundance calculations, and statistical analysis (three levels of analyses are provided: differentially-abundant genes, operons and pathways). The resulting output can be easily visualized with heatmaps and functional pathway diagrams. FMAP functional predictions are consistent with currently available functional analysis pipelines. FMAP is a comprehensive tool for providing functional analysis of metagenomic/metatranscriptomic sequencing data. With the added features of integrated alignment, operon-level analysis, and the ability to process large datasets, FMAP will be a valuable addition to the currently available functional analysis toolbox. We believe that this software will be of great value to the wider biology and bioinformatics communities.

Evaluation of the utility of a discrete-trial functional analysis in early intervention classrooms.

PubMed

Kodak, Tiffany; Fisher, Wayne W; Paden, Amber; Dickes, Nitasha

2013-01-01

We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures. © Society for the Experimental Analysis of Behavior.

Functional Multiple-Set Canonical Correlation Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

Evaluation of the Utility of a Discrete-Trial Functional Analysis in Early Intervention Classrooms

ERIC Educational Resources Information Center

Kodak, Tiffany; Fisher, Wayne W.; Paden, Amber; Dickes, Nitasha

2013-01-01

We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures.

Functional analysis screening for multiple topographies of problem behavior.

PubMed

Bell, Marlesha C; Fahmie, Tara A

2018-04-23

The current study evaluated a screening procedure for multiple topographies of problem behavior in the context of an ongoing functional analysis. Experimenters analyzed the function of a topography of primary concern while collecting data on topographies of secondary concern. We used visual analysis to predict the function of secondary topographies and a subsequent functional analysis to test those predictions. Results showed that a general function was accurately predicted for five of six (83%) secondary topographies. A specific function was predicted and supported for a subset of these topographies. The experimenters discuss the implication of these results for clinicians who have limited time for functional assessment. © 2018 Society for the Experimental Analysis of Behavior.

Functional Analysis and Treatment of Nail Biting

ERIC Educational Resources Information Center

Dufrene, Brad A.; Watson, T. Steuart; Kazmerski, Jennifer S.

2008-01-01

This study applied functional analysis methodology to nail biting exhibited by a 24-year-old female graduate student. Results from the brief functional analysis indicated variability in nail biting across assessment conditions. Functional analysis data were then used to guide treatment development and implementation. Treatment included a…

A Primer on Functional Analysis

ERIC Educational Resources Information Center

Yoman, Jerome

2008-01-01

This article presents principles and basic steps for practitioners to complete a functional analysis of client behavior. The emphasis is on application of functional analysis to adult mental health clients. The article includes a detailed flow chart containing all major functional diagnoses and behavioral interventions, with functional assessment…

Discrete-Trial Functional Analysis and Functional Communication Training with Three Adults with Intellectual Disabilities and Problem Behavior

ERIC Educational Resources Information Center

Chezan, Laura C.; Drasgow, Erik; Martin, Christian A.

2014-01-01

We conducted a sequence of two studies on the use of discrete-trial functional analysis and functional communication training. First, we used discrete-trial functional analysis (DTFA) to identify the function of problem behavior in three adults with intellectual disabilities and problem behavior. Results indicated clear patterns of problem…

Alterations to Functional Analysis Methodology to Clarify the Functions of Low Rate, High Intensity Problem Behavior

PubMed Central

Davis, Barbara J; Schmidt, Jonathan; Bowman, Lynn G; Boelter, Eric W

2012-01-01

Current research provides few suggestions for modifications to functional analysis procedures to accommodate low rate, high intensity problem behavior. This study examined the results of the extended duration functional analysis procedures of Kahng, Abt, and Schonbachler (2001) with six children admitted to an inpatient hospital for the treatment of severe problem behavior. Results of initial functional analyses (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) were inconclusive for all children because of low levels of responding. The altered functional analyses, which changed multiple variables including the duration of the functional analysis (i.e., 6 or 7 hrs), yielded clear behavioral functions for all six participants. These results add additional support for the utility of an altered analysis of low rate, high intensity problem behavior when standard functional analyses do not yield differentiated results. PMID:23326628

Alterations to functional analysis methodology to clarify the functions of low rate, high intensity problem behavior.

PubMed

Davis, Barbara J; Kahng, Sungwoo; Schmidt, Jonathan; Bowman, Lynn G; Boelter, Eric W

2012-01-01

Current research provides few suggestions for modifications to functional analysis procedures to accommodate low rate, high intensity problem behavior. This study examined the results of the extended duration functional analysis procedures of Kahng, Abt, and Schonbachler (2001) with six children admitted to an inpatient hospital for the treatment of severe problem behavior. Results of initial functional analyses (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) were inconclusive for all children because of low levels of responding. The altered functional analyses, which changed multiple variables including the duration of the functional analysis (i.e., 6 or 7 hrs), yielded clear behavioral functions for all six participants. These results add additional support for the utility of an altered analysis of low rate, high intensity problem behavior when standard functional analyses do not yield differentiated results.

Using Trial-Based Functional Analysis to Design Effective Interventions for Students Diagnosed with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Larkin, Wallace; Hawkins, Renee O.; Collins, Tai

2016-01-01

Functional behavior assessments and function-based interventions are effective methods for addressing the challenging behaviors of children; however, traditional functional analysis has limitations that impact usability in applied settings. Trial-based functional analysis addresses concerns relating to the length of time, level of expertise…

A Quantitative Review of Functional Analysis Procedures in Public School Settings

ERIC Educational Resources Information Center

Solnick, Mark D.; Ardoin, Scott P.

2010-01-01

Functional behavioral assessments can consist of indirect, descriptive and experimental procedures, such as a functional analysis. Although the research contains numerous examples demonstrating the effectiveness of functional analysis procedures, experimental conditions are often difficult to implement in classroom settings and analog conditions…

Analysis of Social Variables when an Initial Functional Analysis Indicates Automatic Reinforcement as the Maintaining Variable for Self-Injurious Behavior

ERIC Educational Resources Information Center

Kuhn, Stephanie A. Contrucci; Triggs, Mandy

2009-01-01

Self-injurious behavior (SIB) that occurs at high rates across all conditions of a functional analysis can suggest automatic or multiple functions. In the current study, we conducted a functional analysis for 1 individual with SIB. Results indicated that SIB was, at least in part, maintained by automatic reinforcement. Further analyses using…

Effects of Computer-Based Training on Procedural Modifications to Standard Functional Analyses

ERIC Educational Resources Information Center

Schnell, Lauren K.; Sidener, Tina M.; DeBar, Ruth M.; Vladescu, Jason C.; Kahng, SungWoo

2018-01-01

Few studies have evaluated methods for training decision-making when functional analysis data are undifferentiated. The current study evaluated computer-based training to teach 20 graduate students to arrange functional analysis conditions, analyze functional analysis data, and implement procedural modifications. Participants were exposed to…

Functional analysis and treatment of diurnal bruxism.

PubMed

Lang, Russell; Davenport, Katy; Britt, Courtney; Ninci, Jennifer; Garner, Jennifer; Moore, Melissa

2013-01-01

An analogue functional analysis identified attention as a function for a 5-year-old boy's bruxism (teeth grinding). Functional communication training resulted in a reduction of bruxism and an increase in alternative mands for attention. Results were maintained 3 weeks following the intervention. © Society for the Experimental Analysis of Behavior.

Differential Item Functioning Analysis Using Rasch Item Information Functions

ERIC Educational Resources Information Center

Wyse, Adam E.; Mapuranga, Raymond

2009-01-01

Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…

Linking Brief Functional Analysis to Intervention Design in General Education Settings

ERIC Educational Resources Information Center

Ishuin, Tifanie

2009-01-01

This study focused on the utility and applicability of brief functional analysis in general education settings. The purpose of the study was to first identify the environmental variables maintaining noncompliance through a brief functional analysis, and then to design and implement a functionally equivalent intervention. The participant exhibited…

Assessing the Social Acceptability of the Functional Analysis of Problem Behavior

ERIC Educational Resources Information Center

Langthorne, Paul; McGill, Peter

2011-01-01

Although the clinical utility of the functional analysis is well established, its social acceptability has received minimal attention. The current study assessed the social acceptability of functional analysis procedures among 10 parents and 3 teachers of children who had recently received functional analyses. Participants completed a 9-item…

A statewide survey assessing practitioners' use and perceived utility of functional assessment.

PubMed

Roscoe, Eileen M; Phillips, Katurri M; Kelly, Maureen A; Farber, Rachel; Dube, William V

2015-12-01

The field of applied behavior analysis emphasizes the importance of conducting functional assessment before treatment development for problem behavior. There is, however, little information regarding the extent to which practitioners are using functional assessment in applied settings for individuals with developmental disabilities (DD). The purpose of the current study was to conduct a survey to assess the degree to which various types of functional assessment are implemented in agencies that serve individuals with DD in Massachusetts. Practitioners were asked to indicate their perception about and use of the various categories of functional assessment (e.g., indirect assessment, descriptive assessment, and functional analysis). From the 205 respondents who completed the survey, the most frequently used functional assessment was descriptive assessment. Results indicated that although the majority (67.8%) of practitioners believe functional analysis to be the most informative assessment tool for selecting behavioral treatment, only 34.6% of respondents indicated that they typically use functional analysis to inform the development of a behavior plan. © Society for the Experimental Analysis of Behavior.

Advanced Connectivity Analysis (ACA): a Large Scale Functional Connectivity Data Mining Environment.

PubMed

Chen, Rong; Nixon, Erika; Herskovits, Edward

2016-04-01

Using resting-state functional magnetic resonance imaging (rs-fMRI) to study functional connectivity is of great importance to understand normal development and function as well as a host of neurological and psychiatric disorders. Seed-based analysis is one of the most widely used rs-fMRI analysis methods. Here we describe a freely available large scale functional connectivity data mining software package called Advanced Connectivity Analysis (ACA). ACA enables large-scale seed-based analysis and brain-behavior analysis. It can seamlessly examine a large number of seed regions with minimal user input. ACA has a brain-behavior analysis component to delineate associations among imaging biomarkers and one or more behavioral variables. We demonstrate applications of ACA to rs-fMRI data sets from a study of autism.

Comparative analysis of taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors by metagenomic sequencing and radioisotopic analysis.

PubMed

Luo, Gang; Fotidis, Ioannis A; Angelidaki, Irini

2016-01-01

Biogas production is a very complex process due to the high complexity in diversity and interactions of the microorganisms mediating it, and only limited and diffuse knowledge exists about the variation of taxonomic and functional patterns of microbiomes across different biogas reactors, and their relationships with the metabolic patterns. The present study used metagenomic sequencing and radioisotopic analysis to assess the taxonomic, functional, and metabolic patterns of microbiomes from 14 full-scale biogas reactors operated under various conditions treating either sludge or manure. The results from metagenomic analysis showed that the dominant methanogenic pathway revealed by radioisotopic analysis was not always correlated with the taxonomic and functional compositions. It was found by radioisotopic experiments that the aceticlastic methanogenic pathway was dominant, while metagenomics analysis showed higher relative abundance of hydrogenotrophic methanogens. Principal coordinates analysis showed the sludge-based samples were clearly distinct from the manure-based samples for both taxonomic and functional patterns, and canonical correspondence analysis showed that the both temperature and free ammonia were crucial environmental variables shaping the taxonomic and functional patterns. The study further the overall patterns of functional genes were strongly correlated with overall patterns of taxonomic composition across different biogas reactors. The discrepancy between the metabolic patterns determined by metagenomic analysis and metabolic pathways determined by radioisotopic analysis was found. Besides, a clear correlation between taxonomic and functional patterns was demonstrated for biogas reactors, and also the environmental factors that shaping both taxonomic and functional genes patterns were identified.

Brief functional analysis and treatment of a vocal tic.

PubMed

Watson, T S; Sterling, H E

1998-01-01

This study sought to extend functional methodology to the assessment and treatment of habits. After a descriptive assessment indicated that coughing occurred while eating, a brief functional analysis suggested that social attention was the maintaining variable. Results demonstrated that treatment, derived from the assessment and analysis data, rapidly eliminated the cough. We discuss the appropriateness of using functional analysis procedures for deriving treatments for habits in a clinical setting.

Nonparametric Bayesian models for a spatial covariance.

PubMed

Reich, Brian J; Fuentes, Montserrat

2012-01-01

A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

An exploration of function analysis and function allocation in the commercial flight domain

NASA Technical Reports Server (NTRS)

Mcguire, James C.; Zich, John A.; Goins, Richard T.; Erickson, Jeffery B.; Dwyer, John P.; Cody, William J.; Rouse, William B.

1991-01-01

The applicability is explored of functional analysis methods to support cockpit design. Specifically, alternative techniques are studied for ensuring an effective division of responsibility between the flight crew and automation. A functional decomposition is performed of the commercial flight domain to provide the information necessary to support allocation decisions and demonstrate methodology for allocating functions to flight crew or to automation. The function analysis employed 'bottom up' and 'top down' analyses and demonstrated the comparability of identified functions, using the 'lift off' segment of the 'take off' phase as a test case. The normal flight mission and selected contingencies were addressed. Two alternative methods for using the functional description in the allocation of functions between man and machine were investigated. The two methods were compared in order to ascertain their relative strengths and weaknesses. Finally, conclusions were drawn regarding the practical utility of function analysis methods.

Turkish Special Education Teachers' Implementation of Functional Analysis in Classroom Settings

ERIC Educational Resources Information Center

Erbas, Dilek; Yucesoy, Serife; Turan, Yasemin; Ostrosky, Michaelene M.

2006-01-01

Three Turkish special education teachers conducted a functional analysis to identify variables that might initiate or maintain the problem behaviors of three children with developmental disabilities. The analysis procedures were conducted in natural classroom settings. In Phase 1, following initial training in functional analysis procedures, the…

False Positive Functional Analysis Results as a Contributor of Treatment Failure during Functional Communication Training

ERIC Educational Resources Information Center

Mann, Amanda J.; Mueller, Michael M.

2009-01-01

Research has shown that functional analysis results are beneficial for treatment selection because they identify reinforcers for severe behavior that can then be used to reinforce replacement behaviors either differentially or noncontingently. Theoretically then, if a reinforcer is identified in a functional analysis erroneously, a well researched…

A Systematic Review of Brief Functional Analysis Methodology with Typically Developing Children

ERIC Educational Resources Information Center

Gardner, Andrew W.; Spencer, Trina D.; Boelter, Eric W.; DuBard, Melanie; Jennett, Heather K.

2012-01-01

Brief functional analysis (BFA) is an abbreviated assessment methodology derived from traditional extended functional analysis methods. BFAs are often conducted when time constraints in clinics, schools or homes are of concern. While BFAs have been used extensively to identify the function of problem behavior for children with disabilities, their…

HSI top-down requirements analysis for ship manpower reduction

NASA Astrophysics Data System (ADS)

Malone, Thomas B.; Bost, J. R.

2000-11-01

U.S. Navy ship acquisition programs such as DD 21 and CVNX are increasingly relying on top down requirements analysis (TDRA) to define and assess design approaches for workload and manpower reduction, and for ensuring required levels of human performance, reliability, safety, and quality of life at sea. The human systems integration (HSI) approach to TDRA begins with a function analysis which identifies the functions derived from the requirements in the Operational Requirements Document (ORD). The function analysis serves as the function baseline for the ship, and also supports the definition of RDT&E and Total Ownership Cost requirements. A mission analysis is then conducted to identify mission scenarios, again based on requirements in the ORD, and the Design Reference Mission (DRM). This is followed by a mission/function analysis which establishes the function requirements to successfully perform the ship's missions. Function requirements of major importance for HSI are information, performance, decision, and support requirements associated with each function. An allocation of functions defines the roles of humans and automation in performing the functions associated with a mission. Alternate design concepts, based on function allocation strategies, are then described, and task networks associated with the concepts are developed. Task network simulations are conducted to assess workloads and human performance capabilities associated with alternate concepts. An assessment of the affordability and risk associated with alternate concepts is performed, and manning estimates are developed for feasible design concepts.

Effects of computer-based training on procedural modifications to standard functional analyses.

PubMed

Schnell, Lauren K; Sidener, Tina M; DeBar, Ruth M; Vladescu, Jason C; Kahng, SungWoo

2018-01-01

Few studies have evaluated methods for training decision-making when functional analysis data are undifferentiated. The current study evaluated computer-based training to teach 20 graduate students to arrange functional analysis conditions, analyze functional analysis data, and implement procedural modifications. Participants were exposed to training materials using interactive software during a 1-day session. Following the training, mean scores on the posttest, novel cases probe, and maintenance probe increased for all participants. These results replicate previous findings during a 1-day session and include a measure of participant acceptability of the training. Recommendations for future research on computer-based training and functional analysis are discussed. © 2017 Society for the Experimental Analysis of Behavior.

Functional Analyses and Treatment of Precursor Behavior

PubMed Central

Najdowski, Adel C; Wallace, Michele D; Ellsworth, Carrie L; MacAleese, Alicia N; Cleveland, Jackie M

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe problem behavior (precursor behavior) and evaluated treatments based on the outcomes of the functional analyses of precursor behavior. Responding for all participants was differentiated during the functional analyses, and individualized treatments eliminated precursor behavior. These results suggest that functional analysis of precursor behavior may offer an alternative, indirect method to assess the operant function of severe problem behavior. PMID:18468282

Trial-Based Functional Analysis and Functional Communication Training in an Early Childhood Setting

ERIC Educational Resources Information Center

Lambert, Joseph M.; Bloom, Sarah E.; Irvin, Jennifer

2012-01-01

Problem behavior is common in early childhood special education classrooms. Functional communication training (FCT; Carr & Durand, 1985) may reduce problem behavior but requires identification of its function. The trial-based functional analysis (FA) is a method that can be used to identify problem behavior function in schools. We conducted…

GOMA: functional enrichment analysis tool based on GO modules

PubMed Central

Huang, Qiang; Wu, Ling-Yun; Wang, Yong; Zhang, Xiang-Sun

2013-01-01

Analyzing the function of gene sets is a critical step in interpreting the results of high-throughput experiments in systems biology. A variety of enrichment analysis tools have been developed in recent years, but most output a long list of significantly enriched terms that are often redundant, making it difficult to extract the most meaningful functions. In this paper, we present GOMA, a novel enrichment analysis method based on the new concept of enriched functional Gene Ontology (GO) modules. With this method, we systematically revealed functional GO modules, i.e., groups of functionally similar GO terms, via an optimization model and then ranked them by enrichment scores. Our new method simplifies enrichment analysis results by reducing redundancy, thereby preventing inconsistent enrichment results among functionally similar terms and providing more biologically meaningful results. PMID:23237213

Incorporating Descriptive Assessment Results into the Design of a Functional Analysis: A Case Example Involving a Preschooler's Hand Mouthing

ERIC Educational Resources Information Center

Tiger, Jeffrey H.; Hanley, Gregory P.; Bessette, Kimberly K.

2006-01-01

Functional analysis methodology has become the hallmark of behavioral assessment, yielding a determination of behavioral function in roughly 96% of the cases published (Hanley, Iwata, & McCord, 2003). Some authors have suggested that incorporating the results of a descriptive assessment into the design of a functional analysis may be useful in…

[A functional analysis of healthcare auditors' skills in Venezuela, 2008].

PubMed

Chirinos-Muñoz, Mónica S

2010-10-01

Using functional analysis for identifying the basic, working, specific and generic skills and values which a health service auditor must have. Implementing the functional analysis technique with 10 experts, identifying specific, basic, generic skills and values by means of deductive logic. A functional map was obtained which started by establishing a key purpose based on improving healthcare and service quality from which three key functions emerged. The main functions and skills' units were then broken down into the competitive elements defining what a health service auditor is able to do. This functional map (following functional analysis methodology) shows in detail the simple and complex tasks which a healthcare auditor should apply in the workplace, adopting a forward management approach for improving healthcare and health service quality. This methodology, expressing logical-deductive awareness raising, provides expert consensual information validating each element regarding overall skills.

The Americans with Disabilities Act: Using Job Analysis To Meet New Challenges.

ERIC Educational Resources Information Center

Lozada-Larsen, Susana R.

This paper focuses on the role that job analysis plays under the Americans with Disabilities Act (ADA). The most obvious use of job analysis data is in defining the essential functions of each job. The job analysis technique used should: list the functions of the job, define which functions are essential rather than marginal, and offer proof of…

[The structural functional analysis of functioning of day-hospitals of the Russian Federation].

PubMed

2012-01-01

The article deals with the results of structural functional analysis of functioning of day-hospitals in the Russian Federation. The dynamic analysis is presented concerning day-hospitals' network, capacity; financial support, beds stock structure, treated patients structure, volumes of diagnostic tests and curative procedures. The need in developing of population medical care in conditions of day-hospitals is demonstrated.

A Review of Functional Analysis Methods Conducted in Public School Classroom Settings

ERIC Educational Resources Information Center

Lloyd, Blair P.; Weaver, Emily S.; Staubitz, Johanna L.

2016-01-01

The use of functional behavior assessments (FBAs) to address problem behavior in classroom settings has increased as a result of education legislation and long-standing evidence supporting function-based interventions. Although functional analysis remains the standard for identifying behavior--environment functional relations, this component is…

Correspondence between Traditional Models of Functional Analysis and a Functional Analysis of Manding Behavior

ERIC Educational Resources Information Center

LaRue, Robert H.; Sloman, Kimberly N.; Weiss, Mary Jane; Delmolino, Lara; Hansford, Amy; Szalony, Jill; Madigan, Ryan; Lambright, Nathan M.

2011-01-01

Functional analysis procedures have been effectively used to determine the maintaining variables for challenging behavior and subsequently develop effective interventions. However, fear of evoking dangerous topographies of maladaptive behavior and concerns for reinforcing infrequent maladaptive behavior present challenges for people working in…

Functional Analysis and Treatment of Aggression Maintained by Preferred Conversational Topics

ERIC Educational Resources Information Center

Roscoe, Eileen M.; Kindle, Arianne E.; Pence, Sacha T.

2010-01-01

After an initial functional analysis of a participant's aggression showed unclear outcomes, we conducted preference and reinforcer assessments to identify preferred forms of attention that may maintain problem behavior. Next, we conducted an extended functional analysis that included a modified attention condition. Results showed that the…

Default-Mode Network Functional Connectivity in Aphasia: Therapy-Induced Neuroplasticity

ERIC Educational Resources Information Center

Marcotte, Karine; Perlbarg, Vincent; Marrelec, Guillaume; Benali, Habib; Ansaldo, Ana Ines

2013-01-01

Previous research on participants with aphasia has mainly been based on standard functional neuroimaging analysis. Recent studies have shown that functional connectivity analysis can detect compensatory activity, not revealed by standard analysis. Little is known, however, about the default-mode network in aphasia. In the current study, we studied…

Consumer Surplus, Demand Functions, and Policy Analysis,

DTIC Science & Technology

1983-06-01

ARD-AL758 865 CONSUMER SURPLUS DEMAND FUNCTIONS AND POLICY ANALYSIS 1/2 (U) RAND CORP SANTA MONICA CA F CANM JUN 83 RAND/R-3848-RC UNCLASSIFIED F/O 5...8217 - * 2, Consumer Surplus, Demand Functions, and Policy Analysis Frank Camm OCFILE COEYI b0 loo Thi! d Ci rr.i h,13 bea~n approvedS i i l ot p...ui.- r~aoz an~d sale; its (5 06 VP1 d’ *. . . * . ~ - V * * . R-3048-RC Consumer Surplus, Demand Functions, and Policy Analysis Frank Caomm June 1983

Clarifying Inconclusive Functional Analysis Results: Assessment and Treatment of Automatically Reinforced Aggression

PubMed Central

Saini, Valdeep; Greer, Brian D.; Fisher, Wayne W.

2016-01-01

We conducted a series of studies in which multiple strategies were used to clarify the inconclusive results of one boy’s functional analysis of aggression. Specifically, we (a) evaluated individual response topographies to determine the composition of aggregated response rates, (b) conducted a separate functional analysis of aggression after high rates of disruption masked the consequences maintaining aggression during the initial functional analysis, (c) modified the experimental design used during the functional analysis of aggression to improve discrimination and decrease interaction effects between conditions, and (d) evaluated a treatment matched to the reinforcer hypothesized to maintain aggression. An effective yet practical intervention for aggression was developed based on the results of these analyses and from data collected during the matched-treatment evaluation. PMID:25891269

Analyzing coastal environments by means of functional data analysis

NASA Astrophysics Data System (ADS)

Sierra, Carlos; Flor-Blanco, Germán; Ordoñez, Celestino; Flor, Germán; Gallego, José R.

2017-07-01

Here we used Functional Data Analysis (FDA) to examine particle-size distributions (PSDs) in a beach/shallow marine sedimentary environment in Gijón Bay (NW Spain). The work involved both Functional Principal Components Analysis (FPCA) and Functional Cluster Analysis (FCA). The grainsize of the sand samples was characterized by means of laser dispersion spectroscopy. Within this framework, FPCA was used as a dimension reduction technique to explore and uncover patterns in grain-size frequency curves. This procedure proved useful to describe variability in the structure of the data set. Moreover, an alternative approach, FCA, was applied to identify clusters and to interpret their spatial distribution. Results obtained with this latter technique were compared with those obtained by means of two vector approaches that combine PCA with CA (Cluster Analysis). The first method, the point density function (PDF), was employed after adapting a log-normal distribution to each PSD and resuming each of the density functions by its mean, sorting, skewness and kurtosis. The second applied a centered-log-ratio (clr) to the original data. PCA was then applied to the transformed data, and finally CA to the retained principal component scores. The study revealed functional data analysis, specifically FPCA and FCA, as a suitable alternative with considerable advantages over traditional vector analysis techniques in sedimentary geology studies.

A Comparison of Experimental Functional Analysis and the Questions about Behavioral Function (QABF) in the Assessment of Challenging Behavior of Individuals with Autism

ERIC Educational Resources Information Center

Healy, Olive; Brett, Denise; Leader, Geraldine

2013-01-01

We compared two functional behavioral assessment methods: the Questions About Behavioral Function (QABF; a standardized test) and experimental functional analysis (EFA) to identify behavioral functions of aggressive/destructive behavior, self-injurious behavior and stereotypy in 32 people diagnosed with autism. Both assessments found that self…

An Examination of the Effects of a Video-Based Training Package on Professional Staff's Implementation of a Brief Functional Analysis and Data Analysis

ERIC Educational Resources Information Center

Fleming, Courtney V.

2011-01-01

Minimal research has investigated training packages used to teach professional staff how to implement functional analysis procedures and to interpret data gathered during functional analysis. The current investigation used video-based training with role-play and feedback to teach six professionals in a clinical setting to implement procedures of a…

Classification of functional interactions from multi-electrodes data using conditional modularity analysis

NASA Astrophysics Data System (ADS)

Makhtar, Siti Noormiza; Senik, Mohd Harizal

2018-02-01

The availability of massive amount of neuronal signals are attracting widespread interest in functional connectivity analysis. Functional interactions estimated by multivariate partial coherence analysis in the frequency domain represent the connectivity strength in this study. Modularity is a network measure for the detection of community structure in network analysis. The discovery of community structure for the functional neuronal network was implemented on multi-electrode array (MEA) signals recorded from hippocampal regions in isoflurane-anaesthetized Lister-hooded rats. The analysis is expected to show modularity changes before and after local unilateral kainic acid (KA)-induced epileptiform activity. The result is presented using color-coded graphic of conditional modularity measure for 19 MEA nodes. This network is separated into four sub-regions to show the community detection within each sub-region. The results show that classification of neuronal signals into the inter- and intra-modular nodes is feasible using conditional modularity analysis. Estimation of segregation properties using conditional modularity analysis may provide further information about functional connectivity from MEA data.

Discrete-Trial Functional Analysis and Functional Communication Training with Three Individuals with Autism and Severe Problem Behavior

ERIC Educational Resources Information Center

Schmidt, Jonathan D.; Drasgow, Erik; Halle, James W.; Martin, Christian A.; Bliss, Sacha A.

2014-01-01

Discrete-trial functional analysis (DTFA) is an experimental method for determining the variables maintaining problem behavior in the context of natural routines. Functional communication training (FCT) is an effective method for replacing problem behavior, once identified, with a functionally equivalent response. We implemented these procedures…

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.

PubMed

Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J

2017-12-01

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.

Functional Generalized Structured Component Analysis.

PubMed

Suk, Hye Won; Hwang, Heungsun

2016-12-01

An extension of Generalized Structured Component Analysis (GSCA), called Functional GSCA, is proposed to analyze functional data that are considered to arise from an underlying smooth curve varying over time or other continua. GSCA has been geared for the analysis of multivariate data. Accordingly, it cannot deal with functional data that often involve different measurement occasions across participants and a large number of measurement occasions that exceed the number of participants. Functional GSCA addresses these issues by integrating GSCA with spline basis function expansions that represent infinite-dimensional curves onto a finite-dimensional space. For parameter estimation, functional GSCA minimizes a penalized least squares criterion by using an alternating penalized least squares estimation algorithm. The usefulness of functional GSCA is illustrated with gait data.

Evaluation of automated decisionmaking methodologies and development of an integrated robotic system simulation, volume 2, part 1. Appendix A: Software documentation

NASA Technical Reports Server (NTRS)

Lowrie, J. W.; Fermelia, A. J.; Haley, D. C.; Gremban, K. D.; Vanbaalen, J.; Walsh, R. W.

1982-01-01

Documentation of the preliminary software developed as a framework for a generalized integrated robotic system simulation is presented. The program structure is composed of three major functions controlled by a program executive. The three major functions are: system definition, analysis tools, and post processing. The system definition function handles user input of system parameters and definition of the manipulator configuration. The analysis tools function handles the computational requirements of the program. The post processing function allows for more detailed study of the results of analysis tool function executions. Also documented is the manipulator joint model software to be used as the basis of the manipulator simulation which will be part of the analysis tools capability.

A complementation assay for in vivo protein structure/function analysis in Physcomitrella patens (Funariaceae)

DOE PAGES

Scavuzzo-Duggan, Tess R.; Chaves, Arielle M.; Roberts, Alison W.

2015-07-14

Here, a method for rapid in vivo functional analysis of engineered proteins was developed using Physcomitrella patens. A complementation assay was designed for testing structure/function relationships in cellulose synthase (CESA) proteins. The components of the assay include (1) construction of test vectors that drive expression of epitope-tagged PpCESA5 carrying engineered mutations, (2) transformation of a ppcesa5 knockout line that fails to produce gametophores with test and control vectors, (3) scoring the stable transformants for gametophore production, (4) statistical analysis comparing complementation rates for test vectors to positive and negative control vectors, and (5) analysis of transgenic protein expression by Westernmore » blotting. The assay distinguished mutations that generate fully functional, nonfunctional, and partially functional proteins. In conclusion, compared with existing methods for in vivo testing of protein function, this complementation assay provides a rapid method for investigating protein structure/function relationships in plants.« less

Software ion scan functions in analysis of glycomic and lipidomic MS/MS datasets.

PubMed

Haramija, Marko

2018-03-01

Hardware ion scan functions unique to tandem mass spectrometry (MS/MS) mode of data acquisition, such as precursor ion scan (PIS) and neutral loss scan (NLS), are important for selective extraction of key structural data from complex MS/MS spectra. However, their software counterparts, software ion scan (SIS) functions, are still not regularly available. Software ion scan functions can be easily coded for additional functionalities, such as software multiple precursor ion scan, software no ion scan, and software variable ion scan functions. These are often necessary, since they allow more efficient analysis of complex MS/MS datasets, often encountered in glycomics and lipidomics. Software ion scan functions can be easily coded by using modern script languages and can be independent of instrument manufacturer. Here we demonstrate the utility of SIS functions on a medium-size glycomic MS/MS dataset. Knowledge of sample properties, as well as of diagnostic and conditional diagnostic ions crucial for data analysis, was needed. Based on the tables constructed with the output data from the SIS functions performed, a detailed analysis of a complex MS/MS glycomic dataset could be carried out in a quick, accurate, and efficient manner. Glycomic research is progressing slowly, and with respect to the MS experiments, one of the key obstacles for moving forward is the lack of appropriate bioinformatic tools necessary for fast analysis of glycomic MS/MS datasets. Adding novel SIS functionalities to the glycomic MS/MS toolbox has a potential to significantly speed up the glycomic data analysis process. Similar tools are useful for analysis of lipidomic MS/MS datasets as well, as will be discussed briefly. Copyright © 2017 John Wiley & Sons, Ltd.

Functional Connectivity Parcellation of the Human Thalamus by Independent Component Analysis.

PubMed

Zhang, Sheng; Li, Chiang-Shan R

2017-11-01

As a key structure to relay and integrate information, the thalamus supports multiple cognitive and affective functions through the connectivity between its subnuclei and cortical and subcortical regions. Although extant studies have largely described thalamic regional functions in anatomical terms, evidence accumulates to suggest a more complex picture of subareal activities and connectivities of the thalamus. In this study, we aimed to parcellate the thalamus and examine whole-brain connectivity of its functional clusters. With resting state functional magnetic resonance imaging data from 96 adults, we used independent component analysis (ICA) to parcellate the thalamus into 10 components. On the basis of the independence assumption, ICA helps to identify how subclusters overlap spatially. Whole brain functional connectivity of each subdivision was computed for independent component's time course (ICtc), which is a unique time series to represent an IC. For comparison, we computed seed-region-based functional connectivity using the averaged time course across all voxels within a thalamic subdivision. The results showed that, at p < 10 -6 , corrected, 49% of voxels on average overlapped among subdivisions. Compared with seed-region analysis, ICtc analysis revealed patterns of connectivity that were more distinguished between thalamic clusters. ICtc analysis demonstrated thalamic connectivity to the primary motor cortex, which has eluded the analysis as well as previous studies based on averaged time series, and clarified thalamic connectivity to the hippocampus, caudate nucleus, and precuneus. The new findings elucidate functional organization of the thalamus and suggest that ICA clustering in combination with ICtc rather than seed-region analysis better distinguishes whole-brain connectivities among functional clusters of a brain region.

How Do Executive Functions Fit with the Cattell-Horn-Carroll Model? Some Evidence from a Joint Factor Analysis of the Delis-Kaplan Executive Function System and the Woodcock-Johnson III Tests of Cognitive Abilities

ERIC Educational Resources Information Center

Floyd, Randy G.; Bergeron, Renee; Hamilton, Gloria; Parra, Gilbert R.

2010-01-01

This study investigated the relations among executive functions and cognitive abilities through a joint exploratory factor analysis and joint confirmatory factor analysis of 25 test scores from the Delis-Kaplan Executive Function System and the Woodcock-Johnson III Tests of Cognitive Abilities. Participants were 100 children and adolescents…

Psychometric Properties on Lecturers' Beliefs on Teaching Function: Rasch Model Analysis

ERIC Educational Resources Information Center

Mofreh, Samah Ali Mohsen; Ghafar, Mohammed Najib Abdul; Omar, Abdul Hafiz Hj; Mosaku, Monsurat; Ma'ruf, Amar

2014-01-01

This paper focuses on the psychometric analysis of lecturers' beliefs on teaching function (LBTF) survey using Rasch Model analysis. The sample comprised 34 Community Colleges' lecturers. The Rasch Model is applied to produce specific measurements on the lecturers' beliefs on teaching function in order to generalize results and inferential…

A Comparison of Functional Behavioral Assessment and Functional Analysis Methodology among Students with Mild Disabilities

ERIC Educational Resources Information Center

Lewis, Timothy J.; Mitchell, Barbara S.; Harvey, Kristin; Green, Ambra; McKenzie, Jennifer

2015-01-01

Functional behavioral assessment (FBA) and functional analyses (FA) are grounded in the applied behavior analysis principle that posits problem behavior is functionally related to the environment in which it occurs and is maintained by either providing access to reinforcing outcomes or allowing the individual to avoid or escape that which they…

Applying Cognitive Work Analysis to Time Critical Targeting Functionality

DTIC Science & Technology

2004-10-01

Cognitive Task Analysis , CTA, Cognitive Task Analysis , Human Factors, GUI, Graphical User Interface, Heuristic Evaluation... Cognitive Task Analysis MITRE Briefing January 2000 Dynamic Battle Management Functional Architecture 3-1 Section 3 Human Factors...clear distinction between Cognitive Work Analysis (CWA) and Cognitive Task Analysis (CTA), therefore this document will refer to these

Functional principal component analysis of glomerular filtration rate curves after kidney transplant.

PubMed

Dong, Jianghu J; Wang, Liangliang; Gill, Jagbir; Cao, Jiguo

2017-01-01

This article is motivated by some longitudinal clinical data of kidney transplant recipients, where kidney function progression is recorded as the estimated glomerular filtration rates at multiple time points post kidney transplantation. We propose to use the functional principal component analysis method to explore the major source of variations of glomerular filtration rate curves. We find that the estimated functional principal component scores can be used to cluster glomerular filtration rate curves. Ordering functional principal component scores can detect abnormal glomerular filtration rate curves. Finally, functional principal component analysis can effectively estimate missing glomerular filtration rate values and predict future glomerular filtration rate values.

Extrapolation of Functions of Many Variables by Means of Metric Analysis

NASA Astrophysics Data System (ADS)

Kryanev, Alexandr; Ivanov, Victor; Romanova, Anastasiya; Sevastianov, Leonid; Udumyan, David

2018-02-01

The paper considers a problem of extrapolating functions of several variables. It is assumed that the values of the function of m variables at a finite number of points in some domain D of the m-dimensional space are given. It is required to restore the value of the function at points outside the domain D. The paper proposes a fundamentally new method for functions of several variables extrapolation. In the presented paper, the method of extrapolating a function of many variables developed by us uses the interpolation scheme of metric analysis. To solve the extrapolation problem, a scheme based on metric analysis methods is proposed. This scheme consists of two stages. In the first stage, using the metric analysis, the function is interpolated to the points of the domain D belonging to the segment of the straight line connecting the center of the domain D with the point M, in which it is necessary to restore the value of the function. In the second stage, based on the auto regression model and metric analysis, the function values are predicted along the above straight-line segment beyond the domain D up to the point M. The presented numerical example demonstrates the efficiency of the method under consideration.

Functional Analyses and Treatment of Precursor Behavior

ERIC Educational Resources Information Center

Najdowski, Adel C.; Wallace, Michele D.; Ellsworth, Carrie L.; MacAleese, Alicia N.; Cleveland, Jackie

2008-01-01

Functional analysis has been demonstrated to be an effective method to identify environmental variables that maintain problem behavior. However, there are cases when conducting functional analyses of severe problem behavior may be contraindicated. The current study applied functional analysis procedures to a class of behavior that preceded severe…

The Potential of "Function" as an Archival Descriptor

ERIC Educational Resources Information Center

Chaudron, Gerald

2008-01-01

Functional analysis has been incorporated widely into appraisal methods for decades. These methods, from documentation strategy to macroappraisal, are discussed, and the usefulness and limitations of functional analysis in appraisal are examined. Yet, while archival thinkers have focused on function in appraisal, little has been written on…

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Functional reconstitution of Drosophila melanogaster NMJ glutamate receptors

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

Han, Tae Hee; Dharkar, Poorva; Mayer, Mark L.

The Drosophila larval neuromuscular junction (NMJ), at which glutamate acts as the excitatory neurotransmitter, is a widely used model for genetic analysis of synapse function and development. Despite decades of study, the inability to reconstitute NMJ glutamate receptor function using heterologous expression systems has complicated the analysis of receptor function, such that it is difficult to resolve the molecular basis for compound phenotypes observed in mutant flies. In this paper, we find that Drosophila Neto functions as an essential component required for the function of NMJ glutamate receptors, permitting analysis of glutamate receptor responses in Xenopus oocytes. Finally, in combinationmore » with a crystallographic analysis of the GluRIIB ligand binding domain, we use this system to characterize the subunit dependence of assembly, channel block, and ligand selectivity for Drosophila NMJ glutamate receptors.« less

Functional reconstitution of Drosophila melanogaster NMJ glutamate receptors

DOE PAGES

Han, Tae Hee; Dharkar, Poorva; Mayer, Mark L.; ...

2015-04-27

The Drosophila larval neuromuscular junction (NMJ), at which glutamate acts as the excitatory neurotransmitter, is a widely used model for genetic analysis of synapse function and development. Despite decades of study, the inability to reconstitute NMJ glutamate receptor function using heterologous expression systems has complicated the analysis of receptor function, such that it is difficult to resolve the molecular basis for compound phenotypes observed in mutant flies. In this paper, we find that Drosophila Neto functions as an essential component required for the function of NMJ glutamate receptors, permitting analysis of glutamate receptor responses in Xenopus oocytes. Finally, in combinationmore » with a crystallographic analysis of the GluRIIB ligand binding domain, we use this system to characterize the subunit dependence of assembly, channel block, and ligand selectivity for Drosophila NMJ glutamate receptors.« less

Plant functional genomics

NASA Astrophysics Data System (ADS)

Holtorf, Hauke; Guitton, Marie-Christine; Reski, Ralf

2002-04-01

Functional genome analysis of plants has entered the high-throughput stage. The complete genome information from key species such as Arabidopsis thaliana and rice is now available and will further boost the application of a range of new technologies to functional plant gene analysis. To broadly assign functions to unknown genes, different fast and multiparallel approaches are currently used and developed. These new technologies are based on known methods but are adapted and improved to accommodate for comprehensive, large-scale gene analysis, i.e. such techniques are novel in the sense that their design allows researchers to analyse many genes at the same time and at an unprecedented pace. Such methods allow analysis of the different constituents of the cell that help to deduce gene function, namely the transcripts, proteins and metabolites. Similarly the phenotypic variations of entire mutant collections can now be analysed in a much faster and more efficient way than before. The different methodologies have developed to form their own fields within the functional genomics technological platform and are termed transcriptomics, proteomics, metabolomics and phenomics. Gene function, however, cannot solely be inferred by using only one such approach. Rather, it is only by bringing together all the information collected by different functional genomic tools that one will be able to unequivocally assign functions to unknown plant genes. This review focuses on current technical developments and their impact on the field of plant functional genomics. The lower plant Physcomitrella is introduced as a new model system for gene function analysis, owing to its high rate of homologous recombination.

Trial-Based Functional Analysis Informs Treatment for Vocal Scripting.

PubMed

Rispoli, Mandy; Brodhead, Matthew; Wolfe, Katie; Gregori, Emily

2018-05-01

Research on trial-based functional analysis has primarily focused on socially maintained challenging behaviors. However, procedural modifications may be necessary to clarify ambiguous assessment results. The purposes of this study were to evaluate the utility of iterative modifications to trial-based functional analysis on the identification of putative reinforcement and subsequent treatment for vocal scripting. For all participants, modifications to the trial-based functional analysis identified a primary function of automatic reinforcement. The structure of the trial-based format led to identification of social attention as an abolishing operation for vocal scripting. A noncontingent attention treatment was evaluated using withdrawal designs for each participant. This noncontingent attention treatment resulted in near zero levels of vocal scripting for all participants. Implications for research and practice are presented.

Escape-to-Attention as a Potential Variable for Maintaining Problem Behavior in the School Setting

ERIC Educational Resources Information Center

Sarno, Jana M.; Sterling, Heather E.; Mueller, Michael M.; Dufrene, Brad; Tingstrom, Daniel H.; Olmi, D. Joe

2011-01-01

Mueller, Sterling-Turner, and Moore (2005) reported a novel escape-to-attention (ETA) functional analysis condition in a school setting with one child. The current study replicates Mueller et al.'s functional analysis procedures with three elementary school-age boys referred for problem behavior. Functional analysis verified the participant's…

Brief Functional Analysis and Intervention Evaluation for Treatment of Saliva-Play

ERIC Educational Resources Information Center

Luiselli, James K.; Ricciardi, Joseph N.; Schmidt, Sarah; Tarr, Melissa

2004-01-01

We conducted a brief (8 days) functional analysis to identify sources of control over persistent saliva-play displayed by a 6-year old child with autism in a school setting. The functional analysis suggested that saliva-play was maintained by automatic reinforcement, leading to an intervention evaluation (3 days) that compared two methods of…

A Factor Analysis of Peking Opera: Its Functions in Mass Communications.

ERIC Educational Resources Information Center

Cheng, Philip H.

The study reported in this paper examined the structure and function of Chinese opera (also known as Peking opera) as an effective communication medium of social control and change in China, a land populated by 800 million people and nourished by a 5,000-year-old civilization. The study followed structural-functional analysis, content analysis,…

Progressing from Identification and Functional Analysis of Precursor Behavior to Treatment of Self-Injurious Behavior

ERIC Educational Resources Information Center

Dracobly, Joseph D.; Smith, Richard G.

2012-01-01

This multiple-study experiment evaluated the utility of assessing and treating severe self-injurious behavior (SIB) based on the outcomes of a functional analysis of precursor behavior. In Study 1, a precursor to SIB was identified using descriptive assessment and conditional probability analyses. In Study 2, a functional analysis of precursor…

Functional Analysis and Reduction of Inappropriate Spitting

ERIC Educational Resources Information Center

Carter, Stacy L.; Wheeler, John J.

2007-01-01

Functional analysis was used to determine the possible function of inappropriate spitting behavior of an adult woman who had been diagnosed with profound mental retardation. Results of an initial descriptive assessment indicated a possible attention function and led to an attention-based intervention, which was deemed ineffective at reducing the…

Classwide Functional Analysis and Treatment of Preschoolers' Disruptive Behavior

ERIC Educational Resources Information Center

Poole, Veena Y.; Dufrene, Brad A.; Sterling, Heather E.; Tingstrom, Daniel H.; Hardy, Christina M.

2012-01-01

Relatively few functional assessment and intervention studies have been conducted in preschool classrooms with children of typical development who engage in high incidence problem behaviors. Moreover, limited studies have used functional assessment procedures with the class as the unit of analysis. This study included functional analyses and a…

The Effects of Functional Communication Training on the Appropriate Behavior of a Student with Emotional and Behavioral Disorders

ERIC Educational Resources Information Center

Jolivette, Kristine; Stichter, Janine P.; Houchins, David E.; Kennedy, Christina

2007-01-01

Functional analysis is used to generate and test hypotheses, specific to an individual's appropriate and inappropriate behaviors, by directly manipulating antecedent and consequent events within natural or analog environments. In the case that a function(s) was not determined or the behavior has multiple motivations during the functional analysis,…

The Use of Trial-Based Functional Analysis in Public School Classrooms for Two Students with Developmental Disabilities

ERIC Educational Resources Information Center

Rispoli, Mandy J.; Davis, Heather S.; Goodwyn, Fara D.; Camargo, Siglia

2013-01-01

Analogue functional analyses are a well-researched means of determining behavioral function in research and clinical contexts. However, conducting analogue functional analyses in school settings can be problematic and may lead to inconclusive results. The purpose of this study was to compare the results of a trial-based functional analysis with…

Echocardiographic Evaluation of Left Atrial Mechanics: Function, History, Novel Techniques, Advantages, and Pitfalls.

PubMed

Leischik, Roman; Littwitz, Henning; Dworrak, Birgit; Garg, Pankaj; Zhu, Meihua; Sahn, David J; Horlitz, Marc

2015-01-01

Left atrial (LA) functional analysis has an established role in assessing left ventricular diastolic function. The current standard echocardiographic parameters used to study left ventricular diastolic function include pulsed-wave Doppler mitral inflow analysis, tissue Doppler imaging measurements, and LA dimension estimation. However, the above-mentioned parameters do not directly quantify LA performance. Deformation studies using strain and strain-rate imaging to assess LA function were validated in previous research, but this technique is not currently used in routine clinical practice. This review discusses the history, importance, and pitfalls of strain technology for the analysis of LA mechanics.

Aircraft/Air Traffic Management Functional Analysis Model. Version 2.0; User's Guide

NASA Technical Reports Server (NTRS)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) a National Aeronautics and Space Administration (NASA) contract. This document provides a guide for using the model in analysis. Those interested in making enhancements or modification to the model should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Technical Description.

Relative contributions of three descriptive methods: implications for behavioral assessment.

PubMed

Pence, Sacha T; Roscoe, Eileen M; Bourret, Jason C; Ahearn, William H

2009-01-01

This study compared the outcomes of three descriptive analysis methods-the ABC method, the conditional probability method, and the conditional and background probability method-to each other and to the results obtained from functional analyses. Six individuals who had been diagnosed with developmental delays and exhibited problem behavior participated. Functional analyses indicated that participants' problem behavior was maintained by social positive reinforcement (n = 2), social negative reinforcement (n = 2), or automatic reinforcement (n = 2). Results showed that for all but 1 participant, descriptive analysis outcomes were similar across methods. In addition, for all but 1 participant, the descriptive analysis outcome differed substantially from the functional analysis outcome. This supports the general finding that descriptive analysis is a poor means of determining functional relations.

On Special Functions in the Context of Clifford Analysis

NASA Astrophysics Data System (ADS)

Malonek, H. R.; Falcão, M. I.

2010-09-01

Considering the foundation of Quaternionic Analysis by R. Fueter and his collaborators in the beginning of the 1930s as starting point of Clifford Analysis, we can look back to 80 years of work in this field. However the interest in multivariate analysis using Clifford algebras only started to grow significantly in the 70s. Since then a great amount of papers on Clifford Analysis referring different classes of Special Functions have appeared. This situation may have been triggered by a more systematic treatment of monogenic functions by their multiple series development derived from Gegenbauer or associated Legendre polynomials (and not only by their integral representation). Also approaches to Special Functions by means of algebraic methods, either Lie algebras or through Lie groups and symmetric spaces gained by that time importance and influenced their treatment in Clifford Analysis. In our talk we will rely on the generalization of the classical approach to Special Functions through differential equations with respect to the hypercomplex derivative, which is a more recently developed tool in Clifford Analysis. In this context special attention will be payed to the role of Special Functions as intermediator between continuous and discrete mathematics. This corresponds to a more recent trend in combinatorics, since it has been revealed that many algebraic structures have hidden combinatorial underpinnings.

FGWAS: Functional genome wide association analysis.

PubMed

Huang, Chao; Thompson, Paul; Wang, Yalin; Yu, Yang; Zhang, Jingwen; Kong, Dehan; Colen, Rivka R; Knickmeyer, Rebecca C; Zhu, Hongtu

2017-10-01

Functional phenotypes (e.g., subcortical surface representation), which commonly arise in imaging genetic studies, have been used to detect putative genes for complexly inherited neuropsychiatric and neurodegenerative disorders. However, existing statistical methods largely ignore the functional features (e.g., functional smoothness and correlation). The aim of this paper is to develop a functional genome-wide association analysis (FGWAS) framework to efficiently carry out whole-genome analyses of functional phenotypes. FGWAS consists of three components: a multivariate varying coefficient model, a global sure independence screening procedure, and a test procedure. Compared with the standard multivariate regression model, the multivariate varying coefficient model explicitly models the functional features of functional phenotypes through the integration of smooth coefficient functions and functional principal component analysis. Statistically, compared with existing methods for genome-wide association studies (GWAS), FGWAS can substantially boost the detection power for discovering important genetic variants influencing brain structure and function. Simulation studies show that FGWAS outperforms existing GWAS methods for searching sparse signals in an extremely large search space, while controlling for the family-wise error rate. We have successfully applied FGWAS to large-scale analysis of data from the Alzheimer's Disease Neuroimaging Initiative for 708 subjects, 30,000 vertices on the left and right hippocampal surfaces, and 501,584 SNPs. Copyright © 2017 Elsevier Inc. All rights reserved.

A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet.

PubMed

Brown, A M

2001-06-01

The objective of this present study was to introduce a simple, easily understood method for carrying out non-linear regression analysis based on user input functions. While it is relatively straightforward to fit data with simple functions such as linear or logarithmic functions, fitting data with more complicated non-linear functions is more difficult. Commercial specialist programmes are available that will carry out this analysis, but these programmes are expensive and are not intuitive to learn. An alternative method described here is to use the SOLVER function of the ubiquitous spreadsheet programme Microsoft Excel, which employs an iterative least squares fitting routine to produce the optimal goodness of fit between data and function. The intent of this paper is to lead the reader through an easily understood step-by-step guide to implementing this method, which can be applied to any function in the form y=f(x), and is well suited to fast, reliable analysis of data in all fields of biology.

Computational Methods to Work as First-Pass Filter in Deleterious SNP Analysis of Alkaptonuria

PubMed Central

Magesh, R.; George Priya Doss, C.

2012-01-01

A major challenge in the analysis of human genetic variation is to distinguish functional from nonfunctional SNPs. Discovering these functional SNPs is one of the main goals of modern genetics and genomics studies. There is a need to effectively and efficiently identify functionally important nsSNPs which may be deleterious or disease causing and to identify their molecular effects. The prediction of phenotype of nsSNPs by computational analysis may provide a good way to explore the function of nsSNPs and its relationship with susceptibility to disease. In this context, we surveyed and compared variation databases along with in silico prediction programs to assess the effects of deleterious functional variants on protein functions. In other respects, we attempted these methods to work as first-pass filter to identify the deleterious substitutions worth pursuing for further experimental research. In this analysis, we used the existing computational methods to explore the mutation-structure-function relationship in HGD gene causing alkaptonuria. PMID:22606059

Electrochemical reactions in fluoride-ion batteries: mechanistic insights from pair distribution function analysis

DOE PAGES

Grenier, Antonin; Porras-Gutierrez, Ana-Gabriela; Groult, Henri; ...

2017-07-05

Detailed analysis of electrochemical reactions occurring in rechargeable Fluoride-Ion Batteries (FIBs) is provided by means of synchrotron X-ray diffraction (XRD) and Pair Distribution Function (PDF) analysis.

Trade-Off Analysis between Concerns Based on Aspect-Oriented Requirements Engineering

NASA Astrophysics Data System (ADS)

Laurito, Abelyn Methanie R.; Takada, Shingo

The identification of functional and non-functional concerns is an important activity during requirements analysis. However, there may be conflicts between the identified concerns, and they must be discovered and resolved through trade-off analysis. Aspect-Oriented Requirements Engineering (AORE) has trade-off analysis as one of its goals, but most AORE approaches do not actually offer support for trade-off analysis; they focus on describing concerns and generating their composition. This paper proposes an approach for trade-off analysis based on AORE using use cases and the Requirements Conflict Matrix (RCM) to represent compositions. RCM shows the positive or negative effect of non-functional concerns over use cases and other non-functional concerns. Our approach is implemented within a tool called E-UCEd (Extended Use Case Editor). We also show the results of evaluating our tool.

An Extended Functional Analysis Protocol Assesses the Role of Stereotypy in Aggression in Two Young Children with Autism Spectrum Disorder

ERIC Educational Resources Information Center

White, Pamela; O'Reilly, Mark; Fragale, Christina; Kang, Soyeon; Muhich, Kimberly; Falcomata, Terry; Lang, Russell; Sigafoos, Jeff; Lancioni, Giulio

2011-01-01

Two children with autism who engaged in aggression and stereotypy were assessed using common analogue functional analysis procedures. Aggression was maintained by access to specific preferred items. Data on the rates of stereotypy and appropriate play were collected during an extended functional analysis tangible condition. These data reveal that…

Functional analysis and treatment of elopement for a child with attention deficit hyperactivity disorder.

PubMed

Kodak, Tiffany; Grow, Laura; Northup, John

2004-01-01

We conducted a functional analysis of elopement in an outdoor setting for a child with a diagnosis of attention deficit hyperactivity disorder. A subsequent treatment consisting of noncontingent attention and time-out was demonstrated to be effective in eliminating elopement. Modifications of functional analysis procedures associated with the occurrence of elopement in a natural setting are demonstrated.

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

Association Between Blood Glucose and Functional Outcome in Intracerebral Hemorrhage: A Systematic Review and Meta-Analysis.

PubMed

Zheng, Jun; Yu, Zhiyuan; Ma, Lu; Guo, Rui; Lin, Sen; You, Chao; Li, Hao

2018-03-16

Intracerebral hemorrhage (ICH) is a devastating subtype of stroke. Patients with ICH have poor functional outcomes. The association between blood glucose level and functional outcome in ICH remains unclear. This systematic review and meta-analysis aimed to investigate the association between blood glucose level and functional outcomes in patients with ICH. Literature was searched systemically in PubMed, EMBASE, Web of Science, and Cochrane Library. Published cohort studies evaluating the association between blood glucose and functional outcome in patients with ICH were included. This meta-analysis was performed using odds ratios (ORs) and 95% confidence intervals (CIs). A total of 16 studies were included in our meta-analysis. Our data show that hyperglycemia defined by cutoff values was significantly associated with unfavorable functional outcome (OR, 1.80; 95% CI, 1.36-2.39; P < 0.001). Our analysis also suggested a significant association between increased blood glucose levels and functional outcomes (OR, 1.05; 95% CI, 1.03-1.07; P < 0.001). High blood glucose level is significantly associated with poor functional outcome in ICH. Further studies with larger sample sizes, more time points, and longer follow-up times are necessary to confirm this association. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional Analysis in Public Schools: A Summary of 90 Functional Analyses

ERIC Educational Resources Information Center

Mueller, Michael M.; Nkosi, Ajamu; Hine, Jeffrey F.

2011-01-01

Several review and epidemiological studies have been conducted over recent years to inform behavior analysts of functional analysis outcomes. None to date have closely examined demographic and clinical data for functional analyses conducted exclusively in public school settings. The current paper presents a data-based summary of 90 functional…

Use of Analog Functional Analysis in Assessing the Function of Mealtime Behavior Problems.

ERIC Educational Resources Information Center

Girolami, Peter A.; Scotti, Joseph R.

2001-01-01

This study applied the methodology of an analog experimental (functional) analysis of behavior to the specific interaction between parents and three children with mental retardation exhibiting food refusal and related mealtime problems. Analog results were highly consistent with other forms of functional assessment data, including interviews,…

Effect of exercise on cognitive function in chronic disease patients: a meta-analysis and systematic review of randomized controlled trials.

PubMed

Cai, Hong; Li, Guichen; Hua, Shanshan; Liu, Yufei; Chen, Li

2017-01-01

The purpose of this study was to conduct a meta-analysis and systematic review to assess the effect of exercise on cognitive function in people with chronic diseases. PubMed, Web of Science, Embase, the Cochrane Library, CINAHL, PsycINFO, and three Chinese databases were electronically searched for papers that were published until September 2016. This meta-analysis and systematic review included randomized controlled trials that evaluated the effect of exercise on cognitive function compared with control group for people with chronic diseases. Totally, 35 studies met the inclusion criteria, with 3,113 participants. The main analysis revealed a positive overall random effect of exercise intervention on cognitive function in patients with chronic diseases. The secondary analysis revealed that aerobic exercise interventions and aerobic included exercise interventions had a positive effect on cognition in patients with chronic diseases. The intervention offering low frequency had a positive effect on cognitive function in patients with chronic diseases. Finally, we found that interventions offered at both low exercise intensity and moderate exercise intensity had a positive effect on cognitive function in patients with chronic diseases. The secondary analysis also revealed that exercise interventions were beneficial in Alzheimer's disease patients when grouped by disease type. This meta-analysis and systematic review suggests that exercise interventions positively influence cognitive function in patients with chronic diseases. Beneficial effect was independent of the type of disease, type of exercise, frequency, and the intensity of the exercise intervention.

Quantile Functions, Convergence in Quantile, and Extreme Value Distribution Theory.

DTIC Science & Technology

1980-11-01

Gnanadesikan (1968). Quantile functions are advocated by Parzen (1979) as providing an approach to probability-based data analysis. Quantile functions are... Gnanadesikan , R. (1968). Probability Plotting Methods for the Analysis of Data, Biomtrika, 55, 1-17.

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

DOE PAGES

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

2017-10-13

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

The Information Content of Discrete Functions and Their Application in Genetic Data Analysis

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

Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.

The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less

Short-term forecasting of meteorological time series using Nonparametric Functional Data Analysis (NPFDA)

NASA Astrophysics Data System (ADS)

Curceac, S.; Ternynck, C.; Ouarda, T.

2015-12-01

Over the past decades, a substantial amount of research has been conducted to model and forecast climatic variables. In this study, Nonparametric Functional Data Analysis (NPFDA) methods are applied to forecast air temperature and wind speed time series in Abu Dhabi, UAE. The dataset consists of hourly measurements recorded for a period of 29 years, 1982-2010. The novelty of the Functional Data Analysis approach is in expressing the data as curves. In the present work, the focus is on daily forecasting and the functional observations (curves) express the daily measurements of the above mentioned variables. We apply a non-linear regression model with a functional non-parametric kernel estimator. The computation of the estimator is performed using an asymmetrical quadratic kernel function for local weighting based on the bandwidth obtained by a cross validation procedure. The proximities between functional objects are calculated by families of semi-metrics based on derivatives and Functional Principal Component Analysis (FPCA). Additionally, functional conditional mode and functional conditional median estimators are applied and the advantages of combining their results are analysed. A different approach employs a SARIMA model selected according to the minimum Akaike (AIC) and Bayessian (BIC) Information Criteria and based on the residuals of the model. The performance of the models is assessed by calculating error indices such as the root mean square error (RMSE), relative RMSE, BIAS and relative BIAS. The results indicate that the NPFDA models provide more accurate forecasts than the SARIMA models. Key words: Nonparametric functional data analysis, SARIMA, time series forecast, air temperature, wind speed

Functional analysis and treatment of elopement for a child with attention deficit hyperactivity disorder.

PubMed Central

Kodak, Tiffany; Grow, Laura; Northup, John

2004-01-01

We conducted a functional analysis of elopement in an outdoor setting for a child with a diagnosis of attention deficit hyperactivity disorder. A subsequent treatment consisting of noncontingent attention and time-out was demonstrated to be effective in eliminating elopement. Modifications of functional analysis procedures associated with the occurrence of elopement in a natural setting are demonstrated. PMID:15293643

RELATIVE CONTRIBUTIONS OF THREE DESCRIPTIVE METHODS: IMPLICATIONS FOR BEHAVIORAL ASSESSMENT

PubMed Central

Pence, Sacha T; Roscoe, Eileen M; Bourret, Jason C; Ahearn, William H

2009-01-01

This study compared the outcomes of three descriptive analysis methods—the ABC method, the conditional probability method, and the conditional and background probability method—to each other and to the results obtained from functional analyses. Six individuals who had been diagnosed with developmental delays and exhibited problem behavior participated. Functional analyses indicated that participants' problem behavior was maintained by social positive reinforcement (n  =  2), social negative reinforcement (n  =  2), or automatic reinforcement (n  =  2). Results showed that for all but 1 participant, descriptive analysis outcomes were similar across methods. In addition, for all but 1 participant, the descriptive analysis outcome differed substantially from the functional analysis outcome. This supports the general finding that descriptive analysis is a poor means of determining functional relations. PMID:19949536

Function modeling: improved raster analysis through delayed reading and function raster datasets

Treesearch

John S. Hogland; Nathaniel M. Anderson; J .Greg Jones

2013-01-01

Raster modeling is an integral component of spatial analysis. However, conventional raster modeling techniques can require a substantial amount of processing time and storage space, often limiting the types of analyses that can be performed. To address this issue, we have developed Function Modeling. Function Modeling is a new modeling framework that streamlines the...

Regional Morphology Analysis Package (RMAP): Empirical Orthogonal Function Analysis, Background and Examples

DTIC Science & Technology

2007-10-01

1984. Complex principal component analysis : Theory and examples. Journal of Climate and Applied Meteorology 23: 1660-1673. Hotelling, H. 1933...Sediments 99. ASCE: 2,566-2,581. Von Storch, H., and A. Navarra. 1995. Analysis of climate variability. Applications of statistical techniques. Berlin...ERDC TN-SWWRP-07-9 October 2007 Regional Morphology Empirical Analysis Package (RMAP): Orthogonal Function Analysis , Background and Examples by

Geometric Analysis of Wing Sections

DOT National Transportation Integrated Search

1995-04-01

This paper describes a new geometric analysis procedure for wing sections. This procedure is based on the normal mode analysis for continuous functions. A set of special shape functions is introduced to represent the geometry of the wing section. The...

Integrative analysis of environmental sequences using MEGAN4.

PubMed

Huson, Daniel H; Mitra, Suparna; Ruscheweyh, Hans-Joachim; Weber, Nico; Schuster, Stephan C

2011-09-01

A major challenge in the analysis of environmental sequences is data integration. The question is how to analyze different types of data in a unified approach, addressing both the taxonomic and functional aspects. To facilitate such analyses, we have substantially extended MEGAN, a widely used taxonomic analysis program. The new program, MEGAN4, provides an integrated approach to the taxonomic and functional analysis of metagenomic, metatranscriptomic, metaproteomic, and rRNA data. While taxonomic analysis is performed based on the NCBI taxonomy, functional analysis is performed using the SEED classification of subsystems and functional roles or the KEGG classification of pathways and enzymes. A number of examples illustrate how such analyses can be performed, and show that one can also import and compare classification results obtained using others' tools. MEGAN4 is freely available for academic purposes, and installers for all three major operating systems can be downloaded from www-ab.informatik.uni-tuebingen.de/software/megan.

Inferring Functional Neural Connectivity with Phase Synchronization Analysis: A Review of Methodology

PubMed Central

Sun, Junfeng; Li, Zhijun; Tong, Shanbao

2012-01-01

Functional neural connectivity is drawing increasing attention in neuroscience research. To infer functional connectivity from observed neural signals, various methods have been proposed. Among them, phase synchronization analysis is an important and effective one which examines the relationship of instantaneous phase between neural signals but neglecting the influence of their amplitudes. In this paper, we review the advances in methodologies of phase synchronization analysis. In particular, we discuss the definitions of instantaneous phase, the indexes of phase synchronization and their significance test, the issues that may affect the detection of phase synchronization and the extensions of phase synchronization analysis. In practice, phase synchronization analysis may be affected by observational noise, insufficient samples of the signals, volume conduction, and reference in recording neural signals. We make comments and suggestions on these issues so as to better apply phase synchronization analysis to inferring functional connectivity from neural signals. PMID:22577470

Molar Functional Relations and Clinical Behavior Analysis: Implications for Assessment and Treatment

ERIC Educational Resources Information Center

Waltz, Thomas J.; Follette, William C.

2009-01-01

The experimental analysis of behavior has identified several molar functional relations that are highly relevant to clinical behavior analysis. These include matching, discounting, momentum, and variability. Matching provides a broader analysis of how multiple sources of reinforcement influence how individuals choose to allocate their time and…

Dynamic analysis of patterns of renal sympathetic nerve activity: implications for renal function.

PubMed

DiBona, Gerald F

2005-03-01

Methods of dynamic analysis are used to provide additional understanding of the renal sympathetic neural control of renal function. The concept of functionally specific subgroups of renal sympathetic nerve fibres conveying information encoded in the frequency domain is presented. Analog pulse modulation and pseudorandom binary sequence stimulation patterns are used for the determination of renal vascular frequency response. Transfer function analysis is used to determine the effects of non-renal vasoconstrictor and vasoconstrictor intensities of renal sympathetic nerve activity on dynamic autoregulation of renal blood flow.

Text Mining Improves Prediction of Protein Functional Sites

PubMed Central

Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Earth Observatory Satellite system definition study. Report no. 3: Design/cost tradeoff studies. Appendix A: EOS program WBS dictionary. Appendix B: EOS mission functional analysis

NASA Technical Reports Server (NTRS)

1974-01-01

The work breakdown structure (WBS) dictionary for the Earth Observatory Satellite (EOS) is defined. The various elements of the EOS program are examined to include the aggregate of hardware, computer software, services, and data required to develop, produce, test, support, and operate the space vehicle and the companion ground data management system. A functional analysis of the EOS mission is developed. The operations for three typical EOS missions, Delta, Titan, and Shuttle launched are considered. The functions were determined for the top program elements, and the mission operations, function 2.0, was expanded to level one functions. Selection of ten level one functions for further analysis to level two and three functions were based on concern for the EOS operations and associated interfaces.

[Design and implementation of online statistical analysis function in information system of air pollution and health impact monitoring].

PubMed

Lü, Yiran; Hao, Shuxin; Zhang, Guoqing; Liu, Jie; Liu, Yue; Xu, Dongqun

2018-01-01

To implement the online statistical analysis function in information system of air pollution and health impact monitoring, and obtain the data analysis information real-time. Using the descriptive statistical method as well as time-series analysis and multivariate regression analysis, SQL language and visual tools to implement online statistical analysis based on database software. Generate basic statistical tables and summary tables of air pollution exposure and health impact data online; Generate tendency charts of each data part online and proceed interaction connecting to database; Generate butting sheets which can lead to R, SAS and SPSS directly online. The information system air pollution and health impact monitoring implements the statistical analysis function online, which can provide real-time analysis result to its users.

Streamflow characterization using functional data analysis of the Potomac River

NASA Astrophysics Data System (ADS)

Zelmanow, A.; Maslova, I.; Ticlavilca, A. M.; McKee, M.

2013-12-01

Flooding and droughts are extreme hydrological events that affect the United States economically and socially. The severity and unpredictability of flooding has caused billions of dollars in damage and the loss of lives in the eastern United States. In this context, there is an urgent need to build a firm scientific basis for adaptation by developing and applying new modeling techniques for accurate streamflow characterization and reliable hydrological forecasting. The goal of this analysis is to use numerical streamflow characteristics in order to classify, model, and estimate the likelihood of extreme events in the eastern United States, mainly the Potomac River. Functional data analysis techniques are used to study yearly streamflow patterns, with the extreme streamflow events characterized via functional principal component analysis. These methods are merged with more classical techniques such as cluster analysis, classification analysis, and time series modeling. The developed functional data analysis approach is used to model continuous streamflow hydrographs. The forecasting potential of this technique is explored by incorporating climate factors to produce a yearly streamflow outlook.

In vivo microvascular and macrovascular endothelial function is not associated with circulating dimethylarginines in patients with rheumatoid arthritis: a prospective analysis of the DRACCO cohort.

PubMed

Dimitroulas, Theodoros; Sandoo, Aamer; Hodson, James; Smith, Jacqueline P; Kitas, George D

2016-07-01

To examine associations between asymmetric (ADMA), symmetric dimethylarginine (SDMA) and ADMA:SDMA ratio with assessments of endothelial function and coronary artery perfusion in RA patients. ADMA and SDMA levels were measured in 197 RA individuals [144 (77.4%) females, median age: 66 years (quartiles: 59-73)]. Patients underwent assessments of microvascular endothelium-dependent and endothelium-independent function, macrovascular endothelium-dependent and endothelium-independent function and vascular morphology (pulse wave analysis, carotid intima-media thickness (cIMT), and carotid plaque). Coronary perfusion was assessed by subendocardial viability ratio (SEVR). SEVR correlated with SDMA (r = 0.172, p = 0.026) and ADMA:SDMA (r = -0.160, p = 0.041) in univariable analysis, but not in multivariable analysis accounting for confounding factors. Neither ADMA:SDMA ratio nor SDMA were significantly correlated with microvascular or macrovascular endothelial function, or with arterial stiffness and cIMT. Within subgroup of patients (n = 26) with high inflammatory markers, a post-hoc analysis showed that SDMA and the ADMA:SDMA ratio were significantly associated with endothelium-dependent microvascular function in univariable analysis, with Pearson's r correlation coefficients of -0.440 (p = 0.031) and 0.511 (p = 0.011), respectively. Similar finding were established between ADMA:SDMA ratio and arterial stiffness in univariable analysis, with Pearson's r of 0.493, (p = 0.024). Dimethylarginines were not found to be significantly associated with several assessments of vascular function and morphology in patients with RA, however, post-hoc analysis indicates that there may be associations in patients with raised inflammatory markers. Our results suggest that dysregulated NO metabolism may not be the sole mechanism for the development of preclinical atherosclerosis in RA.

A Factor Analysis of Functional Independence and Functional Assessment Measure Scores Among Focal and Diffuse Brain Injury Patients: The Importance of Bifactor Models.

PubMed

Gunn, Sarah; Burgess, Gerald H; Maltby, John

2018-04-30

To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. A National Health Service acute acquired brain injury inpatient rehabilitation hospital. Referred sample of N=447 adults admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation INTERVENTION: Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory factor analysis suggested a 2-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory factor analysis suggested a 3-factor bifactor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the exploratory factor analysis, and by a general factor explaining the majority of the variance in scores on confirmatory factor analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (eg, motor, psychosocial, and communication function) after brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Multilevel sparse functional principal component analysis.

PubMed

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

Advances in the quantification of mitochondrial function in primary human immune cells through extracellular flux analysis.

PubMed

Nicholas, Dequina; Proctor, Elizabeth A; Raval, Forum M; Ip, Blanche C; Habib, Chloe; Ritou, Eleni; Grammatopoulos, Tom N; Steenkamp, Devin; Dooms, Hans; Apovian, Caroline M; Lauffenburger, Douglas A; Nikolajczyk, Barbara S

2017-01-01

Numerous studies show that mitochondrial energy generation determines the effectiveness of immune responses. Furthermore, changes in mitochondrial function may regulate lymphocyte function in inflammatory diseases like type 2 diabetes. Analysis of lymphocyte mitochondrial function has been facilitated by introduction of 96-well format extracellular flux (XF96) analyzers, but the technology remains imperfect for analysis of human lymphocytes. Limitations in XF technology include the lack of practical protocols for analysis of archived human cells, and inadequate data analysis tools that require manual quality checks. Current analysis tools for XF outcomes are also unable to automatically assess data quality and delete untenable data from the relatively high number of biological replicates needed to power complex human cell studies. The objectives of work presented herein are to test the impact of common cellular manipulations on XF outcomes, and to develop and validate a new automated tool that objectively analyzes a virtually unlimited number of samples to quantitate mitochondrial function in immune cells. We present significant improvements on previous XF analyses of primary human cells that will be absolutely essential to test the prediction that changes in immune cell mitochondrial function and fuel sources support immune dysfunction in chronic inflammatory diseases like type 2 diabetes.

Combining Multiobjective Optimization and Cluster Analysis to Study Vocal Fold Functional Morphology

PubMed Central

Palaparthi, Anil; Riede, Tobias

2017-01-01

Morphological design and the relationship between form and function have great influence on the functionality of a biological organ. However, the simultaneous investigation of morphological diversity and function is difficult in complex natural systems. We have developed a multiobjective optimization (MOO) approach in association with cluster analysis to study the form-function relation in vocal folds. An evolutionary algorithm (NSGA-II) was used to integrate MOO with an existing finite element model of the laryngeal sound source. Vocal fold morphology parameters served as decision variables and acoustic requirements (fundamental frequency, sound pressure level) as objective functions. A two-layer and a three-layer vocal fold configuration were explored to produce the targeted acoustic requirements. The mutation and crossover parameters of the NSGA-II algorithm were chosen to maximize a hypervolume indicator. The results were expressed using cluster analysis and were validated against a brute force method. Results from the MOO and the brute force approaches were comparable. The MOO approach demonstrated greater resolution in the exploration of the morphological space. In association with cluster analysis, MOO can efficiently explore vocal fold functional morphology. PMID:24771563

Effect of exercise on cognitive function in chronic disease patients: a meta-analysis and systematic review of randomized controlled trials

PubMed Central

Cai, Hong; Li, Guichen; Hua, Shanshan; Liu, Yufei; Chen, Li

2017-01-01

Background The purpose of this study was to conduct a meta-analysis and systematic review to assess the effect of exercise on cognitive function in people with chronic diseases. Methods PubMed, Web of Science, Embase, the Cochrane Library, CINAHL, PsycINFO, and three Chinese databases were electronically searched for papers that were published until September 2016. This meta-analysis and systematic review included randomized controlled trials that evaluated the effect of exercise on cognitive function compared with control group for people with chronic diseases. Results Totally, 35 studies met the inclusion criteria, with 3,113 participants. The main analysis revealed a positive overall random effect of exercise intervention on cognitive function in patients with chronic diseases. The secondary analysis revealed that aerobic exercise interventions and aerobic included exercise interventions had a positive effect on cognition in patients with chronic diseases. The intervention offering low frequency had a positive effect on cognitive function in patients with chronic diseases. Finally, we found that interventions offered at both low exercise intensity and moderate exercise intensity had a positive effect on cognitive function in patients with chronic diseases. The secondary analysis also revealed that exercise interventions were beneficial in Alzheimer’s disease patients when grouped by disease type. Conclusion This meta-analysis and systematic review suggests that exercise interventions positively influence cognitive function in patients with chronic diseases. Beneficial effect was independent of the type of disease, type of exercise, frequency, and the intensity of the exercise intervention. PMID:28546744

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

PubMed Central

Seeley, Matthew K.; Francom, Devin; Reese, C. Shane; Hopkins, J. Ty

2017-01-01

Abstract In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function. PMID:29339984

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach.

PubMed

Park, Jihong; Seeley, Matthew K; Francom, Devin; Reese, C Shane; Hopkins, J Ty

2017-12-01

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle, knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. When using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

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

Park, Jihong; Seeley, Matthew K.; Francom, Devin

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle,more » knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.« less

Functional vs. Traditional Analysis in Biomechanical Gait Data: An Alternative Statistical Approach

DOE PAGES

Park, Jihong; Seeley, Matthew K.; Francom, Devin; ...

2017-12-28

In human motion studies, discrete points such as peak or average kinematic values are commonly selected to test hypotheses. The purpose of this study was to describe a functional data analysis and describe the advantages of using functional data analyses when compared with a traditional analysis of variance (ANOVA) approach. Nineteen healthy participants (age: 22 ± 2 yrs, body height: 1.7 ± 0.1 m, body mass: 73 ± 16 kg) walked under two different conditions: control and pain+effusion. Pain+effusion was induced by injection of sterile saline into the joint capsule and hypertonic saline into the infrapatellar fat pad. Sagittal-plane ankle,more » knee, and hip joint kinematics were recorded and compared following injections using 2×2 mixed model ANOVAs and FANOVAs. The results of ANOVAs detected a condition × time interaction for the peak ankle (F1,18 = 8.56, p = 0.01) and hip joint angle (F1,18 = 5.77, p = 0.03), but did not for the knee joint angle (F1,18 = 0.36, p = 0.56). The functional data analysis, however, found several differences at initial contact (ankle and knee joint), in the mid-stance (each joint) and at toe off (ankle). Although a traditional ANOVA is often appropriate for discrete or summary data, in biomechanical applications, the functional data analysis could be a beneficial alternative. Thus when using the functional data analysis approach, a researcher can (1) evaluate the entire data as a function, and (2) detect the location and magnitude of differences within the evaluated function.« less

The Necessity of Functional Analysis for Space Exploration Programs

NASA Technical Reports Server (NTRS)

Morris, A. Terry; Breidenthal, Julian C.

2011-01-01

As NASA moves toward expanded commercial spaceflight within its human exploration capability, there is increased emphasis on how to allocate responsibilities between government and commercial organizations to achieve coordinated program objectives. The practice of program-level functional analysis offers an opportunity for improved understanding of collaborative functions among heterogeneous partners. Functional analysis is contrasted with the physical analysis more commonly done at the program level, and is shown to provide theoretical performance, risk, and safety advantages beneficial to a government-commercial partnership. Performance advantages include faster convergence to acceptable system solutions; discovery of superior solutions with higher commonality, greater simplicity and greater parallelism by substituting functional for physical redundancy to achieve robustness and safety goals; and greater organizational cohesion around program objectives. Risk advantages include avoidance of rework by revelation of some kinds of architectural and contractual mismatches before systems are specified, designed, constructed, or integrated; avoidance of cost and schedule growth by more complete and precise specifications of cost and schedule estimates; and higher likelihood of successful integration on the first try. Safety advantages include effective delineation of must-work and must-not-work functions for integrated hazard analysis, the ability to formally demonstrate completeness of safety analyses, and provably correct logic for certification of flight readiness. The key mechanism for realizing these benefits is the development of an inter-functional architecture at the program level, which reveals relationships between top-level system requirements that would otherwise be invisible using only a physical architecture. This paper describes the advantages and pitfalls of functional analysis as a means of coordinating the actions of large heterogeneous organizations for space exploration programs.

Functional Behavioral Assessment: A School Based Model.

ERIC Educational Resources Information Center

Asmus, Jennifer M.; Vollmer, Timothy R.; Borrero, John C.

2002-01-01

This article begins by discussing requirements for functional behavioral assessment under the Individuals with Disabilities Education Act and then describes a comprehensive model for the application of behavior analysis in the schools. The model includes descriptive assessment, functional analysis, and intervention and involves the participation…

Function Invariant and Parameter Scale-Free Transformation Methods

ERIC Educational Resources Information Center

Bentler, P. M.; Wingard, Joseph A.

1977-01-01

A scale-invariant simple structure function of previously studied function components for principal component analysis and factor analysis is defined. First and second partial derivatives are obtained, and Newton-Raphson iterations are utilized. The resulting solutions are locally optimal and subjectively pleasing. (Author/JKS)

Detailed requirements document for the integrated structural analysis system, phase B

NASA Technical Reports Server (NTRS)

Rainey, J. A.

1976-01-01

The requirements are defined for a software system entitled integrated Structural Analysis System (ISAS) Phase B which is being developed to provide the user with a tool by which a complete and detailed analysis of a complex structural system can be performed. This software system will allow for automated interface with numerous structural analysis batch programs and for user interaction in the creation, selection, and validation of data. This system will include modifications to the 4 functions developed for ISAS, and the development of 25 new functions. The new functions are described.

Generalization of the subsonic kernel function in the s-plane, with applications to flutter analysis

NASA Technical Reports Server (NTRS)

Cunningham, H. J.; Desmarais, R. N.

1984-01-01

A generalized subsonic unsteady aerodynamic kernel function, valid for both growing and decaying oscillatory motions, is developed and applied in a modified flutter analysis computer program to solve the boundaries of constant damping ratio as well as the flutter boundary. Rates of change of damping ratios with respect to dynamic pressure near flutter are substantially lower from the generalized-kernel-function calculations than from the conventional velocity-damping (V-g) calculation. A rational function approximation for aerodynamic forces used in control theory for s-plane analysis gave rather good agreement with kernel-function results, except for strongly damped motion at combinations of high (subsonic) Mach number and reduced frequency.

Left atrial function: evaluation by strain analysis

PubMed Central

Gan, Gary C. H.; Ferkh, Aaisha; Boyd, Anita

2018-01-01

The left atrium has an important role in modulating left ventricular filling and is an important biomarker of cardiovascular disease and adverse cardiovascular outcomes. While previously left atrial (LA) size was utilised, the role of LA function as a biomarker is increasingly being evaluated, both independently and also in combination with LA size. Strain analysis has been utilised for evaluation of LA function and can be measured throughout the cardiac cycle, thereby enabling the evaluation of LA reservoir, conduit and contractile function. Strain evaluates myocardial deformation while strain rate examines the rate of change in strain. This review will focus on the various types of strain analysis for evaluation of LA function, alterations in LA strain in physiological and pathologic states that alter LA function and finally evaluate its utility as a prognostic marker. PMID:29541609

Functional Relationships and Regression Analysis.

ERIC Educational Resources Information Center

Preece, Peter F. W.

1978-01-01

Using a degenerate multivariate normal model for the distribution of organismic variables, the form of least-squares regression analysis required to estimate a linear functional relationship between variables is derived. It is suggested that the two conventional regression lines may be considered to describe functional, not merely statistical,…

Functional Analysis in Virtual Environments

ERIC Educational Resources Information Center

Vasquez, Eleazar, III; Marino, Matthew T.; Donehower, Claire; Koch, Aaron

2017-01-01

Functional analysis (FA) is an assessment procedure involving the systematic manipulation of an individual's environment to determine why a target behavior is occurring. An analog FA provides practitioners the opportunity to manipulate variables in a controlled environment and formulate a hypothesis for the function of a behavior. In previous…

Spherical Harmonic Analysis of Particle Velocity Distribution Function: Comparison of Moments and Anisotropies using Cluster Data

NASA Technical Reports Server (NTRS)

Gurgiolo, Chris; Vinas, Adolfo F.

2009-01-01

This paper presents a spherical harmonic analysis of the plasma velocity distribution function using high-angular, energy, and time resolution Cluster data obtained from the PEACE spectrometer instrument to demonstrate how this analysis models the particle distribution function and its moments and anisotropies. The results show that spherical harmonic analysis produced a robust physical representation model of the velocity distribution function, resolving the main features of the measured distributions. From the spherical harmonic analysis, a minimum set of nine spectral coefficients was obtained from which the moment (up to the heat flux), anisotropy, and asymmetry calculations of the velocity distribution function were obtained. The spherical harmonic method provides a potentially effective "compression" technique that can be easily carried out onboard a spacecraft to determine the moments and anisotropies of the particle velocity distribution function for any species. These calculations were implemented using three different approaches, namely, the standard traditional integration, the spherical harmonic (SPH) spectral coefficients integration, and the singular value decomposition (SVD) on the spherical harmonic methods. A comparison among the various methods shows that both SPH and SVD approaches provide remarkable agreement with the standard moment integration method.

Behavior analytic approaches to problem behavior in intellectual disabilities.

PubMed

Hagopian, Louis P; Gregory, Meagan K

2016-03-01

The purpose of the current review is to summarize recent behavior analytic research on problem behavior in individuals with intellectual disabilities. We have focused our review on studies published from 2013 to 2015, but also included earlier studies that were relevant. Behavior analytic research on problem behavior continues to focus on the use and refinement of functional behavioral assessment procedures and function-based interventions. During the review period, a number of studies reported on procedures aimed at making functional analysis procedures more time efficient. Behavioral interventions continue to evolve, and there were several larger scale clinical studies reporting on multiple individuals. There was increased attention on the part of behavioral researchers to develop statistical methods for analysis of within subject data and continued efforts to aggregate findings across studies through evaluative reviews and meta-analyses. Findings support continued utility of functional analysis for guiding individualized interventions and for classifying problem behavior. Modifications designed to make functional analysis more efficient relative to the standard method of functional analysis were reported; however, these require further validation. Larger scale studies on behavioral assessment and treatment procedures provided additional empirical support for effectiveness of these approaches and their sustainability outside controlled clinical settings.

Graph analysis of functional brain networks: practical issues in translational neuroscience

PubMed Central

De Vico Fallani, Fabrizio; Richiardi, Jonas; Chavez, Mario; Achard, Sophie

2014-01-01

The brain can be regarded as a network: a connected system where nodes, or units, represent different specialized regions and links, or connections, represent communication pathways. From a functional perspective, communication is coded by temporal dependence between the activities of different brain areas. In the last decade, the abstract representation of the brain as a graph has allowed to visualize functional brain networks and describe their non-trivial topological properties in a compact and objective way. Nowadays, the use of graph analysis in translational neuroscience has become essential to quantify brain dysfunctions in terms of aberrant reconfiguration of functional brain networks. Despite its evident impact, graph analysis of functional brain networks is not a simple toolbox that can be blindly applied to brain signals. On the one hand, it requires the know-how of all the methodological steps of the pipeline that manipulate the input brain signals and extract the functional network properties. On the other hand, knowledge of the neural phenomenon under study is required to perform physiologically relevant analysis. The aim of this review is to provide practical indications to make sense of brain network analysis and contrast counterproductive attitudes. PMID:25180301

Closed-loop, pilot/vehicle analysis of the approach and landing task

NASA Technical Reports Server (NTRS)

Anderson, M. R.; Schmidt, D. K.

1986-01-01

In the case of approach and landing, it is universally accepted that the pilot uses more than one vehicle response, or output, to close his control loops. Therefore, to model this task, a multi-loop analysis technique is required. The analysis problem has been in obtaining reasonable analytic estimates of the describing functions representing the pilot's loop compensation. Once these pilot describing functions are obtained, appropriate performance and workload metrics must then be developed for the landing task. The optimal control approach provides a powerful technique for obtaining the necessary describing functions, once the appropriate task objective is defined in terms of a quadratic objective function. An approach is presented through the use of a simple, reasonable objective function and model-based metrics to evaluate loop performance and pilot workload. The results of an analysis of the LAHOS (Landing and Approach of Higher Order Systems) study performed by R.E. Smith is also presented.

[Hazard function and life table: an introduction to the failure time analysis].

PubMed

Matsushita, K; Inaba, H

1987-04-01

Failure time analysis has become popular in demographic studies. It can be viewed as a part of regression analysis with limited dependent variables as well as a special case of event history analysis and multistate demography. The idea of hazard function and failure time analysis, however, has not been properly introduced to nor commonly discussed by demographers in Japan. The concept of hazard function in comparison with life tables is briefly described, where the force of mortality is interchangeable with the hazard rate. The basic idea of failure time analysis is summarized for the cases of exponential distribution, normal distribution, and proportional hazard models. The multiple decrement life table is also introduced as an example of lifetime data analysis with cause-specific hazard rates.

A Guided Tour of Mathematical Methods

NASA Astrophysics Data System (ADS)

Snieder, Roel

2009-04-01

1. Introduction; 2. Dimensional analysis; 3. Power series; 4. Spherical and cylindrical co-ordinates; 5. The gradient; 6. The divergence of a vector field; 7. The curl of a vector field; 8. The theorem of Gauss; 9. The theorem of Stokes; 10. The Laplacian; 11. Conservation laws; 12. Scale analysis; 13. Linear algebra; 14. The Dirac delta function; 15. Fourier analysis; 16. Analytic functions; 17. Complex integration; 18. Green's functions: principles; 19. Green's functions: examples; 20. Normal modes; 21. Potential theory; 22. Cartesian tensors; 23. Perturbation theory; 24. Asymptotic evaluation of integrals; 25. Variational calculus; 26. Epilogue, on power and knowledge; References.

Transforming user needs into functional requirements for an antibiotic clinical decision support system: explicating content analysis for system design.

PubMed

Bright, T J

2013-01-01

Many informatics studies use content analysis to generate functional requirements for system development. Explication of this translational process from qualitative data to functional requirements can strengthen the understanding and scientific rigor when applying content analysis in informatics studies. To describe a user-centered approach transforming emergent themes derived from focus group data into functional requirements for informatics solutions and to illustrate these methods to the development of an antibiotic clinical decision support system (CDS). THE APPROACH CONSISTED OF FIVE STEPS: 1) identify unmet therapeutic planning information needs via Focus Group Study-I, 2) develop a coding framework of therapeutic planning themes to refine the domain scope to antibiotic therapeutic planning, 3) identify functional requirements of an antibiotic CDS system via Focus Group Study-II, 4) discover informatics solutions and functional requirements from coded data, and 5) determine the types of information needed to support the antibiotic CDS system and link with the identified informatics solutions and functional requirements. The coding framework for Focus Group Study-I revealed unmet therapeutic planning needs. Twelve subthemes emerged and were clustered into four themes; analysis indicated a need for an antibiotic CDS intervention. Focus Group Study-II included five types of information needs. Comments from the Barrier/Challenge to information access and Function/Feature themes produced three informatics solutions and 13 functional requirements of an antibiotic CDS system. Comments from the Patient, Institution, and Domain themes generated required data elements for each informatics solution. This study presents one example explicating content analysis of focus group data and the analysis process to functional requirements from narrative data. Illustration of this 5-step method was used to develop an antibiotic CDS system, resolving unmet antibiotic prescribing needs. As a reusable approach, these techniques can be refined and applied to resolve unmet information needs with informatics interventions in additional domains.

A Mobile Computing Solution for Collecting Functional Analysis Data on a Pocket PC

ERIC Educational Resources Information Center

Jackson, James; Dixon, Mark R.

2007-01-01

The present paper provides a task analysis for creating a computerized data system using a Pocket PC and Microsoft Visual Basic. With Visual Basic software and any handheld device running the Windows MOBLE operating system, this task analysis will allow behavior analysts to program and customize their own functional analysis data-collection…

Functional Analysis and Treatment of Human-Directed Undesirable Behavior Exhibited by a Captive Chimpanzee

ERIC Educational Resources Information Center

Martin, Allison L.; Bloomsmith, Mollie A.; Kelley, Michael E.; Marr, M. Jackson; Maple, Terry L.

2011-01-01

A functional analysis identified the reinforcer maintaining feces throwing and spitting exhibited by a captive adult chimpanzee ("Pan troglodytes"). The implementation of a function-based treatment combining extinction with differential reinforcement of an alternate behavior decreased levels of inappropriate behavior. These findings further…

Analysis of Multiple Manding Topographies during Functional Communication Training

ERIC Educational Resources Information Center

Harding, Jay W.; Wacker, David P.; Berg, Wendy K.; Winborn-Kemmerer, Lisa; Lee, John F.; Ibrahimovic, Muska

2009-01-01

We evaluated the effects of reinforcing multiple manding topographies during functional communication training (FCT) to decrease problem behavior for three preschool-age children. During Phase 1, a functional analysis identified conditions that maintained problem behavior for each child. During Phase 2, the children's parents taught them to…

18 CFR 301.7 - Average System Cost methodology functionalization.

Code of Federal Regulations, 2010 CFR

2010-04-01

... SYSTEM COST METHODOLOGY FOR SALES FROM UTILITIES TO BONNEVILLE POWER ADMINISTRATION UNDER NORTHWEST POWER... functionalization under its Direct Analysis assigns costs, revenues, debits or credits based upon the actual and/or...) Functionalization methods. (1) Direct analysis, if allowed or required by Table 1, assigns costs, revenues, debits...

A Top Level Analysis of Training Management Functions.

ERIC Educational Resources Information Center

Ackerson, Jack

1995-01-01

Discusses how to conduct a top-level analysis of training management functions to identify problems within a training system resulting from rapid growth, the acquisition of new departments, or mergers. The data gathering process and analyses are explained, training management functions and activities are described, and root causes and solutions…

Classroom-Based Strategies to Incorporate Hypothesis Testing in Functional Behavior Assessments

ERIC Educational Resources Information Center

Lloyd, Blair P.; Weaver, Emily S.; Staubitz, Johanna L.

2017-01-01

When results of descriptive functional behavior assessments are unclear, hypothesis testing can help school teams understand how the classroom environment affects a student's challenging behavior. This article describes two hypothesis testing strategies that can be used in classroom settings: structural analysis and functional analysis. For each…

Functional Analysis and Intervention for Breath Holding.

ERIC Educational Resources Information Center

Kern, Lee; And Others

1995-01-01

A functional analysis of breath-holding episodes in a 7-year-old girl with severe mental retardation and Cornelia-de-Lange syndrome indicated that breath holding served an operant function, primarily to gain access to attention. Use of extinction, scheduled attention, and a picture card communication system decreased breath holding. (Author/SW)

Functional Assessment of Challenging Behavior: Toward a Strategy for Applied Settings

ERIC Educational Resources Information Center

Matson, Johnny L.; Minshawi, Noha F.

2007-01-01

The development of experimental functional analysis and more recently functional analysis checklists have become common technologies for evaluating antecedent events and the consequences of problematic behaviors. Children and developmentally disabled persons across the life span with challenging behaviors have been the primary focus of this…

Sectorial technetium-99m-dimercaptosuccinic acid scintigraphy for monitoring the effect of extracorporeal piezoelectric lithotripsy for calyceal calculi on regional renal function.

PubMed

Al-Tawheed, A; Al-Awadi, K A; Kehinde, E O; Loutfi, I; Abdul-Haleem, H; Al-Mohannadi, S

2003-01-01

To apply a semiquantitative method for analysis of technetium-99m-dimercaptosuccinic acid ((99m)Tc-DMSA) renal scintigraphy for monitoring the effect of extracorporeal piezoelectric lithotripsy (EPL) in patients with calyceal stones on regional kidney function and to check whether EPL had caused any deleterious effect on the target calyceal renal parenchymal function. Forty patients (mean age 35 years) suffering from calyceal stones documented by abdominal plain radiography, intravenous urogram or abdominal ultrasound were studied. All patients were treated by EPL. (99m)Tc-DMSA scan was performed before and 4 weeks after EPL. Sector analysis involved calculation of the relative function of the target calyx to the function of the ipsilateral kidney and the relative function of the treated kidney to global renal function. The stone sizes were 6-11 mm in diameter and 11 were located in the upper, 13 in the middle and 16 in the lower calyx. After EPL, the overall stone clearance rate was 85% (100% for calculi in the upper and middle calyces, 62% for lower calyces). The sector analysis did not show statistically significant change of the relative regional (calyceal) or whole kidney function between the pre- and post-EPL (99m)Tc-DMSA scans. Using sector analysis, EPL appeared to be a safe modality and its usage was not associated with any untoward effect on calyceal or whole kidney function. Sector analysis of (99m)Tc-DMSA renal scan is a simple semiquantitative method for monitoring regional changes of kidney function after EPL for treatment of calyceal stone. Copyright 2003 S. Karger AG, Basel

Unified Sequence-Based Association Tests Allowing for Multiple Functional Annotations and Meta-analysis of Noncoding Variation in Metabochip Data.

PubMed

He, Zihuai; Xu, Bin; Lee, Seunggeun; Ionita-Laza, Iuliana

2017-09-07

Substantial progress has been made in the functional annotation of genetic variation in the human genome. Integrative analysis that incorporates such functional annotations into sequencing studies can aid the discovery of disease-associated genetic variants, especially those with unknown function and located outside protein-coding regions. Direct incorporation of one functional annotation as weight in existing dispersion and burden tests can suffer substantial loss of power when the functional annotation is not predictive of the risk status of a variant. Here, we have developed unified tests that can utilize multiple functional annotations simultaneously for integrative association analysis with efficient computational techniques. We show that the proposed tests significantly improve power when variant risk status can be predicted by functional annotations. Importantly, when functional annotations are not predictive of risk status, the proposed tests incur only minimal loss of power in relation to existing dispersion and burden tests, and under certain circumstances they can even have improved power by learning a weight that better approximates the underlying disease model in a data-adaptive manner. The tests can be constructed with summary statistics of existing dispersion and burden tests for sequencing data, therefore allowing meta-analysis of multiple studies without sharing individual-level data. We applied the proposed tests to a meta-analysis of noncoding rare variants in Metabochip data on 12,281 individuals from eight studies for lipid traits. By incorporating the Eigen functional score, we detected significant associations between noncoding rare variants in SLC22A3 and low-density lipoprotein and total cholesterol, associations that are missed by standard dispersion and burden tests. Copyright © 2017 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Functional Extended Redundancy Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Suk, Hye Won; Lee, Jang-Han; Moskowitz, D. S.; Lim, Jooseop

2012-01-01

We propose a functional version of extended redundancy analysis that examines directional relationships among several sets of multivariate variables. As in extended redundancy analysis, the proposed method posits that a weighed composite of each set of exogenous variables influences a set of endogenous variables. It further considers endogenous…

Risk Perception as the Quantitative Parameter of Ethics and Responsibility in Disaster Study

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy; Movchan, Dmytro

2014-05-01

Intensity of impacts of natural disasters is increasing with climate and ecological changes spread. Frequency of disasters is increasing, and recurrence of catastrophes characterizing by essential spatial heterogeneity. Distribution of losses is fundamentally non-linear and reflects complex interrelation of natural, social and environmental factor in the changing world on multi scale range. We faced with new types of risks, which require a comprehensive security concept. Modern understanding of complex security, and complex risk management require analysis of all natural and social phenomena, involvement of all available data, constructing of advanced analytical tools, and transformation of our perception of risk and security issues. Traditional deterministic models used for risk analysis are difficult applicable for analysis of social issues, as well as for analysis of multi scale multi-physics phenomena quantification. Also parametric methods are not absolutely effective because the system analyzed is essentially non-ergodic. The stochastic models of risk analysis are applicable for quantitative analysis of human behavior and risk perception. In framework of risk analysis models the risk perception issues were described. Risk is presented as the superposition of distribution (f(x,y)) and damage functions (p(x,y)): P →δΣ x,yf(x,y)p(x,y). As it was shown risk perception essentially influents to the damage function. Basing on the prospect theory and decision making under uncertainty on cognitive bias and handling of risk, modification of damage function is proposed: p(x,y|α(t)). Modified damage function includes an awareness function α(t), which is the system of risk perception function (rp) and function of education and log-term experience (c) as: α(t) → (c - rp). Education function c(t) describes the trend of education and experience. Risk perception function rp reflects security concept of human behavior, is the basis for prediction of socio-economic and socio-ecological processes. Also there is important positive feedback of risk perception function to distribution function. Risk perception is essentially depends of short-term recent events impact in multi agent media. This is managed function. The generalized view of awareness function is proposed: α(t) = δΣ ic - rpi. Using this form separate parameters has been calculated. For example, risk perception function is about 15-55% of awareness function depends of education, age and social status of people. Also it was estimated that fraction of awareness function in damage function, and so in function of risk is about 15-20%. It means that no less than 8-12% of direct losses depend of short-term responsible behavior of 'information agents': social activity of experts, scientists, correct discussions on ethical issues in geo-sciences and media. Other 6-9% of losses are connected with level of public and professional education. This area is also should be field of responsibility of geo-scientists.

Relations among Functional Systems in Behavior Analysis

PubMed Central

Thompson, Travis

2007-01-01

This paper proposes that an organism's integrated repertoire of operant behavior has the status of a biological system, similar to other biological systems, like the nervous, cardiovascular, or immune systems. Evidence from a number of sources indicates that the distinctions between biological and behavioral events is often misleading, engendering counterproductive explanatory controversy. A good deal of what is viewed as biological (often thought to be inaccessible or hypothetical) can become publicly measurable variables using currently available and developing technologies. Moreover, such endogenous variables can serve as establishing operations, discriminative stimuli, conjoint mediating events, and maintaining consequences within a functional analysis of behavior and need not lead to reductionistic explanation. I suggest that explanatory misunderstandings often arise from conflating different levels of analysis and that behavior analysis can extend its reach by identifying variables operating within a functional analysis that also serve functions in other biological systems. PMID:17575907

Emotional functioning of adolescents and adults with congenital heart disease: a meta-analysis.

PubMed

Jackson, Jamie L; Misiti, Brian; Bridge, Jeffrey A; Daniels, Curt J; Vannatta, Kathryn

2015-01-01

This study aimed to quantitatively compare findings of emotional functioning across studies of adolescents and adults with congenital heart disease (CHD) through meta-analysis. The current meta-analysis included 22 studies of adolescent and adult survivors of CHD who completed measures of emotional functioning. Effect sizes were represented by Hedge's g. Heterogeneity was calculated and possible moderators (i.e., lesion severity, age, study location, study quality) were examined. Overall, adolescent and adult survivors of CHD did not differ in emotional functioning from healthy controls or normative data. However, significant heterogeneity was found, and there was a trend for degree of lesion severity to moderate emotional functioning. Further analysis of lesion severity indicated that individuals with moderate lesions reported better emotional functioning than controls/normative data. Limitations in existing literature precluded examination of patient age as a moderator. Study location and quality did not explain a significant portion of the variance in effects. Findings suggest that differences in emotional functioning may exist across lesion severities, and individuals with moderately severe lesions are emotionally thriving. Given the diversity within CHD lesion classifications, future studies should include other indicators of disease severity, such as measures of morbidity, to determine how disease may affect emotional functioning among survivors of CHD. Furthermore, authors and journals need to ensure that research is reported in enough detail to facilitate meta-analysis, a critically important tool in answering discrepancies in the literature. © 2014 Wiley Periodicals, Inc.

Functional connectomics from a "big data" perspective.

PubMed

Xia, Mingrui; He, Yong

2017-10-15

In the last decade, explosive growth regarding functional connectome studies has been observed. Accumulating knowledge has significantly contributed to our understanding of the brain's functional network architectures in health and disease. With the development of innovative neuroimaging techniques, the establishment of large brain datasets and the increasing accumulation of published findings, functional connectomic research has begun to move into the era of "big data", which generates unprecedented opportunities for discovery in brain science and simultaneously encounters various challenging issues, such as data acquisition, management and analyses. Big data on the functional connectome exhibits several critical features: high spatial and/or temporal precision, large sample sizes, long-term recording of brain activity, multidimensional biological variables (e.g., imaging, genetic, demographic, cognitive and clinic) and/or vast quantities of existing findings. We review studies regarding functional connectomics from a big data perspective, with a focus on recent methodological advances in state-of-the-art image acquisition (e.g., multiband imaging), analysis approaches and statistical strategies (e.g., graph theoretical analysis, dynamic network analysis, independent component analysis, multivariate pattern analysis and machine learning), as well as reliability and reproducibility validations. We highlight the novel findings in the application of functional connectomic big data to the exploration of the biological mechanisms of cognitive functions, normal development and aging and of neurological and psychiatric disorders. We advocate the urgent need to expand efforts directed at the methodological challenges and discuss the direction of applications in this field. Copyright © 2017 Elsevier Inc. All rights reserved.

Characterisation of the novel deleterious RAD51C p.Arg312Trp variant and prioritisation criteria for functional analysis of RAD51C missense changes.

PubMed

Gayarre, Javier; Martín-Gimeno, Paloma; Osorio, Ana; Paumard, Beatriz; Barroso, Alicia; Fernández, Victoria; de la Hoya, Miguel; Rojo, Alejandro; Caldés, Trinidad; Palacios, José; Urioste, Miguel; Benítez, Javier; García, María J

2017-09-26

Despite a high prevalence of deleterious missense variants, most studies of RAD51C ovarian cancer susceptibility gene only provide in silico pathogenicity predictions of missense changes. We identified a novel deleterious RAD51C missense variant (p.Arg312Trp) in a high-risk family, and propose a criteria to prioritise RAD51C missense changes qualifying for functional analysis. To evaluate pathogenicity of p.Arg312Trp variant we used sequence homology, loss of heterozygosity (LOH) and segregation analysis, and a comprehensive functional characterisation. To define a functional-analysis prioritisation criteria, we used outputs for the known functionally confirmed deleterious and benign RAD51C missense changes from nine pathogenicity prediction algorithms. The p.Arg312Trp variant failed to correct mitomycin and olaparib hypersensitivity and to complement abnormal RAD51C foci formation according to functional assays, which altogether with LOH and segregation data demonstrated deleteriousness. Prioritisation criteria were based on the number of predictors providing a deleterious output, with a minimum of 5 to qualify for testing and a PredictProtein score greater than 33 to assign high-priority indication. Our study points to a non-negligible number of RAD51C missense variants likely to impair protein function, provides a guideline to prioritise and encourage their selection for functional analysis and anticipates that reference laboratories should have available resources to conduct such assays.

Quality parameters analysis of optical imaging systems with enhanced focal depth using the Wigner distribution function

PubMed

Zalvidea; Colautti; Sicre

2000-05-01

An analysis of the Strehl ratio and the optical transfer function as imaging quality parameters of optical elements with enhanced focal length is carried out by employing the Wigner distribution function. To this end, we use four different pupil functions: a full circular aperture, a hyper-Gaussian aperture, a quartic phase plate, and a logarithmic phase mask. A comparison is performed between the quality parameters and test images formed by these pupil functions at different defocus distances.

INFANT SIGN TRAINING AND FUNCTIONAL ANALYSIS

PubMed Central

Normand, Matthew P; Machado, Mychal A; Hustyi, Kristin M; Morley, Allison J

2011-01-01

We taught manual signs to typically developing infants using a reversal design and caregiver-nominated stimuli. We delivered the stimuli on a time-based schedule during baseline. During the intervention, we used progressive prompting and reinforcement, described by Thompson et al. (2004, 2007), to establish mands. Following sign training, we conducted functional analyses and verified that the signs functioned as mands. These results provide preliminary validation for the verbal behavior functional analysis methodology and further evidence of the functional independence of verbal operants. PMID:21709786

Large-scale genome-wide analysis identifies genetic variants associated with cardiac structure and function

PubMed Central

Wild, Philipp S.; Felix, Janine F.; Schillert, Arne; Chen, Ming-Huei; Leening, Maarten J.G.; Völker, Uwe; Großmann, Vera; Brody, Jennifer A.; Irvin, Marguerite R.; Shah, Sanjiv J.; Pramana, Setia; Lieb, Wolfgang; Schmidt, Reinhold; Stanton, Alice V.; Malzahn, Dörthe; Lyytikäinen, Leo-Pekka; Tiller, Daniel; Smith, J. Gustav; Di Tullio, Marco R.; Musani, Solomon K.; Morrison, Alanna C.; Pers, Tune H.; Morley, Michael; Kleber, Marcus E.; Aragam, Jayashri; Bis, Joshua C.; Bisping, Egbert; Broeckel, Ulrich; Cheng, Susan; Deckers, Jaap W.; Del Greco M, Fabiola; Edelmann, Frank; Fornage, Myriam; Franke, Lude; Friedrich, Nele; Harris, Tamara B.; Hofer, Edith; Hofman, Albert; Huang, Jie; Hughes, Alun D.; Kähönen, Mika; investigators, KNHI; Kruppa, Jochen; Lackner, Karl J.; Lannfelt, Lars; Laskowski, Rafael; Launer, Lenore J.; Lindgren, Cecilia M.; Loley, Christina; Mayet, Jamil; Medenwald, Daniel; Morris, Andrew P.; Müller, Christian; Müller-Nurasyid, Martina; Nappo, Stefania; Nilsson, Peter M.; Nuding, Sebastian; Nutile, Teresa; Peters, Annette; Pfeufer, Arne; Pietzner, Diana; Pramstaller, Peter P.; Raitakari, Olli T.; Rice, Kenneth M.; Rotter, Jerome I.; Ruohonen, Saku T.; Sacco, Ralph L.; Samdarshi, Tandaw E.; Sharp, Andrew S.P.; Shields, Denis C.; Sorice, Rossella; Sotoodehnia, Nona; Stricker, Bruno H.; Surendran, Praveen; Töglhofer, Anna M.; Uitterlinden, André G.; Völzke, Henry; Ziegler, Andreas; Münzel, Thomas; März, Winfried; Cappola, Thomas P.; Hirschhorn, Joel N.; Mitchell, Gary F.; Smith, Nicholas L.; Fox, Ervin R.; Dueker, Nicole D.; Jaddoe, Vincent W.V.; Melander, Olle; Lehtimäki, Terho; Ciullo, Marina; Hicks, Andrew A.; Lind, Lars; Gudnason, Vilmundur; Pieske, Burkert; Barron, Anthony J.; Zweiker, Robert; Schunkert, Heribert; Ingelsson, Erik; Liu, Kiang; Arnett, Donna K.; Psaty, Bruce M.; Blankenberg, Stefan; Larson, Martin G.; Felix, Stephan B.; Franco, Oscar H.; Zeller, Tanja; Vasan, Ramachandran S.; Dörr, Marcus

2017-01-01

BACKGROUND. Understanding the genetic architecture of cardiac structure and function may help to prevent and treat heart disease. This investigation sought to identify common genetic variations associated with inter-individual variability in cardiac structure and function. METHODS. A GWAS meta-analysis of echocardiographic traits was performed, including 46,533 individuals from 30 studies (EchoGen consortium). The analysis included 16 traits of left ventricular (LV) structure, and systolic and diastolic function. RESULTS. The discovery analysis included 21 cohorts for structural and systolic function traits (n = 32,212) and 17 cohorts for diastolic function traits (n = 21,852). Replication was performed in 5 cohorts (n = 14,321) and 6 cohorts (n = 16,308), respectively. Besides 5 previously reported loci, the combined meta-analysis identified 10 additional genome-wide significant SNPs: rs12541595 near MTSS1 and rs10774625 in ATXN2 for LV end-diastolic internal dimension; rs806322 near KCNRG, rs4765663 in CACNA1C, rs6702619 near PALMD, rs7127129 in TMEM16A, rs11207426 near FGGY, rs17608766 in GOSR2, and rs17696696 in CFDP1 for aortic root diameter; and rs12440869 in IQCH for Doppler transmitral A-wave peak velocity. Findings were in part validated in other cohorts and in GWAS of related disease traits. The genetic loci showed associations with putative signaling pathways, and with gene expression in whole blood, monocytes, and myocardial tissue. CONCLUSION. The additional genetic loci identified in this large meta-analysis of cardiac structure and function provide insights into the underlying genetic architecture of cardiac structure and warrant follow-up in future functional studies. FUNDING. For detailed information per study, see Acknowledgments. PMID:28394258

FunShift: a database of function shift analysis on protein subfamilies

PubMed Central

Abhiman, Saraswathi; Sonnhammer, Erik L. L.

2005-01-01

Members of a protein family normally have a general biochemical function in common, but frequently one or more subgroups have evolved a slightly different function, such as different substrate specificity. It is important to detect such function shifts for a more accurate functional annotation. The FunShift database described here is a compilation of function shift analysis performed between subfamilies in protein families. It consists of two main components: (i) subfamilies derived from protein domain families and (ii) pairwise subfamily comparisons analyzed for function shift. The present release, FunShift 12, was derived from Pfam 12 and consists of 151 934 subfamilies derived from 7300 families. We carried out function shift analysis by two complementary methods on families with up to 500 members. From a total of 179 210 subfamily pairs, 62 384 were predicted to be functionally shifted in 2881 families. Each subfamily pair is provided with a markup of probable functional specificity-determining sites. Tools for searching and exploring the data are provided to make this database a valuable resource for protein function annotation. Knowledge of these functionally important sites will be useful for experimental biologists performing functional mutation studies. FunShift is available at http://FunShift.cgb.ki.se. PMID:15608176

The Need for the United States Army to Possess a Landing Craft with Maneuver Capabilities

DTIC Science & Technology

2015-06-12

Personnel, Facilities and Policy FAA Functional Area Analysis FNA Functional Needs Analysis FSA Functional Solution Analysis HADR Humanitarian ...increase the options available to the JTFC.7 Within the last 25 years, the LCM-8 and other landing craft have been used numerous times for Humanitarian ...and coastal islands after the bridges were destroyed.8 The World Food Program (WFP) and other humanitarian aid providers perfected the use of military

The most common technologies and tools for functional genome analysis.

PubMed

Gasperskaja, Evelina; Kučinskas, Vaidutis

2017-01-01

Since the sequence of the human genome is complete, the main issue is how to understand the information written in the DNA sequence. Despite numerous genome-wide studies that have already been performed, the challenge to determine the function of genes, gene products, and also their interaction is still open. As changes in the human genome are highly likely to cause pathological conditions, functional analysis is vitally important for human health. For many years there have been a variety of technologies and tools used in functional genome analysis. However, only in the past decade there has been rapid revolutionizing progress and improvement in high-throughput methods, which are ranging from traditional real-time polymerase chain reaction to more complex systems, such as next-generation sequencing or mass spectrometry. Furthermore, not only laboratory investigation, but also accurate bioinformatic analysis is required for reliable scientific results. These methods give an opportunity for accurate and comprehensive functional analysis that involves various fields of studies: genomics, epigenomics, proteomics, and interactomics. This is essential for filling the gaps in the knowledge about dynamic biological processes at both cellular and organismal level. However, each method has both advantages and limitations that should be taken into account before choosing the right method for particular research in order to ensure successful study. For this reason, the present review paper aims to describe the most frequent and widely-used methods for the comprehensive functional analysis.

Uncertainty importance analysis using parametric moment ratio functions.

PubMed

Wei, Pengfei; Lu, Zhenzhou; Song, Jingwen

2014-02-01

This article presents a new importance analysis framework, called parametric moment ratio function, for measuring the reduction of model output uncertainty when the distribution parameters of inputs are changed, and the emphasis is put on the mean and variance ratio functions with respect to the variances of model inputs. The proposed concepts efficiently guide the analyst to achieve a targeted reduction on the model output mean and variance by operating on the variances of model inputs. The unbiased and progressive unbiased Monte Carlo estimators are also derived for the parametric mean and variance ratio functions, respectively. Only a set of samples is needed for implementing the proposed importance analysis by the proposed estimators, thus the computational cost is free of input dimensionality. An analytical test example with highly nonlinear behavior is introduced for illustrating the engineering significance of the proposed importance analysis technique and verifying the efficiency and convergence of the derived Monte Carlo estimators. Finally, the moment ratio function is applied to a planar 10-bar structure for achieving a targeted 50% reduction of the model output variance. © 2013 Society for Risk Analysis.

Functional Interaction Network Construction and Analysis for Disease Discovery.

PubMed

Wu, Guanming; Haw, Robin

2017-01-01

Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

Grey Matter Alterations Co-Localize with Functional Abnormalities in Developmental Dyslexia: An ALE Meta-Analysis

PubMed Central

Linkersdörfer, Janosch; Lonnemann, Jan; Lindberg, Sven; Hasselhorn, Marcus; Fiebach, Christian J.

2012-01-01

The neural correlates of developmental dyslexia have been investigated intensively over the last two decades and reliable evidence for a dysfunction of left-hemispheric reading systems in dyslexic readers has been found in functional neuroimaging studies. In addition, structural imaging studies using voxel-based morphometry (VBM) demonstrated grey matter reductions in dyslexics in several brain regions. To objectively assess the consistency of these findings, we performed activation likelihood estimation (ALE) meta-analysis on nine published VBM studies reporting 62 foci of grey matter reduction in dyslexic readers. We found six significant clusters of convergence in bilateral temporo-parietal and left occipito-temporal cortical regions and in the cerebellum bilaterally. To identify possible overlaps between structural and functional deviations in dyslexic readers, we conducted additional ALE meta-analyses of imaging studies reporting functional underactivations (125 foci from 24 studies) or overactivations (95 foci from 11 studies ) in dyslexics. Subsequent conjunction analyses revealed overlaps between the results of the VBM meta-analysis and the meta-analysis of functional underactivations in the fusiform and supramarginal gyri of the left hemisphere. An overlap between VBM results and the meta-analysis of functional overactivations was found in the left cerebellum. The results of our study provide evidence for consistent grey matter variations bilaterally in the dyslexic brain and substantial overlap of these structural variations with functional abnormalities in left hemispheric regions. PMID:22916214

A time-frequency analysis method to obtain stable estimates of magnetotelluric response function based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Cai, Jianhua

2017-05-01

The time-frequency analysis method represents signal as a function of time and frequency, and it is considered a powerful tool for handling arbitrary non-stationary time series by using instantaneous frequency and instantaneous amplitude. It also provides a possible alternative to the analysis of the non-stationary magnetotelluric (MT) signal. Based on the Hilbert-Huang transform (HHT), a time-frequency analysis method is proposed to obtain stable estimates of the magnetotelluric response function. In contrast to conventional methods, the response function estimation is performed in the time-frequency domain using instantaneous spectra rather than in the frequency domain, which allows for imaging the response parameter content as a function of time and frequency. The theory of the method is presented and the mathematical model and calculation procedure, which are used to estimate response function based on HHT time-frequency spectrum, are discussed. To evaluate the results, response function estimates are compared with estimates from a standard MT data processing method based on the Fourier transform. All results show that apparent resistivities and phases, which are calculated from the HHT time-frequency method, are generally more stable and reliable than those determined from the simple Fourier analysis. The proposed method overcomes the drawbacks of the traditional Fourier methods, and the resulting parameter minimises the estimation bias caused by the non-stationary characteristics of the MT data.

Aircraft/Air Traffic Management Functional Analysis Model: Technical Description. 2.0

NASA Technical Reports Server (NTRS)

Etheridge, Melvin; Plugge, Joana; Retina, Nusrat

1998-01-01

The Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 (FAM 2.0), is a discrete event simulation model designed to support analysis of alternative concepts in air traffic management and control. FAM 2.0 was developed by the Logistics Management Institute (LMI) under a National Aeronautics and Space Administration (NASA) contract. This document provides a technical description of FAM 2.0 and its computer files to enable the modeler and programmer to make enhancements or modifications to the model. Those interested in a guide for using the model in analysis should consult the companion document, Aircraft/Air Traffic Management Functional Analysis Model, Version 2.0 Users Manual.

EXPLORING FUNCTIONAL CONNECTIVITY IN FMRI VIA CLUSTERING.

PubMed

Venkataraman, Archana; Van Dijk, Koene R A; Buckner, Randy L; Golland, Polina

2009-04-01

In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering algorithms as alternatives to the commonly used Seed-Based Analysis. To enable clustering of the entire brain volume, we use the Nyström Method to approximate the necessary spectral decompositions. We apply K-Means, Spectral Clustering and Seed-Based Analysis to resting-state fMRI data collected from 45 healthy young adults. Without placing any a priori constraints, both clustering methods yield partitions that are associated with brain systems previously identified via Seed-Based Analysis. Our empirical results suggest that clustering provides a valuable tool for functional connectivity analysis.

Spectral Analysis: From Additive Perspective to Multiplicative Perspective

NASA Astrophysics Data System (ADS)

Wu, Z.

2017-12-01

The early usage of trigonometric functions can be traced back to at least 17th century BC. It was Bhaskara II of the 12th century CE who first proved the mathematical equivalence between the sum of two trigonometric functions of any given angles and the product of two trigonometric functions of related angles, which has been taught these days in middle school classroom. The additive perspective of trigonometric functions led to the development of the Fourier transform that is used to express any functions as the sum of a set of trigonometric functions and opened a new mathematical field called harmonic analysis. Unfortunately, Fourier's sum cannot directly express nonlinear interactions between trigonometric components of different periods, and thereby lacking the capability of quantifying nonlinear interactions in dynamical systems. In this talk, the speaker will introduce the Huang transform and Holo-spectrum which were pioneered by Norden Huang and emphasizes the multiplicative perspective of trigonometric functions in expressing any function. Holo-spectrum is a multi-dimensional spectral expression of a time series that explicitly identifies the interactions among different scales and quantifies nonlinear interactions hidden in a time series. Along with this introduction, the developing concepts of physical, rather than mathematical, analysis of data will be explained. Various enlightening applications of Holo-spectrum analysis in atmospheric and climate studies will also be presented.

75 FR 45133 - Statement of Organization, Functions, and Delegations of Authority

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-02

... Management Analysis and Services Office, Office of the Chief Operating Officer, Centers for Disease Control... entirety the titles and functional statements for the Management Analysis and Services Office (CAJG), insert the following: Management Analysis and Services Office (CAJG). The mission of the Management...

Oak Ridge Environmental Information System (OREIS) functional system design document

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

Birchfield, T.E.; Brown, M.O.; Coleman, P.R.

1994-03-01

The OREIS Functional System Design document provides a detailed functional description of the Oak Ridge Environmental Information System (OREIS). It expands the system requirements defined in the OREIS Phase 1-System Definition Document (ES/ER/TM-34). Documentation of OREIS development is based on the Automated Data Processing System Development Methodology, a Martin Marietta Energy Systems, Inc., procedure written to assist in developing scientific and technical computer systems. This document focuses on the development of the functional design of the user interface, which includes the integration of commercial applications software. The data model and data dictionary are summarized briefly; however, the Data Management Planmore » for OREIS (ES/ER/TM-39), a companion document to the Functional System Design document, provides the complete data dictionary and detailed descriptions of the requirements for the data base structure. The OREIS system will provide the following functions, which are executed from a Menu Manager: (1) preferences, (2) view manager, (3) macro manager, (4) data analysis (assisted analysis and unassisted analysis), and (5) spatial analysis/map generation (assisted ARC/INFO and unassisted ARC/INFO). Additional functionality includes interprocess communications, which handle background operations of OREIS.« less

Do tasks make a difference? Accounting for heterogeneity of performance of children with reading difficulties on tasks of executive function: findings from a meta-analysis.

PubMed

Booth, Josephine N; Boyle, James M E; Kelly, Steve W

2010-03-01

Research studies have implicated executive functions in reading difficulties (RD). But while some studies have found children with RD to be impaired on tasks of executive function other studies report unimpaired performance. A meta-analysis was carried out to determine whether these discrepant findings can be accounted for by differences in the tasks of executive function that are utilized. A total of 48 studies comparing the performance on tasks of executive function of children with RD with their typically developing peers were included in the meta-analysis, yielding 180 effect sizes. An overall effect size of 0.57 (SE .03) was obtained, indicating that children with RD have impairments on tasks of executive function. However, effect sizes varied considerably suggesting that the impairment is not uniform. Moderator analysis revealed that task modality and IQ-achievement discrepancy definitions of RD influenced the magnitude of effect; however, the age and gender of participants and the nature of the RD did not have an influence. While the children's RD were associated with executive function impairments, variation in effect size is a product of the assessment task employed, underlying task demands, and definitional criteria.

Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.

PubMed

Li, Lianshuo; Wang, Zicheng; He, Peng; Ma, Shining; Du, Jie; Jiang, Rui

2016-10-01

Although networks of microbial species have been widely used in the analysis of 16S rRNA sequencing data of a microbiome, the construction and analysis of a complete microbial gene network are in general problematic because of the large number of microbial genes in metagenomics studies. To overcome this limitation, we propose to map microbial genes to functional units, including KEGG orthologous groups and the evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG) orthologous groups, to enable the construction and analysis of a microbial functional network. We devised two statistical methods to infer pairwise relationships between microbial functional units based on a deep sequencing dataset of gut microbiome from type 2 diabetes (T2D) patients as well as healthy controls. Networks containing such functional units and their significant interactions were constructed subsequently. We conducted a variety of analyses of global properties, local properties, and functional modules in the resulting functional networks. Our data indicate that besides the observations consistent with the current knowledge, this study provides novel biological insights into the gut microbiome associated with T2D. Copyright © 2016. Production and hosting by Elsevier Ltd.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Zebra: a web server for bioinformatic analysis of diverse protein families.

PubMed

Suplatov, Dmitry; Kirilin, Evgeny; Takhaveev, Vakil; Svedas, Vytas

2014-01-01

During evolution of proteins from a common ancestor, one functional property can be preserved while others can vary leading to functional diversity. A systematic study of the corresponding adaptive mutations provides a key to one of the most challenging problems of modern structural biology - understanding the impact of amino acid substitutions on protein function. The subfamily-specific positions (SSPs) are conserved within functional subfamilies but are different between them and, therefore, seem to be responsible for functional diversity in protein superfamilies. Consequently, a corresponding method to perform the bioinformatic analysis of sequence and structural data has to be implemented in the common laboratory practice to study the structure-function relationship in proteins and develop novel protein engineering strategies. This paper describes Zebra web server - a powerful remote platform that implements a novel bioinformatic analysis algorithm to study diverse protein families. It is the first application that provides specificity determinants at different levels of functional classification, therefore addressing complex functional diversity of large superfamilies. Statistical analysis is implemented to automatically select a set of highly significant SSPs to be used as hotspots for directed evolution or rational design experiments and analyzed studying the structure-function relationship. Zebra results are provided in two ways - (1) as a single all-in-one parsable text file and (2) as PyMol sessions with structural representation of SSPs. Zebra web server is available at http://biokinet.belozersky.msu.ru/zebra .

Analytical Tools for Affordability Analysis

DTIC Science & Technology

2015-05-01

function (Womer)  Unit cost as a function of learning and rate  Learning with forgetting (Benkard)  Learning depreciates over time  Discretionary...Analytical Tools for Affordability Analysis David Tate Cost Analysis and Research Division Institute for Defense Analyses Report Documentation...ES) Institute for Defense Analyses, Cost Analysis and Research Division,4850 Mark Center Drive,Alexandria,VA,22311-1882 8. PERFORMING ORGANIZATION

Cluster analysis differentiates high and low community functioning in schizophrenia: Subgroups differ on working memory but not other neurocognitive domains.

PubMed

Alden, Eva C; Cobia, Derin J; Reilly, James L; Smith, Matthew J

2015-10-01

Schizophrenia is characterized by impairment in multiple aspects of community functioning. Available literature suggests that community functioning may be enhanced through cognitive remediation, however, evidence is limited regarding whether specific neurocognitive domains may be treatment targets. We characterized schizophrenia subjects based on their level of community functioning through cluster analysis in an effort to identify whether specific neurocognitive domains were associated with variation in functioning. Schizophrenia (SCZ, n=60) and control (CON, n=45) subjects completed a functional capacity task, social competence role-play, functional attainment interview, and a neuropsychological battery. Multiple cluster analytic techniques were used on the measures of functioning in the schizophrenia subjects to generate functionally-defined subgroups. MANOVA evaluated between-group differences in neurocognition. The cluster analysis revealed two distinct groups, consisting of 36 SCZ characterized by high levels of community functioning (HF-SCZ) and 24 SCZ with low levels of community functioning (LF-SCZ). There was a main group effect for neurocognitive performance (p<0.001) with CON outperforming both SCZ groups in all neurocognitive domains. Post-hoc tests revealed that HF-SCZ had higher verbal working memory compared to LF-SCZ (p≤0.05, Cohen's d=0.78) but the two groups did not differ in remaining domains. The cluster analysis classified schizophrenia subjects in HF-SCZ and LF-SCZ using a multidimensional assessment of community functioning. Moreover, HF-SCZ demonstrated rather preserved verbal working memory relative to LF-SCZ. The results suggest that verbal working memory may play a critical role in community functioning, and is a potential cognitive treatment target for schizophrenia subjects. Copyright © 2015 Elsevier B.V. All rights reserved.

A Comparative Study of Definitions on Limit and Continuity of Functions

ERIC Educational Resources Information Center

Shipman, Barbara A.

2012-01-01

Differences in definitions of limit and continuity of functions as treated in courses on calculus and in rigorous undergraduate analysis yield contradictory outcomes and unexpected language. There are results about limits in calculus that are false by the definitions of analysis, functions not continuous by one definition and continuous by…

A Naturalistic Study of Executive Function and Mathematical Problem-Solving

ERIC Educational Resources Information Center

Kotsopoulos, Donna; Lee, Joanne

2012-01-01

Our goal in this research was to understand the specific challenges middle-school students face when engaging in mathematical problem-solving by using executive function (i.e., shifting, updating, and inhibiting) of working memory as a functional construct for the analysis. Using modified talk-aloud protocols, real-time naturalistic analysis of…

Functional Analysis of Episodic Self-Injury Correlated with Recurrent Otitis Media.

ERIC Educational Resources Information Center

O'Reilly, Mark F.

1997-01-01

A functional analysis examined the consequences that maintained episodic self-injury and the relationship between those consequences and otitis media for a 26-month-old child with developmental disabilities. Results indicated that self-injury occurred only during periods of otitis media and may have served as a sensory escape function. (Author/CR)

Functional Analysis of All Salmonid Genomes (FAASG): an international initiative supporting future salmonid research, conservation and aquaculture

USDA-ARS?s Scientific Manuscript database

We describe an emerging initiative - the 'Functional Analysis of All Salmonid Genomes' (FAASG), which will leverage the extensive trait diversity that has evolved since a whole genome duplication event in the salmonid ancestor, to develop an integrative understanding of the functional genomic basis ...

Brief Functional Analysis and Supplemental Feeding for Postmeal Rumination in Children with Developmental Disabilities

ERIC Educational Resources Information Center

Lyons, Elizabeth A.; Rue, Hanna C.; Luiselli, James K.; DiGennaro, Florence D.

2007-01-01

Rumination is a serious problem demonstrated by some people with developmental disabilities, but previous research has not included a functional analysis and has rarely compared intervention methods during the assessment process. We conducted functional analyses with 2 children who displayed postmeal rumination and subsequently evaluated a…

A Functional Analysis of Gestural Behaviors Emitted by Young Children with Severe Developmental Disabilities

ERIC Educational Resources Information Center

Ferreri, Summer J.; Plavnick, Joshua B.

2011-01-01

Many children with severe developmental disabilities emit idiosyncratic gestures that may function as verbal operants (Sigafoos et al., 2000). This study examined the effectiveness of a functional analysis methodology to identify the variables responsible for gestures emitted by 2 young children with severe developmental disabilities. Potential…

Republication of "Functional Analysis of Classroom Variables for Students with Emotional and Behavioral Disorders"

ERIC Educational Resources Information Center

Dunlap, Glen; Kern, Lee; dePerczel, Maria; Clarke, Shelley; Wilson, Diane; Childs, Karen E.; White, Ronnie; Falk, George D.

2018-01-01

Functional assessment and functional analysis are processes that have been applied successfully in work with people who have developmental disabilities, but they have been used rarely with students who experience emotional or behavioral disorders. In the present study, five students in elementary school programs for severe emotional disturbance…

Alternations of functional connectivity in amblyopia patients: a resting-state fMRI study

NASA Astrophysics Data System (ADS)

Wang, Jieqiong; Hu, Ling; Li, Wenjing; Xian, Junfang; Ai, Likun; He, Huiguang

2014-03-01

Amblyopia is a common yet hard-to-cure disease in children and results in poor or blurred vision. Some efforts such as voxel-based analysis, cortical thickness analysis have been tried to reveal the pathogenesis of amblyopia. However, few studies focused on alterations of the functional connectivity (FC) in amblyopia. In this study, we analyzed the abnormalities of amblyopia patients by both the seed-based FC with the left/right primary visual cortex and the network constructed throughout the whole brain. Experiments showed the following results: (1)As for the seed-based FC analysis, FC between superior occipital gyrus and the primary visual cortex was found to significantly decrease in both sides. The abnormalities were also found in lingual gyrus. The results may reflect functional deficits both in dorsal stream and ventral stream. (2)Two increased functional connectivities and 64 decreased functional connectivities were found in the whole brain network analysis. The decreased functional connectivities most concentrate in the temporal cortex. The results suggest that amblyopia may be caused by the deficits in the visual information transmission.

A Guided Tour of Mathematical Methods for the Physical Sciences

NASA Astrophysics Data System (ADS)

Snieder, Roel; van Wijk, Kasper

2015-05-01

1. Introduction; 2. Dimensional analysis; 3. Power series; 4. Spherical and cylindrical coordinates; 5. Gradient; 6. Divergence of a vector field; 7. Curl of a vector field; 8. Theorem of Gauss; 9. Theorem of Stokes; 10. The Laplacian; 11. Scale analysis; 12. Linear algebra; 13. Dirac delta function; 14. Fourier analysis; 15. Analytic functions; 16. Complex integration; 17. Green's functions: principles; 18. Green's functions: examples; 19. Normal modes; 20. Potential-field theory; 21. Probability and statistics; 22. Inverse problems; 23. Perturbation theory; 24. Asymptotic evaluation of integrals; 25. Conservation laws; 26. Cartesian tensors; 27. Variational calculus; 28. Epilogue on power and knowledge.

Functional materials analysis using in situ and in operando X-ray and neutron scattering

PubMed Central

Peterson, Vanessa K.; Papadakis, Christine M.

2015-01-01

In situ and in operando studies are commonplace and necessary in functional materials research. This review highlights recent developments in the analysis of functional materials using state-of-the-art in situ and in operando X-ray and neutron scattering and analysis. Examples are given covering a number of important materials areas, alongside a description of the types of information that can be obtained and the experimental setups used to acquire them. PMID:25866665

A Rasch-validated version of the upper extremity functional index for interval-level measurement of upper extremity function.

PubMed

Hamilton, Clayon B; Chesworth, Bert M

2013-11-01

The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0-100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal disorders of the upper extremity.

A Rasch-Validated Version of the Upper Extremity Functional Index for Interval-Level Measurement of Upper Extremity Function

PubMed Central

Chesworth, Bert M.

2013-01-01

Background The original 20-item Upper Extremity Functional Index (UEFI) has not undergone Rasch validation. Objective The purpose of this study was to determine whether Rasch analysis supports the UEFI as a measure of a single construct (ie, upper extremity function) and whether a Rasch-validated UEFI has adequate reproducibility for individual-level patient evaluation. Design This was a secondary analysis of data from a repeated-measures study designed to evaluate the measurement properties of the UEFI over a 3-week period. Methods Patients (n=239) with musculoskeletal upper extremity disorders were recruited from 17 physical therapy clinics across 4 Canadian provinces. Rasch analysis of the UEFI measurement properties was performed. If the UEFI did not fit the Rasch model, misfitting patients were deleted, items with poor response structure were corrected, and misfitting items and redundant items were deleted. The impact of differential item functioning on the ability estimate of patients was investigated. Results A 15-item modified UEFI was derived to achieve fit to the Rasch model where the total score was supported as a measure of upper extremity function only. The resultant UEFI-15 interval-level scale (0–100, worst to best state) demonstrated excellent internal consistency (person separation index=0.94) and test-retest reliability (intraclass correlation coefficient [2,1]=.95). The minimal detectable change at the 90% confidence interval was 8.1. Limitations Patients who were ambidextrous or bilaterally affected were excluded to allow for the analysis of differential item functioning due to limb involvement and arm dominance. Conclusion Rasch analysis did not support the validity of the 20-item UEFI. However, the UEFI-15 was a valid and reliable interval-level measure of a single dimension: upper extremity function. Rasch analysis supports using the UEFI-15 in physical therapist practice to quantify upper extremity function in patients with musculoskeletal disorders of the upper extremity. PMID:23813086

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Functional Evolution of PLP-dependent Enzymes based on Active-Site Structural Similarities

PubMed Central

Catazaro, Jonathan; Caprez, Adam; Guru, Ashu; Swanson, David; Powers, Robert

2014-01-01

Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5’-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the Comparison of Protein Active Site Structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can be used to infer evolutionary relationships based on functional similarity. The enzymes successfully clustered together based on substrate specificity, function, and three-dimensional fold. This study demonstrates the value of using active site structures for functional evolutionary analysis and the effectiveness of CPASS. PMID:24920327

Functional evolution of PLP-dependent enzymes based on active-site structural similarities.

PubMed

Catazaro, Jonathan; Caprez, Adam; Guru, Ashu; Swanson, David; Powers, Robert

2014-10-01

Families of distantly related proteins typically have very low sequence identity, which hinders evolutionary analysis and functional annotation. Slowly evolving features of proteins, such as an active site, are therefore valuable for annotating putative and distantly related proteins. To date, a complete evolutionary analysis of the functional relationship of an entire enzyme family based on active-site structural similarities has not yet been undertaken. Pyridoxal-5'-phosphate (PLP) dependent enzymes are primordial enzymes that diversified in the last universal ancestor. Using the comparison of protein active site structures (CPASS) software and database, we show that the active site structures of PLP-dependent enzymes can be used to infer evolutionary relationships based on functional similarity. The enzymes successfully clustered together based on substrate specificity, function, and three-dimensional-fold. This study demonstrates the value of using active site structures for functional evolutionary analysis and the effectiveness of CPASS. © 2014 Wiley Periodicals, Inc.

Characterizing Bonding Patterns in Diradicals and Triradicals by Density-Based Wave Function Analysis: A Uniform Approach.

PubMed

Orms, Natalie; Rehn, Dirk R; Dreuw, Andreas; Krylov, Anna I

2018-02-13

Density-based wave function analysis enables unambiguous comparisons of the electronic structure computed by different methods and removes ambiguity of orbital choices. We use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high- and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such as polyradicals. We show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of the bonding pattern.

Functional Regression Models for Epistasis Analysis of Multiple Quantitative Traits.

PubMed

Zhang, Futao; Xie, Dan; Liang, Meimei; Xiong, Momiao

2016-04-01

To date, most genetic analyses of phenotypes have focused on analyzing single traits or analyzing each phenotype independently. However, joint epistasis analysis of multiple complementary traits will increase statistical power and improve our understanding of the complicated genetic structure of the complex diseases. Despite their importance in uncovering the genetic structure of complex traits, the statistical methods for identifying epistasis in multiple phenotypes remains fundamentally unexplored. To fill this gap, we formulate a test for interaction between two genes in multiple quantitative trait analysis as a multiple functional regression (MFRG) in which the genotype functions (genetic variant profiles) are defined as a function of the genomic position of the genetic variants. We use large-scale simulations to calculate Type I error rates for testing interaction between two genes with multiple phenotypes and to compare the power with multivariate pairwise interaction analysis and single trait interaction analysis by a single variate functional regression model. To further evaluate performance, the MFRG for epistasis analysis is applied to five phenotypes of exome sequence data from the NHLBI's Exome Sequencing Project (ESP) to detect pleiotropic epistasis. A total of 267 pairs of genes that formed a genetic interaction network showed significant evidence of epistasis influencing five traits. The results demonstrate that the joint interaction analysis of multiple phenotypes has a much higher power to detect interaction than the interaction analysis of a single trait and may open a new direction to fully uncovering the genetic structure of multiple phenotypes.

Effects of Body Mass Index on Lung Function Index of Chinese Population

NASA Astrophysics Data System (ADS)

Guo, Qiao; Ye, Jun; Yang, Jian; Zhu, Changan; Sheng, Lei; Zhang, Yongliang

2018-01-01

To study the effect of body mass index (BMI) on lung function indexes in Chinese population. A cross-sectional study was performed on 10, 592 participants. The linear relationship between lung function and BMI was evaluated by multivariate linear regression analysis, and the correlation between BMI and lung function was assessed by Pearson correlation analysis. Correlation analysis showed that BMI was positively related with the decreasing of forced vital capacity (FVC), forced expiratory volume in one second (FEV1) and FEV1/FVC (P <0.05), the increasing of FVC% predicted value (FVC%pre) and FEV1% predicted value (FEV1%pre). These suggested that Chinese people can restrain the decline of lung function to prevent the occurrence and development of COPD by the control of BMI.

Pan-Cancer Analysis of Mutation Hotspots in Protein Domains.

PubMed

Miller, Martin L; Reznik, Ed; Gauthier, Nicholas P; Aksoy, Bülent Arman; Korkut, Anil; Gao, Jianjiong; Ciriello, Giovanni; Schultz, Nikolaus; Sander, Chris

2015-09-23

In cancer genomics, recurrence of mutations in independent tumor samples is a strong indicator of functional impact. However, rare functional mutations can escape detection by recurrence analysis owing to lack of statistical power. We enhance statistical power by extending the notion of recurrence of mutations from single genes to gene families that share homologous protein domains. Domain mutation analysis also sharpens the functional interpretation of the impact of mutations, as domains more succinctly embody function than entire genes. By mapping mutations in 22 different tumor types to equivalent positions in multiple sequence alignments of domains, we confirm well-known functional mutation hotspots, identify uncharacterized rare variants in one gene that are equivalent to well-characterized mutations in another gene, detect previously unknown mutation hotspots, and provide hypotheses about molecular mechanisms and downstream effects of domain mutations. With the rapid expansion of cancer genomics projects, protein domain hotspot analysis will likely provide many more leads linking mutations in proteins to the cancer phenotype. Copyright © 2015 Elsevier Inc. All rights reserved.

Using Multicriteria Analysis in Issues Concerning Adaptation of Historic Facilities for the Needs of Public Utility Buildings with a Function of a Theatre

NASA Astrophysics Data System (ADS)

Obracaj, Piotr; Fabianowski, Dariusz

2017-10-01

Implementations concerning adaptation of historic facilities for public utility objects are associated with the necessity of solving many complex, often conflicting expectations of future users. This mainly concerns the function that includes construction, technology and aesthetic issues. The list of issues is completed with proper protection of historic values, different in each case. The procedure leading to obtaining the expected solution is a multicriteria procedure, usually difficult to accurately define and requiring designer’s large experience. An innovative approach has been used for the analysis, namely - the modified EA FAHP (Extent Analysis Fuzzy Analytic Hierarchy Process) Chang’s method of a multicriteria analysis for the assessment of complex functional and spatial issues. Selection of optimal spatial form of an adapted historic building intended for the multi-functional public utility facility was analysed. The assumed functional flexibility was determined in the scope of: education, conference, and chamber spectacles, such as drama, concerts, in different stage-audience layouts.

An analysis of the functioning of mental healthcare in northwestern Poland.

PubMed

Bażydło, Marta; Karakiewicz, Beata

Modern psychiatry faces numerous challenges related with the change of the epidemiology of mental disorders and the development of knowledge in this area of science. An answer to this situation is to be the introduction of community psychiatry. The implementation of this model in Poland was the aim of the National Mental Health Protection Programme. The aim of the study was to analyse the functioning of mental healthcare using the example of the West Pomeranian Province in Poland. The analysis relied on a qualitative method. Three group interviews in an interdisciplinary advisory panel were conducted. People representing various areas acting for people with mental disorders participated in each meeting. Based on the conclusions that were drawn, PEST and SWOT analyses of functioning of mental healthcare were performed. Within the analysis of the macro-environment of mental healthcare, the influence of the following factors was evaluated through PEST analysis: political and legal, economic, socio-cultural, and technological. All of these factors were assessed as negative for the functioning of mental healthcare. Then, a SWOT analysis was performed to indicate the strengths, weaknesses, opportunities, and threats in the functioning of mental healthcare. 1. Mental healthcare is more influenced by external factors than by internal factors. 2. Macro-environmental factors influence the functioning of mental healthcare in a significantly negative manner. 3. The basic problem in the functioning of mental healthcare is insufficient funding. 4. In order to improve the functioning of mental healthcare, it is necessary to change the funding methods, regulations, the way society perceives mental disorders, and the system of monitoring mental healthcare services.

Assignment of functional activations to probabilistic cytoarchitectonic areas revisited.

PubMed

Eickhoff, Simon B; Paus, Tomas; Caspers, Svenja; Grosbras, Marie-Helene; Evans, Alan C; Zilles, Karl; Amunts, Katrin

2007-07-01

Probabilistic cytoarchitectonic maps in standard reference space provide a powerful tool for the analysis of structure-function relationships in the human brain. While these microstructurally defined maps have already been successfully used in the analysis of somatosensory, motor or language functions, several conceptual issues in the analysis of structure-function relationships still demand further clarification. In this paper, we demonstrate the principle approaches for anatomical localisation of functional activations based on probabilistic cytoarchitectonic maps by exemplary analysis of an anterior parietal activation evoked by visual presentation of hand gestures. After consideration of the conceptual basis and implementation of volume or local maxima labelling, we comment on some potential interpretational difficulties, limitations and caveats that could be encountered. Extending and supplementing these methods, we then propose a supplementary approach for quantification of structure-function correspondences based on distribution analysis. This approach relates the cytoarchitectonic probabilities observed at a particular functionally defined location to the areal specific null distribution of probabilities across the whole brain (i.e., the full probability map). Importantly, this method avoids the need for a unique classification of voxels to a single cortical area and may increase the comparability between results obtained for different areas. Moreover, as distribution-based labelling quantifies the "central tendency" of an activation with respect to anatomical areas, it will, in combination with the established methods, allow an advanced characterisation of the anatomical substrates of functional activations. Finally, the advantages and disadvantages of the various methods are discussed, focussing on the question of which approach is most appropriate for a particular situation.

Rasch analysis of the Italian Lower Extremity Functional Scale: insights on dimensionality and suggestions for an improved 15-item version.

PubMed

Bravini, Elisabetta; Giordano, Andrea; Sartorio, Francesco; Ferriero, Giorgio; Vercelli, Stefano

2017-04-01

To investigate dimensionality and the measurement properties of the Italian Lower Extremity Functional Scale using both classical test theory and Rasch analysis methods, and to provide insights for an improved version of the questionnaire. Rasch analysis of individual patient data. Rehabilitation centre. A total of 135 patients with musculoskeletal diseases of the lower limb. Patients were assessed with the Lower Extremity Functional Scale before and after the rehabilitation. Rasch analysis showed some problems related to rating scale category functioning, items fit, and items redundancy. After an iterative process, which resulted in the reduction of rating scale categories from 5 to 4, and in the deletion of 5 items, the psychometric properties of the Italian Lower Extremity Functional Scale improved. The retained 15 items with a 4-level response format fitted the Rasch model (internal construct validity), and demonstrated unidimensionality and good reliability indices (person-separation reliability 0.92; Cronbach's alpha 0.94). Then, the analysis showed differential item functioning for six of the retained items. The sensitivity to change of the Italian 15-item Lower Extremity Functional Scale was nearly equal to the one of the original version (effect size: 0.93 and 0.98; standardized response mean: 1.20 and 1.28, respectively for the 15-item and 20-item versions). The Italian Lower Extremity Functional Scale had unsatisfactory measurement properties. However, removing five items and simplifying the scoring from 5 to 4 levels resulted in a more valid measure with good reliability and sensitivity to change.

A Unified Approach to Functional Principal Component Analysis and Functional Multiple-Set Canonical Correlation.

PubMed

Choi, Ji Yeh; Hwang, Heungsun; Yamamoto, Michio; Jung, Kwanghee; Woodward, Todd S

2017-06-01

Functional principal component analysis (FPCA) and functional multiple-set canonical correlation analysis (FMCCA) are data reduction techniques for functional data that are collected in the form of smooth curves or functions over a continuum such as time or space. In FPCA, low-dimensional components are extracted from a single functional dataset such that they explain the most variance of the dataset, whereas in FMCCA, low-dimensional components are obtained from each of multiple functional datasets in such a way that the associations among the components are maximized across the different sets. In this paper, we propose a unified approach to FPCA and FMCCA. The proposed approach subsumes both techniques as special cases. Furthermore, it permits a compromise between the techniques, such that components are obtained from each set of functional data to maximize their associations across different datasets, while accounting for the variance of the data well. We propose a single optimization criterion for the proposed approach, and develop an alternating regularized least squares algorithm to minimize the criterion in combination with basis function approximations to functions. We conduct a simulation study to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of multiple-subject functional magnetic resonance imaging data to obtain low-dimensional components of blood-oxygen level-dependent signal changes of the brain over time, which are highly correlated across the subjects as well as representative of the data. The extracted components are used to identify networks of neural activity that are commonly activated across the subjects while carrying out a working memory task.

Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants?

PubMed

Lovelock, Paul K; Spurdle, Amanda B; Mok, Myth T S; Farrugia, Daniel J; Lakhani, Sunil R; Healey, Sue; Arnold, Stephen; Buchanan, Daniel; Couch, Fergus J; Henderson, Beric R; Goldgar, David E; Tavtigian, Sean V; Chenevix-Trench, Georgia; Brown, Melissa A

2007-01-01

Many of the DNA sequence variants identified in the breast cancer susceptibility gene BRCA1 remain unclassified in terms of their potential pathogenicity. Both multifactorial likelihood analysis and functional approaches have been proposed as a means to elucidate likely clinical significance of such variants, but analysis of the comparative value of these methods for classifying all sequence variants has been limited. We have compared the results from multifactorial likelihood analysis with those from several functional analyses for the four BRCA1 sequence variants A1708E, G1738R, R1699Q, and A1708V. Our results show that multifactorial likelihood analysis, which incorporates sequence conservation, co-inheritance, segregation, and tumour immunohistochemical analysis, may improve classification of variants. For A1708E, previously shown to be functionally compromised, analysis of oestrogen receptor, cytokeratin 5/6, and cytokeratin 14 tumour expression data significantly strengthened the prediction of pathogenicity, giving a posterior probability of pathogenicity of 99%. For G1738R, shown to be functionally defective in this study, immunohistochemistry analysis confirmed previous findings of inconsistent 'BRCA1-like' phenotypes for the two tumours studied, and the posterior probability for this variant was 96%. The posterior probabilities of R1699Q and A1708V were 54% and 69%, respectively, only moderately suggestive of increased risk. Interestingly, results from functional analyses suggest that both of these variants have only partial functional activity. R1699Q was defective in foci formation in response to DNA damage and displayed intermediate transcriptional transactivation activity but showed no evidence for centrosome amplification. In contrast, A1708V displayed an intermediate transcriptional transactivation activity and a normal foci formation response in response to DNA damage but induced centrosome amplification. These data highlight the need for a range of functional studies to be performed in order to identify variants with partially compromised function. The results also raise the possibility that A1708V and R1699Q may be associated with a low or moderate risk of cancer. While data pooling strategies may provide more information for multifactorial analysis to improve the interpretation of the clinical significance of these variants, it is likely that the development of current multifactorial likelihood approaches and the consideration of alternative statistical approaches will be needed to determine whether these individually rare variants do confer a low or moderate risk of breast cancer.

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function

PubMed Central

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D.

2009-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings. PMID:19834575

A Parallel Independent Component Analysis Approach to Investigate Genomic Influence on Brain Function.

PubMed

Liu, Jingyu; Demirci, Oguz; Calhoun, Vince D

2008-01-01

Relationships between genomic data and functional brain images are of great interest but require new analysis approaches to integrate the high-dimensional data types. This letter presents an extension of a technique called parallel independent component analysis (paraICA), which enables the joint analysis of multiple modalities including interconnections between them. We extend our earlier work by allowing for multiple interconnections and by providing important overfitting controls. Performance was assessed by simulations under different conditions, and indicated reliable results can be extracted by properly balancing overfitting and underfitting. An application to functional magnetic resonance images and single nucleotide polymorphism array produced interesting findings.

Exploring Relationship between Students' Questioning Behaviors and Inquiry Tasks in an Online Forum through Analysis of Ideational Function of Questions

ERIC Educational Resources Information Center

Tan, Seng-Chee; Seah, Lay-Hoon

2011-01-01

In this study we explored questioning behaviors among elementary students engaging in inquiry science using the "Knowledge Forum", a computer-supported collaborative learning tool. Adapting the theory of systemic functional linguistics, we developed the Ideational Function of Question (IFQ) analytical framework by means of inductive analysis of…

The Limits of Functional Analysis in the Study of Mass Communication.

ERIC Educational Resources Information Center

Anderson, James A.; Meyer, Timothy P.

The fundamental limits of the functional approach to the study of mass communication are embodied in two of its criticisms. The first weakness is in its logical structure and the second involves the limits that are set by known methods. Functional analysis has difficulties as a meaningful research perspective because the process of mass…

Training Head Start Teachers to Conduct Trial-Based Functional Analysis of Challenging Behavior

ERIC Educational Resources Information Center

Rispoli, Mandy; Burke, Mack D.; Hatton, Heather; Ninci, Jennifer; Zaini, Samar; Sanchez, Lisa

2015-01-01

Trial-based functional analysis (TBFA) is a procedure for experimentally identifying the function of challenging behavior within applied settings. The purpose of this study was to examine the effects of a TBFA teacher-training package in the context of two Head Start centers implementing programwide positive behavior support (PWPBS). Four Head…

Tag Questions across Irish English and British English: A Corpus Analysis of Form and Function

ERIC Educational Resources Information Center

Barron, Anne; Pandarova, Irina; Muderack, Karoline

2015-01-01

The present study, situated in the area of variational pragmatics, contrasts tag question (TQ) use in Ireland and Great Britain using spoken data from the Irish and British components of the International Corpus of English (ICE). Analysis is on the formal and functional level and also investigates form-functional relationships. Findings reveal…

Tuning Energetic Material Reactivity Using Surface Functionalization of Aluminum Fuels

DTIC Science & Technology

2012-10-30

analysis of three different thermites consisting of aluminum (Al) particles with and without surface functionalization combined with molybdenum...of thermites , aluminum synthesis, aluminum fluoropolymer combustion, acid coatings Keerti S. Kappagantula, Cory Farley, Michelle L. Pantoya, Jillian...Reactivity Using Surface Functionalization of Aluminum Fuels Report Title ABSTRACT Combustion analysis of three different thermites consisting of aluminum (Al

Training Public School Special Educators to Implement Two Functional Analysis Models

ERIC Educational Resources Information Center

Rispoli, Mandy; Neely, Leslie; Healy, Olive; Gregori, Emily

2016-01-01

The purpose of this study was to investigate the efficacy and efficiency of a training package to teach public school special educators to conduct functional analyses of challenging behavior. Six public school educators were divided into two cohorts of three and were taught two models of functional analysis of challenging behavior: traditional and…

An Example of an Elementary School Paraprofessional-Implemented Functional Analysis and Intervention

ERIC Educational Resources Information Center

Bessette, Kimberly K.; Wills, Howard P.

2007-01-01

The Individuals With Disabilities Education Act mandates the performance of functional assessment for students with severe behavior problems. A functional analysis can be one part of this process but its use has been minimal. This study evaluates whether a paraprofessional could (a) be trained to correctly perform 3 conditions of a functional…

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

[Range of Hip Joint Motion and Weight of Lower Limb Function under 3D Dynamic Marker].

PubMed

Xia, Q; Zhang, M; Gao, D; Xia, W T

2017-12-01

To explore the range of reasonable weight coefficient of hip joint in lower limb function. When the hip joints of healthy volunteers under normal conditions or fixed at three different positions including functional, flexed and extension positions, the movements of lower limbs were recorded by LUKOtronic motion capture and analysis system. The degree of lower limb function loss was calculated using Fugl-Meyer lower limb function assessment form when the hip joints were fixed at the aforementioned positions. One-way analysis of variance and Tamhane's T2 method were used to proceed statistics analysis and calculate the range of reasonable weight coefficient of hip joint. There were significant differences between the degree of lower limb function loss when the hip joints fixed at flexed and extension positions and at functional position. While the differences between the degree of lower limb function loss when the hip joints fixed at flexed position and extension position had no statistical significance. In 95% confidence interval, the reasonable weight coefficient of hip joint in lower limb function was between 61.05% and 73.34%. Expect confirming the reasonable weight coefficient, the effects of functional and non-functional positions on the degree of lower limb function loss should also be considered for the assessment of hip joint function loss. Copyright© by the Editorial Department of Journal of Forensic Medicine

Functional sequencing read annotation for high precision microbiome analysis

PubMed Central

Zhu, Chengsheng; Miller, Maximilian; Marpaka, Srinayani; Vaysberg, Pavel; Rühlemann, Malte C; Wu, Guojun; Heinsen, Femke-Anouska; Tempel, Marie; Zhao, Liping; Lieb, Wolfgang; Franke, Andre; Bromberg, Yana

2018-01-01

Abstract The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it. PMID:29194524

Functional Evolution of a cis-Regulatory Module

PubMed Central

Palsson, Arnar; Alekseeva, Elena; Bergman, Casey M; Nathan, Janaki; Kreitman, Martin

2005-01-01

Lack of knowledge about how regulatory regions evolve in relation to their structure–function may limit the utility of comparative sequence analysis in deciphering cis-regulatory sequences. To address this we applied reverse genetics to carry out a functional genetic complementation analysis of a eukaryotic cis-regulatory module—the even-skipped stripe 2 enhancer—from four Drosophila species. The evolution of this enhancer is non-clock-like, with important functional differences between closely related species and functional convergence between distantly related species. Functional divergence is attributable to differences in activation levels rather than spatiotemporal control of gene expression. Our findings have implications for understanding enhancer structure–function, mechanisms of speciation and computational identification of regulatory modules. PMID:15757364

Multidimensional Functional Behaviour Assessment within a Problem Analysis Framework.

ERIC Educational Resources Information Center

Ryba, Ken; Annan, Jean

This paper presents a new approach to contextualized problem analysis developed for use with multimodal Functional Behaviour Assessment (FBA) at Massey University in Auckland, New Zealand. The aim of problem analysis is to simplify complex problems that are difficult to understand. It accomplishes this by providing a high order framework that can…

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction.

PubMed

Abulnaga, S Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M; Onyike, Chiadi U; Ying, Sarah H; Prince, Jerry L

2016-02-27

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

NASA Astrophysics Data System (ADS)

Abulnaga, S. Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M.; Onyike, Chiadi U.; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

Skeletal effects in Angle Class II/1 patients treated with the functional regulator type II : Cephalometric and tensor analysis.

PubMed

Schulz, Simone; Koos, Bernd; Duske, Kathrin; Stahl, Franka

2016-11-01

The purpose of this work was to employ both cephalometric and tensor analysis in characterizing the skeletal changes experienced by patients with Angle Class II/1 malocclusion during functional orthodontic treatment with the functional regulator type II. A total of 23 patients with Class II/1 malocclusion based on lateral cephalograms obtained before and after treatment with the functional regulator type II were analyzed. Another 23 patients with Angle Class II/1 malocclusion who had not undergone treatment were included as controls. Our cephalometric data attest to significant therapeutic effects of the functional regulator type II on the skeletal mandibular system, including significant advancement of the mandible, increases in effective mandibular length with enhancement of the chin profile, and reduction of growth-related bite deepening. No treatment-related effects were observed at the cranial-base and midface levels. In addition, tensor analysis revealed significant stimulation of mandibular growth in sagittal directions, without indications of growth effects on the maxilla. Its growth-pattern findings differed from those of cephalometric analysis by indicating that the appliance did promote horizontal development, which supports the functional orthodontic treatment effect in Angle Class II/1 cases. Tensor analysis yielded additional insights into sagittal and vertical growth changes not identifiable by strictly cephalometric means. The functional regulator type II was an effective treatment modality for Angle Class II/1 malocclusion and influenced the skeletal development of these patients in favorable ways.

Functional Data Analysis in NTCP Modeling: A New Method to Explore the Radiation Dose-Volume Effects

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

Benadjaoud, Mohamed Amine, E-mail: mohamedamine.benadjaoud@gustaveroussy.fr; Université Paris sud, Le Kremlin-Bicêtre; Institut Gustave Roussy, Villejuif

2014-11-01

Purpose/Objective(s): To describe a novel method to explore radiation dose-volume effects. Functional data analysis is used to investigate the information contained in differential dose-volume histograms. The method is applied to the normal tissue complication probability modeling of rectal bleeding (RB) for patients irradiated in the prostatic bed by 3-dimensional conformal radiation therapy. Methods and Materials: Kernel density estimation was used to estimate the individual probability density functions from each of the 141 rectum differential dose-volume histograms. Functional principal component analysis was performed on the estimated probability density functions to explore the variation modes in the dose distribution. The functional principalmore » components were then tested for association with RB using logistic regression adapted to functional covariates (FLR). For comparison, 3 other normal tissue complication probability models were considered: the Lyman-Kutcher-Burman model, logistic model based on standard dosimetric parameters (LM), and logistic model based on multivariate principal component analysis (PCA). Results: The incidence rate of grade ≥2 RB was 14%. V{sub 65Gy} was the most predictive factor for the LM (P=.058). The best fit for the Lyman-Kutcher-Burman model was obtained with n=0.12, m = 0.17, and TD50 = 72.6 Gy. In PCA and FLR, the components that describe the interdependence between the relative volumes exposed at intermediate and high doses were the most correlated to the complication. The FLR parameter function leads to a better understanding of the volume effect by including the treatment specificity in the delivered mechanistic information. For RB grade ≥2, patients with advanced age are significantly at risk (odds ratio, 1.123; 95% confidence interval, 1.03-1.22), and the fits of the LM, PCA, and functional principal component analysis models are significantly improved by including this clinical factor. Conclusion: Functional data analysis provides an attractive method for flexibly estimating the dose-volume effect for normal tissues in external radiation therapy.« less

Mission analysis for cross-site transfer

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

Riesenweber, S.D.; Fritz, R.L.; Shipley, L.E.

1995-11-01

The Mission Analysis Report describes the requirements and constraints associated with the Transfer Waste Function as necessary to support the Manage Tank Waste, Retrieve Waste, and Process Tank Waste Functions described in WHC-SD-WM-FRD-020, Tank Waste Remediation System (TWRS) Functions and Requirements Document and DOE/RL-92-60, Revision 1, TWRS Functions and Requirements Document, March 1994. It further assesses the ability of the ``initial state`` (or current cross-site transfer system) to meet the requirements and constraints.

Functional Group Analysis for Diesel-like Mixing-Controlled Compression Ignition Combustion Blendstocks

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

Gaspar, Daniel J.; McCormick, Robert L.; Polikarpov, Evgueni

This report addresses the suitability of hydrocarbon and oxygenate functional groups for use as a diesel-like fuel blending component in an advanced, mixing-controlled, compression ignition combustion engine. The functional groups are chosen from those that could be derived from a biomass feedstock, and represent a full range of chemistries. This first systematic analysis of functional groups will be of value to all who are pursuing new bio-blendstocks for diesel-like fuels.

Cognitive and physical functions related to the level of supervision and dependence in the toileting of stroke patients.

PubMed

Sato, Atsushi; Okuda, Yutaka; Fujita, Takaaki; Kimura, Norihiko; Hoshina, Noriyuki; Kato, Sayaka; Tanaka, Shigenari

2016-01-01

This study aimed to clarify which cognitive and physical factors are associated with the need for toileting assistance in stroke patients and to calculate cut-off values for discriminating between independent supervision and dependent toileting ability. This cross-sectional study included 163 first-stroke patients in nine convalescent rehabilitation wards. Based on their FIM Ⓡ instrument score for toileting, the patients were divided into an independent-supervision group and a dependent group. Multiple logistic regression analysis and receiver operating characteristic analysis were performed to identify factors related to toileting performance. The Minimental State Examination (MMSE); the Stroke Impairment Assessment Set (SIAS) score for the affected lower limb, speech, and visuospatial functions; and the Functional Assessment for Control of Trunk (FACT) were analyzed as independent variables. The multiple logistic regression analysis showed that the FIM Ⓡ instrument score for toileting was associated with the SIAS score for the affected lower limb function, MMSE, and FACT. On receiver operating characteristic analysis, the SIAS score for the affected lower limb function cut-off value was 8/7 points, the MMSE cut-off value was 25/24 points, and the FACT cut-off value was 14/13 points. Affected lower limb function, cognitive function, and trunk function were related with the need for toileting assistance. These cut-off values may be useful for judging whether toileting assistance is needed in stroke patients.

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

ReSeqTools: an integrated toolkit for large-scale next-generation sequencing based resequencing analysis.

PubMed

He, W; Zhao, S; Liu, X; Dong, S; Lv, J; Liu, D; Wang, J; Meng, Z

2013-12-04

Large-scale next-generation sequencing (NGS)-based resequencing detects sequence variations, constructs evolutionary histories, and identifies phenotype-related genotypes. However, NGS-based resequencing studies generate extraordinarily large amounts of data, making computations difficult. Effective use and analysis of these data for NGS-based resequencing studies remains a difficult task for individual researchers. Here, we introduce ReSeqTools, a full-featured toolkit for NGS (Illumina sequencing)-based resequencing analysis, which processes raw data, interprets mapping results, and identifies and annotates sequence variations. ReSeqTools provides abundant scalable functions for routine resequencing analysis in different modules to facilitate customization of the analysis pipeline. ReSeqTools is designed to use compressed data files as input or output to save storage space and facilitates faster and more computationally efficient large-scale resequencing studies in a user-friendly manner. It offers abundant practical functions and generates useful statistics during the analysis pipeline, which significantly simplifies resequencing analysis. Its integrated algorithms and abundant sub-functions provide a solid foundation for special demands in resequencing projects. Users can combine these functions to construct their own pipelines for other purposes.

Network analysis of mesoscale optical recordings to assess regional, functional connectivity.

PubMed

Lim, Diana H; LeDue, Jeffrey M; Murphy, Timothy H

2015-10-01

With modern optical imaging methods, it is possible to map structural and functional connectivity. Optical imaging studies that aim to describe large-scale neural connectivity often need to handle large and complex datasets. In order to interpret these datasets, new methods for analyzing structural and functional connectivity are being developed. Recently, network analysis, based on graph theory, has been used to describe and quantify brain connectivity in both experimental and clinical studies. We outline how to apply regional, functional network analysis to mesoscale optical imaging using voltage-sensitive-dye imaging and channelrhodopsin-2 stimulation in a mouse model. We include links to sample datasets and an analysis script. The analyses we employ can be applied to other types of fluorescence wide-field imaging, including genetically encoded calcium indicators, to assess network properties. We discuss the benefits and limitations of using network analysis for interpreting optical imaging data and define network properties that may be used to compare across preparations or other manipulations such as animal models of disease.

Gene context analysis in the Integrated Microbial Genomes (IMG) data management system.

PubMed

Mavromatis, Konstantinos; Chu, Ken; Ivanova, Natalia; Hooper, Sean D; Markowitz, Victor M; Kyrpides, Nikos C

2009-11-24

Computational methods for determining the function of genes in newly sequenced genomes have been traditionally based on sequence similarity to genes whose function has been identified experimentally. Function prediction methods can be extended using gene context analysis approaches such as examining the conservation of chromosomal gene clusters, gene fusion events and co-occurrence profiles across genomes. Context analysis is based on the observation that functionally related genes are often having similar gene context and relies on the identification of such events across phylogenetically diverse collection of genomes. We have used the data management system of the Integrated Microbial Genomes (IMG) as the framework to implement and explore the power of gene context analysis methods because it provides one of the largest available genome integrations. Visualization and search tools to facilitate gene context analysis have been developed and applied across all publicly available archaeal and bacterial genomes in IMG. These computations are now maintained as part of IMG's regular genome content update cycle. IMG is available at: http://img.jgi.doe.gov.

Transfer function characteristics of super resolving systems

NASA Technical Reports Server (NTRS)

Milster, Tom D.; Curtis, Craig H.

1992-01-01

Signal quality in an optical storage device greatly depends on the optical system transfer function used to write and read data patterns. The problem is similar to analysis of scanning optical microscopes. Hopkins and Braat have analyzed write-once-read-many (WORM) optical data storage devices. Herein, transfer function analysis of magnetooptic (MO) data storage devices is discussed with respect to improving transfer-function characteristics. Several authors have described improving the transfer function as super resolution. However, none have thoroughly analyzed the MO optical system and effects of the medium. Both the optical system transfer function and effects of the medium of this development are discussed.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

atBioNet--an integrated network analysis tool for genomics and biomarker discovery.

PubMed

Ding, Yijun; Chen, Minjun; Liu, Zhichao; Ding, Don; Ye, Yanbin; Zhang, Min; Kelly, Reagan; Guo, Li; Su, Zhenqiang; Harris, Stephen C; Qian, Feng; Ge, Weigong; Fang, Hong; Xu, Xiaowei; Tong, Weida

2012-07-20

Large amounts of mammalian protein-protein interaction (PPI) data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks). The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http://www.fda.gov/ScienceResearch/BioinformaticsTools/ucm285284.htm.

A new feedback image encryption scheme based on perturbation with dynamical compound chaotic sequence cipher generator

NASA Astrophysics Data System (ADS)

Tong, Xiaojun; Cui, Minggen; Wang, Zhu

2009-07-01

The design of the new compound two-dimensional chaotic function is presented by exploiting two one-dimensional chaotic functions which switch randomly, and the design is used as a chaotic sequence generator which is proved by Devaney's definition proof of chaos. The properties of compound chaotic functions are also proved rigorously. In order to improve the robustness against difference cryptanalysis and produce avalanche effect, a new feedback image encryption scheme is proposed using the new compound chaos by selecting one of the two one-dimensional chaotic functions randomly and a new image pixels method of permutation and substitution is designed in detail by array row and column random controlling based on the compound chaos. The results from entropy analysis, difference analysis, statistical analysis, sequence randomness analysis, cipher sensitivity analysis depending on key and plaintext have proven that the compound chaotic sequence cipher can resist cryptanalytic, statistical and brute-force attacks, and especially it accelerates encryption speed, and achieves higher level of security. By the dynamical compound chaos and perturbation technology, the paper solves the problem of computer low precision of one-dimensional chaotic function.

Analysis of space vehicle structures using the transfer-function concept

NASA Technical Reports Server (NTRS)

Heer, E.; Trubert, M. R.

1969-01-01

Analysis of large complex systems is accomplished by dividing it into suitable subsystems and determining the individual dynamical and vibrational responses. Frequency transfer functions then determine the vibrational response of the whole system.

GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis.

PubMed

Zheng, Qi; Wang, Xiu-Jie

2008-07-01

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T.

PubMed

San Emeterio Nateras, Oscar; Yu, Fang; Muir, Eric R; Bazan, Carlos; Franklin, Crystal G; Li, Wei; Li, Jinqi; Lancaster, Jack L; Duong, Timothy Q

2016-04-01

To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P < .0001). The centroid coordinates across the four trials deviated by 2 in-plane voxels ± 2 mm (standard deviation) and up to one adjacent image section ± 3 mm. ICA of group resting-state functional MR imaging data revealed prominent functional connectivity patterns within the spinal cord gray matter. There were statistically significant (z score > 3, P < .001) bilateral, unilateral, and intersegmental correlations in the ventral horns, dorsal horns, and central spinal cord gray matter. Three-dimensional surface rendering provided visualization of these components along the length of the spinal cord. Seed-based analysis showed that many ICA components exhibited strong and significant (P < .05) correlations, corroborating the ICA results. Resting-state functional MR imaging connectivity networks are qualitatively consistent with known neuroanatomic and functional structures in the spinal cord. Resting-state functional MR imaging of the human cervical spinal cord with a 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

Pain, activities of daily living and sport function at different time points after hip arthroscopy in patients with femoroacetabular impingement: a systematic review with meta-analysis.

PubMed

Kierkegaard, Signe; Langeskov-Christensen, Martin; Lund, Bent; Naal, Florian D; Mechlenburg, Inger; Dalgas, Ulrik; Casartelli, Nicola C

2017-04-01

To investigate pain, activities of daily living (ADL) function, sport function, quality of life and satisfaction at different time points after hip arthroscopy in patients with femoroacetabular impingement (FAI). Systematic review with meta-analysis. Weighted mean differences between preoperative and postoperative outcomes were calculated and used for meta-analysis. EMBASE, MEDLINE, SportsDiscus, CINAHL, Cochrane Library, and PEDro. Studies that evaluated hip pain, ADL function, sport function and quality of life before and after hip arthroscopy and postoperative satisfaction in patients with symptomatic FAI. Twenty-six studies (22 case series, 3 cohort studies, 1 randomised controlled trial (RCT)) were included in the systematic review and 19 in the meta-analysis. Clinically relevant pain and ADL function improvements were first reported between 3 and 6 months, and sport function improvements between 6 months and 1 year after surgery. It is not clear when quality of life improvements were first achieved. On average, residual mild pain and ADL and sport function scores lower than their healthy counterparts were reported by patients following surgery. Postoperative patient satisfaction ranged from 68% to 100%. On average, patients reported earlier pain and ADL function improvements, and slower sport function improvements after hip arthroscopy for FAI. However, average scores from patients indicate residual mild hip pain and/or hip function lower than their healthy counterparts after surgery. Owing to the current low level of evidence, future RCTs and cohort studies should investigate the effectiveness of hip arthroscopy in patients with FAI. CRD42015019649. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Sleep Disturbance, Daytime Symptoms, and Functional Performance in Patients With Stable Heart Failure: A Mediation Analysis.

PubMed

Jeon, Sangchoon; Redeker, Nancy S

2016-01-01

Sleep disturbance is common among patients with heart failure (HF) who also experience symptom burden and poor functional performance. We evaluated the extent to which sleep-related, daytime symptoms (fatigue, excessive daytime sleepiness, and depressive symptoms) mediate the relationship between sleep disturbance and functional performance among patients with stable HF. We recruited patients with stable HF for this secondary analysis of data from a cross-sectional, observational study. Participants completed unattended ambulatory polysomnography from which the Respiratory Disturbance Index was calculated, along with a Six-Minute Walk Test, questionnaires to elicit sleep disturbance (Pittsburgh Sleep Quality Index, Insomnia Symptoms from the Sleep Habits Questionnaire), daytime symptoms (Center for Epidemiologic Studies Depression Scale, Global Fatigue Index, Epworth Sleepiness Scale), and self-reported functional performance (Medical Outcomes Study SF36 V2 Physical Function Scale). We used structural equation modeling with latent variables for the key analysis. Follow-up, exploratory regression analysis with bootstrapped samples was used to examine the extent to which individual daytime symptoms mediated effects of sleep disturbance on functional performance after controlling for clinical and demographic covariates. The sample included 173 New York Heart Association Class I-IV HF patients (n = 60/34.7% women; M = 60.7, SD = 16.07 years of age). Daytime symptoms mediated the relationship between sleep disturbance and functional performance. Fatigue and depression mediated the relationship between insomnia symptoms and self-reported functional performance, whereas fatigue and sleepiness mediated the relationship between sleep quality and functional performance. Sleepiness mediated the relationship between the respiratory index and self-reported functional performance only in people who did not report insomnia. Daytime symptoms explain the relationships between sleep disturbance and functional performance in stable HF.

Transforming User Needs into Functional Requirements for an Antibiotic Clinical Decision Support System

PubMed Central

Bright, T.J.

2013-01-01

Summary Background Many informatics studies use content analysis to generate functional requirements for system development. Explication of this translational process from qualitative data to functional requirements can strengthen the understanding and scientific rigor when applying content analysis in informatics studies. Objective To describe a user-centered approach transforming emergent themes derived from focus group data into functional requirements for informatics solutions and to illustrate these methods to the development of an antibiotic clinical decision support system (CDS). Methods The approach consisted of five steps: 1) identify unmet therapeutic planning information needs via Focus Group Study-I, 2) develop a coding framework of therapeutic planning themes to refine the domain scope to antibiotic therapeutic planning, 3) identify functional requirements of an antibiotic CDS system via Focus Group Study-II, 4) discover informatics solutions and functional requirements from coded data, and 5) determine the types of information needed to support the antibiotic CDS system and link with the identified informatics solutions and functional requirements. Results The coding framework for Focus Group Study-I revealed unmet therapeutic planning needs. Twelve subthemes emerged and were clustered into four themes; analysis indicated a need for an antibiotic CDS intervention. Focus Group Study-II included five types of information needs. Comments from the Barrier/Challenge to information access and Function/Feature themes produced three informatics solutions and 13 functional requirements of an antibiotic CDS system. Comments from the Patient, Institution, and Domain themes generated required data elements for each informatics solution. Conclusion This study presents one example explicating content analysis of focus group data and the analysis process to functional requirements from narrative data. Illustration of this 5-step method was used to develop an antibiotic CDS system, resolving unmet antibiotic prescribing needs. As a reusable approach, these techniques can be refined and applied to resolve unmet information needs with informatics interventions in additional domains. PMID:24454586

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John; Lui, Su

2017-12-05

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta­-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular ­gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia. 2017 Joule Inc., or its licensors

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2018-03-01

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

Association between structural and functional brain alterations in drug-free patients with schizophrenia: a multimodal meta-analysis.

PubMed

Gao, Xin; Zhang, Wenjing; Yao, Li; Xiao, Yuan; Liu, Lu; Liu, Jieke; Li, Siyi; Tao, Bo; Shah, Chandan; Gong, Qiyong; Sweeney, John A; Lui, Su

2017-12-15

Neuroimaging studies have shown both structural and functional abnormalities in patients with schizophrenia. Recently, studies have begun to explore the association between structural and functional grey matter abnormalities. By conducting a meta-analysis on morphometric and functional imaging studies of grey matter alterations in drug-free patients, the present study aims to examine the degree of overlap between brain regions with anatomic and functional changes in patients with schizophrenia. We performed a systematic search of PubMed, Embase, Web of Science and the Cochrane Library to identify relevant publications. A multimodal analysis was then conducted using Seed-based d Mapping software. Exploratory analyses included jackknife, subgroup and meta-regression analyses. We included 15 structural MRI studies comprising 486 drug-free patients and 485 healthy controls, and 16 functional MRI studies comprising 403 drug-free patients and 428 controls in our meta-analysis. Drug-free patients were examined to reduce pharmacological effects on the imaging data. Multimodal analysis showed considerable overlap between anatomic and functional changes, mainly in frontotemporal regions, bilateral medial posterior cingulate/paracingulate gyrus, bilateral insula, basal ganglia and left cerebellum. There were also brain regions showing only anatomic changes in the right superior frontal gyrus, left supramarginal gyrus, right lingual gyrus and functional alternations involving the right angular gyrus. The methodological aspects, patient characteristics and clinical variables of the included studies were heterogeneous, and we cannot exclude medication effects. The present study showed overlapping anatomic and functional brain abnormalities mainly in the default mode (DMN) and auditory networks (AN) in drug-free patients with schizophrenia. However, the pattern of changes differed in these networks. Decreased grey matter was associated with decreased activation within the DMN, whereas it was associated with increased activation within the AN. These discrete patterns suggest different pathophysiological changes impacting structural and functional associations within different neural networks in patients with schizophrenia.

First Monte Carlo analysis of fragmentation functions from single-inclusive e + e - annihilation

DOE PAGES

Sato, Nobuo; Ethier, J. J.; Melnitchouk, W.; ...

2016-12-02

Here, we perform the first iterative Monte Carlo (IMC) analysis of fragmentation functions constrained by all available data from single-inclusive $e^+ e^-$ annihilation into pions and kaons. The IMC method eliminates potential bias in traditional analyses based on single fits introduced by fixing parameters not well contrained by the data, and provides a statistically rigorous determination of uncertainties. Our analysis reveals specific features of fragmentation functions using the new IMC methodology and those obtained from previous analyses, especially for light quarks and for strange quark fragmentation to kaons.

GEAR: genomic enrichment analysis of regional DNA copy number changes.

PubMed

Kim, Tae-Min; Jung, Yu-Chae; Rhyu, Mun-Gan; Jung, Myeong Ho; Chung, Yeun-Jun

2008-02-01

We developed an algorithm named GEAR (genomic enrichment analysis of regional DNA copy number changes) for functional interpretation of genome-wide DNA copy number changes identified by array-based comparative genomic hybridization. GEAR selects two types of chromosomal alterations with potential biological relevance, i.e. recurrent and phenotype-specific alterations. Then it performs functional enrichment analysis using a priori selected functional gene sets to identify primary and clinical genomic signatures. The genomic signatures identified by GEAR represent functionally coordinated genomic changes, which can provide clues on the underlying molecular mechanisms related to the phenotypes of interest. GEAR can help the identification of key molecular functions that are activated or repressed in the tumor genomes leading to the improved understanding on the tumor biology. GEAR software is available with online manual in the website, http://www.systemsbiology.co.kr/GEAR/.

A Functional Analysis of Non-Vocal Verbal Behavior of a Young Child with Autism

ERIC Educational Resources Information Center

Normand, M. P.; Severtson, E. S.; Beavers, G. A.

2008-01-01

The functions of an American Sign Language response were experimentally evaluated with a young boy diagnosed with autism. A functional analysis procedure based on that reported by Lerman et al. (2005) was used to evaluate whether the target sign response would occur under mand, tact, mimetic, or control conditions. The target sign was observed…

Differential Item Functioning Analysis of the Mental, Emotional, and Bodily Toughness Inventory

ERIC Educational Resources Information Center

Gao, Yong; Mack, Mick G.; Ragan, Moira A.; Ragan, Brian

2012-01-01

In this study the authors used differential item functioning analysis to examine if there were items in the Mental, Emotional, and Bodily Toughness Inventory functioning differently across gender and athletic membership. A total of 444 male (56.3%) and female (43.7%) participants (30.9% athletes and 69.1% non-athletes) responded to the Mental,…

Classroom-Based Functional Analysis and Intervention for Disruptive and Off-Task Behaviors

ERIC Educational Resources Information Center

Shumate, Emily D.; Wills, Howard P.

2010-01-01

Although there is a growing body of literature on the use of functional analysis in schools, there is a need for more demonstrations of this technology being used during the course of typical instruction. In this study, we conducted functional analyses of disruptive and off-task behavior in a reading classroom setting for 3 participants of typical…

Functional analysis and intervention for perseverative verbal behaviour of an older adult with traumatic brain injury.

PubMed

Quearry, Amy Garcia; Lundervold, Duane A

2016-01-01

A functional analysis of behaviour was conducted to determine the controlling variables related to the perseverative verbal behaviour (PBV) of a 60-year-old female with a long-standing traumatic brain injury receiving educational assistance. Functional analyses (FA) of antecedent and consequent conditions related to PCB were conducted to determine controlling influence of: (a) content of verbal interaction and, (b) social reinforcement. After isolating the controlling variables, the functioned-based intervention was implemented in 60 minute tutoring sessions. A reversal condition was used to demonstrate experimental control of the behavior during tutoring sessions. PVB which occurred in the context of tutoring for an undergraduate course significantly interfered with the delivery of instruction. Multiple replications of the functional relation between social reinforcement and PVB duration was demonstrated using an A-B-A-B reversal design during functional analysis and tutoring conditions. PVB markedly declined, but did not extinguish over the course of weekly tutoring (extinction) sessions, most likely due to 'bootleg reinforcement' occurring in other situations. Results indicate that perseverative verbal behaviour following closed head injury may be strongly influenced by the social contingencies operating in various contexts and is amenable to applied behaviour analysis interventions.

Studying hemispheric lateralization during a Stroop task through near-infrared spectroscopy-based connectivity

NASA Astrophysics Data System (ADS)

Zhang, Lei; Sun, Jinyan; Sun, Bailei; Luo, Qingming; Gong, Hui

2014-05-01

Near-infrared spectroscopy (NIRS) is a developing and promising functional brain imaging technology. Developing data analysis methods to effectively extract meaningful information from collected data is the major bottleneck in popularizing this technology. In this study, we measured hemodynamic activity of the prefrontal cortex (PFC) during a color-word matching Stroop task using NIRS. Hemispheric lateralization was examined by employing traditional activation and novel NIRS-based connectivity analyses simultaneously. Wavelet transform coherence was used to assess intrahemispheric functional connectivity. Spearman correlation analysis was used to examine the relationship between behavioral performance and activation/functional connectivity, respectively. In agreement with activation analysis, functional connectivity analysis revealed leftward lateralization for the Stroop effect and correlation with behavioral performance. However, functional connectivity was more sensitive than activation for identifying hemispheric lateralization. Granger causality was used to evaluate the effective connectivity between hemispheres. The results showed increased information flow from the left to the right hemispheres for the incongruent versus the neutral task, indicating a leading role of the left PFC. This study demonstrates that the NIRS-based connectivity can reveal the functional architecture of the brain more comprehensively than traditional activation, helping to better utilize the advantages of NIRS.

The Effect of Group Therapy With Transactional Analysis Approach on Emotional Intelligence, Executive Functions and Drug Dependency.

PubMed

Forghani, Masoomeh; Ghanbari Hashem Abadi, Bahram Ali

2016-06-01

The aim of the present study was to evaluate the effect of group psychotherapy with transactional analysis (TA) approach on emotional intelligence (EI), executive functions and substance dependency among drug-addicts at rehabilitation centers in Mashhad city, Iran, in 2013. In this quasi-experimental study with pretest, posttest, case- control stages, 30 patients were selected from a rehabilitation center and randomly divided into two groups. The case group received 12 sessions of group psychotherapy with transactional analysis approach. Then the effects of independent variable (group psychotherapy with TA approach) on EI, executive function and drug dependency were assessed. The Bar-on test was used for EI, Stroop test for measuring executive function and morphine test, meth-amphetamines and B2 test for evaluating drug dependency. Data were analyzed using multifactorial covariance analysis, Levenes' analysis, MANCOVA, t-student and Pearson correlation coefficient tests t with SPSS software. Our results showed that group psychotherapy with the TA approach was effective in improving EI, executive functions and decreasing drug dependency (P < 0.05). The result of this study showed that group psychotherapy with TA approach has significant effects on addicts and prevents addiction recurrence by improving the coping capabilities and some mental functions of the subjects. However, there are some limitations regarding this study including follow-up duration and sample size.

Nonstandard Analysis and Shock Wave Jump Conditions in a One-Dimensional Compressible Gas

NASA Technical Reports Server (NTRS)

Baty, Roy S.; Farassat, Fereidoun; Hargreaves, John

2007-01-01

Nonstandard analysis is a relatively new area of mathematics in which infinitesimal numbers can be defined and manipulated rigorously like real numbers. This report presents a fairly comprehensive tutorial on nonstandard analysis for physicists and engineers with many examples applicable to generalized functions. To demonstrate the power of the subject, the problem of shock wave jump conditions is studied for a one-dimensional compressible gas. It is assumed that the shock thickness occurs on an infinitesimal interval and the jump functions in the thermodynamic and fluid dynamic parameters occur smoothly across this interval. To use conservations laws, smooth pre-distributions of the Dirac delta measure are applied whose supports are contained within the shock thickness. Furthermore, smooth pre-distributions of the Heaviside function are applied which vary from zero to one across the shock wave. It is shown that if the equations of motion are expressed in nonconservative form then the relationships between the jump functions for the flow parameters may be found unambiguously. The analysis yields the classical Rankine-Hugoniot jump conditions for an inviscid shock wave. Moreover, non-monotonic entropy jump conditions are obtained for both inviscid and viscous flows. The report shows that products of generalized functions may be defined consistently using nonstandard analysis; however, physically meaningful products of generalized functions must be determined from the physics of the problem and not the mathematical form of the governing equations.

ACCEPTANCE OF FUNCTIONAL FOOD AMONG CHILEAN CONSUMERS: APPLE LEATHER.

PubMed

van Vliet, Maya; Adasme-Berrios, Cristian; Schnettler, Berta

2015-10-01

the aim of this study is to measure acceptance of a specific functional food: apple (fruit) leather, based on organoleptic characteristics and to identify consumer types and preferences for natural additives which increase the product's functionality and meet current nutritional needs. a sample of 800 consumers provided an evaluation of apple leather in terms of acceptance (liking). A sensorial panel was carried out using a 9-point hedonic scale. Cluster analysis was used to identify different acceptance-based consumer types. In addition, a conjoint analysis was carried out to determine preference for different additives. the cluster analysis resulted in four groups with significant differences in the average likings obtained from the sensory panel. Results indicate that the sweetness of the tested apple leather was evaluated best among all groups and, on average, color was rated as the worst attribute. However, overall likings differ significantly between groups. Results from the conjoint analysis indicate that, in general, consumers prefer natural additives included in the product which enhance functionality. although there is a "global acceptance" of the product, there are significant differences between groups. The results of the conjoint analysis indicate that, in general, consumers prefer the aggregation of natural additives which increase the product's functionality. Apple leather with natural additives, such as anticariogenics and antioxidants, can be considered a functional substitute of unhealthy snacks and/or sweets. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Mathematical Methods for Optical Physics and Engineering

NASA Astrophysics Data System (ADS)

Gbur, Gregory J.

2011-01-01

1. Vector algebra; 2. Vector calculus; 3. Vector calculus in curvilinear coordinate systems; 4. Matrices and linear algebra; 5. Advanced matrix techniques and tensors; 6. Distributions; 7. Infinite series; 8. Fourier series; 9. Complex analysis; 10. Advanced complex analysis; 11. Fourier transforms; 12. Other integral transforms; 13. Discrete transforms; 14. Ordinary differential equations; 15. Partial differential equations; 16. Bessel functions; 17. Legendre functions and spherical harmonics; 18. Orthogonal functions; 19. Green's functions; 20. The calculus of variations; 21. Asymptotic techniques; Appendices; References; Index.

Development of a Time-Variant Figure-of-Merit for Use in Analysis of Air Combat Maneuvering Engagements

DTIC Science & Technology

1976-07-16

Influence of Range 10 5 Range Performance Penalty Function II 6 Influence of Closing Velocity 12 7 Energy Influence Function 14 8 Comparison of the...flELtSHAlL, ..E^) RANGE RANGE Figure 7 Energy Influence Function 14 TM 76-1 SA ! PERFORMANCE INDEX COMPARATIVE ANALYSIS Maneuver Conversion Model...hnergy Integral ■’> E s K Energy Influence Function K* Proportionality Constant MT Target Mach Number N Normal Acceleration (load factor) z

Recent Selected Papers of Northwestern Polytechnical University in Two Parts, Part II.

DTIC Science & Technology

1981-08-28

OF CONTENTS Page Dual Properties of Elastic Structures 1 Matrix Analysis of Wings 76 On a Method for the Determination of Plane Stress Fracture...I= Ea]{(x, v,z) j l~i l’m mini The equation above means that the cisplacement function vector determines the strain function vector. (Assumption II...means that the distributed load function vector is determined by the stress function vector. In Section 1, there was an analysis of a three

Free vibrations and buckling analysis of laminated plates by oscillatory radial basis functions

NASA Astrophysics Data System (ADS)

Neves, A. M. A.; Ferreira, A. J. M.

2015-12-01

In this paper the free vibrations and buckling analysis of laminated plates is performed using a global meshless method. A refined version of Kant's theorie which accounts for transverse normal stress and through-the-thickness deformation is used. The innovation is the use of oscillatory radial basis functions. Numerical examples are performed and results are presented and compared to available references. Such functions proved to be an alternative to the tradicional nonoscillatory radial basis functions.

First passage time: Connecting random walks to functional responses in heterogeneous environments (Invited)

NASA Astrophysics Data System (ADS)

Lewis, M. A.; McKenzie, H.; Merrill, E.

2010-12-01

In this talk I will outline first passage time analysis for animals undertaking complex movement patterns, and will demonstrate how first passage time can be used to derive functional responses in predator prey systems. The result is a new approach to understanding type III functional responses based on a random walk model. I will extend the analysis to heterogeneous environments to assess the effects of linear features on functional responses in wolves and elk using GPS tracking data.

Functional data analysis of sleeping energy expenditure.

PubMed

Lee, Jong Soo; Zakeri, Issa F; Butte, Nancy F

2017-01-01

Adequate sleep is crucial during childhood for metabolic health, and physical and cognitive development. Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE). Functional data analysis methods were applied to SEE data to elucidate the population structure of SEE and to discriminate SEE between obese and non-obese children. Minute-by-minute SEE in 109 children, ages 5-18, was measured in room respiration calorimeters. A smoothing spline method was applied to the calorimetric data to extract the true smoothing function for each subject. Functional principal component analysis was used to capture the important modes of variation of the functional data and to identify differences in SEE patterns. Combinations of functional principal component analysis and classifier algorithm were used to classify SEE. Smoothing effectively removed instrumentation noise inherent in the room calorimeter data, providing more accurate data for analysis of the dynamics of SEE. SEE exhibited declining but subtly undulating patterns throughout the night. Mean SEE was markedly higher in obese than non-obese children, as expected due to their greater body mass. SEE was higher among the obese than non-obese children (p<0.01); however, the weight-adjusted mean SEE was not statistically different (p>0.1, after post hoc testing). Functional principal component scores for the first two components explained 77.8% of the variance in SEE and also differed between groups (p = 0.037). Logistic regression, support vector machine or random forest classification methods were able to distinguish weight-adjusted SEE between obese and non-obese participants with good classification rates (62-64%). Our results implicate other factors, yet to be uncovered, that affect the weight-adjusted SEE of obese and non-obese children. Functional data analysis revealed differences in the structure of SEE between obese and non-obese children that may contribute to disruption of metabolic homeostasis.

Production Functions for Water Delivery Systems: Analysis and Estimation Using Dual Cost Function and Implicit Price Specifications

NASA Astrophysics Data System (ADS)

Teeples, Ronald; Glyer, David

1987-05-01

Both policy and technical analysis of water delivery systems have been based on cost functions that are inconsistent with or are incomplete representations of the neoclassical production functions of economics. We present a full-featured production function model of water delivery which can be estimated from a multiproduct, dual cost function. The model features implicit prices for own-water inputs and is implemented as a jointly estimated system of input share equations and a translog cost function. Likelihood ratio tests are performed showing that a minimally constrained, full-featured production function is a necessary specification of the water delivery operations in our sample. This, plus the model's highly efficient and economically correct parameter estimates, confirms the usefulness of a production function approach to modeling the economic activities of water delivery systems.

Neurophysiological analysis of echolocation in bats

NASA Technical Reports Server (NTRS)

Suga, N.

1972-01-01

An analysis of echolocation and signal processing in brown bats is presented. Data cover echo detection, echo ranging, echolocalization, and echo analysis. Efforts were also made to identify the part of the brain that carries out the most essential processing function for echolocation. Results indicate the inferior colliculus and the auditory nuclei function together to process this information.

Checking Equity: Why Differential Item Functioning Analysis Should Be a Routine Part of Developing Conceptual Assessments

ERIC Educational Resources Information Center

Martinková, Patricia; Drabinová, Adéla; Liaw, Yuan-Ling; Sanders, Elizabeth A.; McFarland, Jenny L.; Price, Rebecca M.

2017-01-01

We provide a tutorial on differential item functioning (DIF) analysis, an analytic method useful for identifying potentially biased items in assessments. After explaining a number of methodological approaches, we test for gender bias in two scenarios that demonstrate why DIF analysis is crucial for developing assessments, particularly because…

Influential Observations in Principal Factor Analysis.

ERIC Educational Resources Information Center

Tanaka, Yutaka; Odaka, Yoshimasa

1989-01-01

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

Smart roadside initiative gap analysis : target functionality and gap analysis.

DOT National Transportation Integrated Search

2015-02-01

This document summarizes the target functionality for the Smart Roadside Initiative, as well as the operational, institutional, and technical gaps that currently impede the deployment of three of its operational scenarios (electronic mainline s...

FUNCTIONAL ANALYSIS AND TREATMENT OF COPROPHAGIA

PubMed Central

Ing, Anna D; Roane, Henry S; Veenstra, Rebecca A

2011-01-01

In the current investigation, functional analysis results suggested that coprophagia, the ingestion of fecal matter, was maintained by automatic reinforcement. Providing noncontingent access to alternative stimuli decreased coprophagia, and the intervention was generalized to two settings. PMID:21541128

Impact of Plant Functional Types on Coherence Between Precipitation and Soil Moisture: A Wavelet Analysis

NASA Astrophysics Data System (ADS)

Liu, Qi; Hao, Yonghong; Stebler, Elaine; Tanaka, Nobuaki; Zou, Chris B.

2017-12-01

Mapping the spatiotemporal patterns of soil moisture within heterogeneous landscapes is important for resource management and for the understanding of hydrological processes. A critical challenge in this mapping is comparing remotely sensed or in situ observations from areas with different vegetation cover but subject to the same precipitation regime. We address this challenge by wavelet analysis of multiyear observations of soil moisture profiles from adjacent areas with contrasting plant functional types (grassland, woodland, and encroached) and precipitation. The analysis reveals the differing soil moisture patterns and dynamics between plant functional types. The coherence at high-frequency periodicities between precipitation and soil moisture generally decreases with depth but this is much more pronounced under woodland compared to grassland. Wavelet analysis provides new insights on soil moisture dynamics across plant functional types and is useful for assessing differences and similarities in landscapes with heterogeneous vegetation cover.

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function

PubMed Central

2009-01-01

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html. PMID:19775443

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

HYBRID NEURAL NETWORK AND SUPPORT VECTOR MACHINE METHOD FOR OPTIMIZATION

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor)

2005-01-01

System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.

Hybrid Neural Network and Support Vector Machine Method for Optimization

NASA Technical Reports Server (NTRS)

Rai, Man Mohan (Inventor)

2007-01-01

System and method for optimization of a design associated with a response function, using a hybrid neural net and support vector machine (NN/SVM) analysis to minimize or maximize an objective function, optionally subject to one or more constraints. As a first example, the NN/SVM analysis is applied iteratively to design of an aerodynamic component, such as an airfoil shape, where the objective function measures deviation from a target pressure distribution on the perimeter of the aerodynamic component. As a second example, the NN/SVM analysis is applied to data classification of a sequence of data points in a multidimensional space. The NN/SVM analysis is also applied to data regression.

Development of a probabilistic analysis methodology for structural reliability estimation

NASA Technical Reports Server (NTRS)

Torng, T. Y.; Wu, Y.-T.

1991-01-01

The novel probabilistic analysis method for assessment of structural reliability presented, which combines fast-convolution with an efficient structural reliability analysis, can after identifying the most important point of a limit state proceed to establish a quadratic-performance function. It then transforms the quadratic function into a linear one, and applies fast convolution. The method is applicable to problems requiring computer-intensive structural analysis. Five illustrative examples of the method's application are given.

The effect of preoperative training on functional recovery in patients undergoing total knee arthroplasty: A systematic review and meta-analysis.

PubMed

Ma, Jian-Xiong; Zhang, Lu-Kai; Kuang, Ming-Jie; Zhao, Jie; Wang, Ying; Lu, Bin; Sun, Lei; Ma, Xin-Long

2018-03-01

A meta-analysis to evaluate the efficacy of preoperative training on functional recovery in patients undergoing total knee arthroplasty. Randomized controlled trials (RCTs) about relevant studies were searched from PubMed (1996-2017.4), Embase (1980-2017.4), and the Cochrane Library (CENTRAL 2017.4). Nine studies which evaluated the effect of preoperative training on functional recovery in patients undergoing TKA were included in our meta-analysis. Meta-analysis results were collected and analyzed by Review Manager 5.3 (Copenhagen: The Nordic Cochrane Center the Collaboration 2014). Nine studies containing 777 patients meet the inclusion criteria. Our pooled data analysis indicated that preoperative training was as effective as the control group in terms of visual analogue scale(VAS) score at ascend stairs (P = 0.41) and descend stars (P = 0.80), rang of motion (ROM) of flexion (P = 0.86) and extension (P = 0.60), short form 36 (SF-36) of physical function score (P = 0.07) and bodily pain score (P = 0.39), western Ontario and Macmaster universities osteoarthritis index (WOMAC) function score (P = 0.10), and time up and go (P = 0.28). While differences were found in length of stay (P < 0.05). Our meta-analysis demonstrated that preoperative training have the similar efficacy on functional recovery in patients following total knee arthroplasty compared with control group. However, high quality studies with more patients were needed in future. Copyright © 2018 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Sources of Disconnection in Neurocognitive Aging: Cerebral White Matter Integrity, Resting-state Functional Connectivity, and White Matter Hyperintensity Volume

PubMed Central

Madden, David J.; Parks, Emily L.; Tallman, Catherine W.; Boylan, Maria A.; Hoagey, David A.; Cocjin, Sally B.; Packard, Lauren E.; Johnson, Micah A.; Chou, Ying-hui; Potter, Guy G.; Chen, Nan-kuei; Siciliano, Rachel E.; Monge, Zachary A.; Honig, Jesse A.; Diaz, Michele T.

2017-01-01

Age-related decline in fluid cognition can be characterized as a disconnection among specific brain structures, leading to a decline in functional efficiency. The potential sources of disconnection, however, are unclear. We investigated imaging measures of cerebral white matter integrity, resting-state functional connectivity, and white matter hyperintensity (WMH) volume as mediators of the relation between age and fluid cognition, in 145 healthy, community-dwelling adults 19–79 years of age. At a general level of analysis, with a single composite measure of fluid cognition and single measures of each of the three imaging modalities, age exhibited an independent influence on the cognitive and imaging measures, and the imaging variables did not mediate the age-cognition relation. At a more specific level of analysis, resting-state functional connectivity of sensorimotor networks was a significant mediator of the age-related decline in executive function. These findings suggest that different levels of analysis lead to different models of neurocognitive disconnection, and that resting-state functional connectivity, in particular, may contribute to age-related decline in executive function. PMID:28389085

Estimation of Psychophysical Thresholds Based on Neural Network Analysis of DPOAE Input/Output Functions

NASA Astrophysics Data System (ADS)

Naghibolhosseini, Maryam; Long, Glenis

2011-11-01

The distortion product otoacoustic emission (DPOAE) input/output (I/O) function may provide a potential tool for evaluating cochlear compression. Hearing loss causes an increase in the level of the sound that is just audible for the person, which affects the cochlea compression and thus the dynamic range of hearing. Although the slope of the I/O function is highly variable when the total DPOAE is used, separating the nonlinear-generator component from the reflection component reduces this variability. We separated the two components using least squares fit (LSF) analysis of logarithmic sweeping tones, and confirmed that the separated generator component provides more consistent I/O functions than the total DPOAE. In this paper we estimated the slope of the I/O functions of the generator components at different sound levels using LSF analysis. An artificial neural network (ANN) was used to estimate psychophysical thresholds using the estimated slopes of the I/O functions. DPOAE I/O functions determined in this way may help to estimate hearing thresholds and cochlear health.

Mixed kernel function support vector regression for global sensitivity analysis

NASA Astrophysics Data System (ADS)

Cheng, Kai; Lu, Zhenzhou; Wei, Yuhao; Shi, Yan; Zhou, Yicheng

2017-11-01

Global sensitivity analysis (GSA) plays an important role in exploring the respective effects of input variables on an assigned output response. Amongst the wide sensitivity analyses in literature, the Sobol indices have attracted much attention since they can provide accurate information for most models. In this paper, a mixed kernel function (MKF) based support vector regression (SVR) model is employed to evaluate the Sobol indices at low computational cost. By the proposed derivation, the estimation of the Sobol indices can be obtained by post-processing the coefficients of the SVR meta-model. The MKF is constituted by the orthogonal polynomials kernel function and Gaussian radial basis kernel function, thus the MKF possesses both the global characteristic advantage of the polynomials kernel function and the local characteristic advantage of the Gaussian radial basis kernel function. The proposed approach is suitable for high-dimensional and non-linear problems. Performance of the proposed approach is validated by various analytical functions and compared with the popular polynomial chaos expansion (PCE). Results demonstrate that the proposed approach is an efficient method for global sensitivity analysis.

Data on the application of Functional Data Analysis in food fermentations.

PubMed

Ruiz-Bellido, M A; Romero-Gil, V; García-García, P; Rodríguez-Gómez, F; Arroyo-López, F N; Garrido-Fernández, A

2016-12-01

This article refers to the paper "Assessment of table olive fermentation by functional data analysis" (Ruiz-Bellido et al., 2016) [1]. The dataset include pH, titratable acidity, yeast count and area values obtained during fermentation process (380 days) of Aloreña de Málaga olives subjected to five different fermentation systems: i) control of acidified cured olives, ii) highly acidified cured olives, iii) intermediate acidified cured olives, iv) control of traditional cracked olives, and v) traditional olives cracked after 72 h of exposure to air. Many of the Tables and Figures shown in this paper were deduced after application of Functional Data Analysis to raw data using a routine executed under R software for comparison among treatments by the transformation of raw data into smooth curves and the application of a new battery of statistical tools (functional pointwise estimation of the averages and standard deviations, maximum, minimum, first and second derivatives, functional regression, and functional F and t-tests).

Macroevolutionary trends of atomic composition and related functional group proportion in eukaryotic and prokaryotic proteins.

PubMed

Zhang, Yu-Juan; Yang, Chun-Lin; Hao, You-Jin; Li, Ying; Chen, Bin; Wen, Jian-Fan

2014-01-25

To fully explore the trends of atomic composition during the macroevolution from prokaryote to eukaryote, five atoms (oxygen, sulfur, nitrogen, carbon, hydrogen) and related functional groups in prokaryotic and eukaryotic proteins were surveyed and compared. Genome-wide analysis showed that eukaryotic proteins have more oxygen, sulfur and nitrogen atoms than prokaryotes do. Clusters of Orthologous Groups (COG) analysis revealed that oxygen, sulfur, carbon and hydrogen frequencies are higher in eukaryotic proteins than in their prokaryotic orthologs. Furthermore, functional group analysis demonstrated that eukaryotic proteins tend to have higher proportions of sulfhydryl, hydroxyl and acylamino, but lower of sulfide and carboxyl. Taken together, an apparent trend of increase was observed for oxygen and sulfur atoms in the macroevolution; the variation of oxygen and sulfur compositions and their related functional groups in macroevolution made eukaryotic proteins carry more useful functional groups. These results will be helpful for better understanding the functional significances of atomic composition evolution. Copyright © 2013 Elsevier B.V. All rights reserved.

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

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

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Characterizing bonding patterns in diradicals and triradicals by density-based wave function analysis: A uniform approach

DOE PAGES

Orms, Natalie; Rehn, Dirk; Dreuw, Andreas; ...

2017-12-21

Density-based wave function analysis enables unambiguous comparisons of electronic structure computed by different methods and removes ambiguity of orbital choices. Here, we use this tool to investigate the performance of different spin-flip methods for several prototypical diradicals and triradicals. In contrast to previous calibration studies that focused on energy gaps between high and low spin-states, we focus on the properties of the underlying wave functions, such as the number of effectively unpaired electrons. Comparison of different density functional and wave function theory results provides insight into the performance of the different methods when applied to strongly correlated systems such asmore » polyradicals. We also show that canonical molecular orbitals for species like large copper-containing diradicals fail to correctly represent the underlying electronic structure due to highly non-Koopmans character, while density-based analysis of the same wave function delivers a clear picture of bonding pattern.« less

Toward a revised evolutionary adaptationist analysis of depression: the social navigation hypothesis.

PubMed

Watson, Paul J; Andrews, Paul W

2002-10-01

Evolutionary biologists use Darwinian theory and functional design ("reverse engineering") analyses, to develop and test hypotheses about the adaptive functions of traits. Based upon a consideration of human social life and a functional design analysis of depression's core symptomatology we offer a comprehensive theory of its adaptive significance called the Social Navigation Hypothesis (SNH). The SNH attempts to account for all intensities of depression based on standard evolutionary theories of sociality, communication and psychological pain. The SNH suggests that depression evolved to perform two complimentary social problem-solving functions. First, depression induces cognitive changes that focus and enhance capacities for the accurate analysis and solution of key social problems, suggesting a social rumination function. Second, the costs associated with the anhedonia and psychomotor perturbation of depression can persuade reluctant social partners to provide help or make concessions via two possible mechanisms, namely, honest signaling and passive, unintentional fitness extortion. Thus it may also have a social motivation function.

Functional approach in estimation of cultural ecosystem services of recreational areas

NASA Astrophysics Data System (ADS)

Sautkin, I. S.; Rogova, T. V.

2018-01-01

The article is devoted to the identification and analysis of cultural ecosystem services of recreational areas from the different forest plant functional groups in the suburbs of Kazan. The study explored two cultural ecosystem services supplied by forest plants by linking these services to different plant functional traits. Information on the functional traits of 76 plants occurring in the forest ecosystems of the investigated area was collected from reference books on the biological characteristics of plant species. Analysis of these species and traits with the Ward clustering method yielded four functional groups with different potentials for delivering ecosystem services. The results show that the contribution of species diversity to services can be characterized through the functional traits of plants. This proves that there is a stable relationship between biodiversity and the quality and quantity of ecosystem services. The proposed method can be extended to other types of services (regulating and supporting). The analysis can be used in the socio-economic assessment of natural ecosystems for recreation and other uses.

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

PubMed

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

Systematic Characterization and Analysis of the Taxonomic Drivers of Functional Shifts in the Human Microbiome.

PubMed

Manor, Ohad; Borenstein, Elhanan

2017-02-08

Comparative analyses of the human microbiome have identified both taxonomic and functional shifts that are associated with numerous diseases. To date, however, microbiome taxonomy and function have mostly been studied independently and the taxonomic drivers of functional imbalances have not been systematically identified. Here, we present FishTaco, an analytical and computational framework that integrates taxonomic and functional comparative analyses to accurately quantify taxon-level contributions to disease-associated functional shifts. Applying FishTaco to several large-scale metagenomic cohorts, we show that shifts in the microbiome's functional capacity can be traced back to specific taxa. Furthermore, the set of taxa driving functional shifts and their contribution levels vary markedly between functions. We additionally find that similar functional imbalances in different diseases are driven by both disease-specific and shared taxa. Such integrated analysis of microbiome ecological and functional dynamics can inform future microbiome-based therapy, pinpointing putative intervention targets for manipulating the microbiome's functional capacity. Copyright © 2017 Elsevier Inc. All rights reserved.

Manipulations of Cartesian Graphs: A First Introduction to Analysis.

ERIC Educational Resources Information Center

Lowenthal, Francis; Vandeputte, Christiane

1989-01-01

Introduces an introductory module for analysis. Describes stock of basic functions and their graphs as part one and three methods as part two: transformations of simple graphs, the sum of stock functions, and upper and lower bounds. (YP)

The Function sin x/x.

ERIC Educational Resources Information Center

Gearhart, William B.; Shultz, Harris S.

1990-01-01

Presents some examples from geometry: area of a circle; centroid of a sector; Buffon's needle problem; and expression for pi. Describes several roles of the trigonometric function in mathematics and applications, including Fourier analysis, spectral theory, approximation theory, and numerical analysis. (YP)

How Root Cause Analysis Can Improve the Value Methodology

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

Wixson, James Robert

2002-05-01

Root cause analysis (RCA) is an important methodology that can be integrated with the VE Job Plan to generate superior results from the VE Methodology. The point at which RCA is most appropriate is after the function analysis and FAST Model have been built and functions for improvement have been chosen. These functions are then subjected to a simple, but, rigorous RCA to get to the root cause of their deficiencies, whether it is high cost/poor value, poor quality, or poor reliability. Once the most probable causes for these problems have been arrived at, better solutions for improvement can bemore » developed in the creativity phase because the team better understands the problems associated with these functions.« less

Occupancy analysis: design and operational energy studies in a new high-rise office building. Volume 3

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

Not Available

1983-10-01

The objective of this analysis, is simply to: determine how energy consumption varies as a function of building occupancy and utilization. This analysis is primarily involved with the relationship between occupancy patterns and energy consumption. It also addresses the relationship between building functional use (e.g., office, computer, parking, and food service) and energy consumption. This study investigates variations in use and energy consumption during (1) the period of building startup from pre-occupancy through initial occupancy to full occupancy, and (2) daily and night occupancy for weekdays, weekends, holidays, and vacation periods. The report includes an investigation of the relationship betweenmore » specific functional uses, systems requirements for those functions, and energy consumption.« less

The extended Lennard-Jones potential energy function: A simpler model for direct-potential-fit analysis

NASA Astrophysics Data System (ADS)

Hajigeorgiou, Photos G.

2016-12-01

An analytical model for the diatomic potential energy function that was recently tested as a universal function (Hajigeorgiou, 2010) has been further modified and tested as a suitable model for direct-potential-fit analysis. Applications are presented for the ground electronic states of three diatomic molecules: oxygen, carbon monoxide, and hydrogen fluoride. The adjustable parameters of the extended Lennard-Jones potential model are determined through nonlinear regression by fits to calculated rovibrational energy term values or experimental spectroscopic line positions. The model is shown to lead to reliable, compact and simple representations for the potential energy functions of these systems and could therefore be classified as a suitable and attractive model for direct-potential-fit analysis.

Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis.

PubMed

Nadzirin, Nurul; Firdaus-Raih, Mohd

2012-10-08

Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under "unknown function" are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.

Multilayer motif analysis of brain networks

NASA Astrophysics Data System (ADS)

Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

2017-04-01

In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

Functional Proteomic Analysis of Human NucleolusD⃞

PubMed Central

Scherl, Alexander; Couté, Yohann; Déon, Catherine; Callé, Aleth; Kindbeiter, Karine; Sanchez, Jean-Charles; Greco, Anna; Hochstrasser, Denis; Diaz, Jean-Jacques

2002-01-01

The notion of a “plurifunctional” nucleolus is now well established. However, molecular mechanisms underlying the biological processes occurring within this nuclear domain remain only partially understood. As a first step in elucidating these mechanisms we have carried out a proteomic analysis to draw up a list of proteins present within nucleoli of HeLa cells. This analysis allowed the identification of 213 different nucleolar proteins. This catalog complements that of the 271 proteins obtained recently by others, giving a total of ∼350 different nucleolar proteins. Functional classification of these proteins allowed outlining several biological processes taking place within nucleoli. Bioinformatic analyses permitted the assignment of hypothetical functions for 43 proteins for which no functional information is available. Notably, a role in ribosome biogenesis was proposed for 31 proteins. More generally, this functional classification reinforces the plurifunctional nature of nucleoli and provides convincing evidence that nucleoli may play a central role in the control of gene expression. Finally, this analysis supports the recent demonstration of a coupling of transcription and translation in higher eukaryotes. PMID:12429849

Objective function analysis for electric soundings (VES), transient electromagnetic soundings (TEM) and joint inversion VES/TEM

NASA Astrophysics Data System (ADS)

Bortolozo, Cassiano Antonio; Bokhonok, Oleg; Porsani, Jorge Luís; Monteiro dos Santos, Fernando Acácio; Diogo, Liliana Alcazar; Slob, Evert

2017-11-01

Ambiguities in geophysical inversion results are always present. How these ambiguities appear in most cases open to interpretation. It is interesting to investigate ambiguities with regard to the parameters of the models under study. Residual Function Dispersion Map (RFDM) can be used to differentiate between global ambiguities and local minima in the objective function. We apply RFDM to Vertical Electrical Sounding (VES) and TEM Sounding inversion results. Through topographic analysis of the objective function we evaluate the advantages and limitations of electrical sounding data compared with TEM sounding data, and the benefits of joint inversion in comparison with the individual methods. The RFDM analysis proved to be a very interesting tool for understanding the joint inversion method of VES/TEM. Also the advantage of the applicability of the RFDM analyses in real data is explored in this paper to demonstrate not only how the objective function of real data behaves but the applicability of the RFDM approach in real cases. With the analysis of the results, it is possible to understand how the joint inversion can reduce the ambiguity of the methods.

Using scale and feather traits for module construction provides a functional approach to chicken epidermal development.

PubMed

Bao, Weier; Greenwold, Matthew J; Sawyer, Roger H

2017-11-01

Gene co-expression network analysis has been a research method widely used in systematically exploring gene function and interaction. Using the Weighted Gene Co-expression Network Analysis (WGCNA) approach to construct a gene co-expression network using data from a customized 44K microarray transcriptome of chicken epidermal embryogenesis, we have identified two distinct modules that are highly correlated with scale or feather development traits. Signaling pathways related to feather development were enriched in the traditional KEGG pathway analysis and functional terms relating specifically to embryonic epidermal development were also enriched in the Gene Ontology analysis. Significant enrichment annotations were discovered from customized enrichment tools such as Modular Single-Set Enrichment Test (MSET) and Medical Subject Headings (MeSH). Hub genes in both trait-correlated modules showed strong specific functional enrichment toward epidermal development. Also, regulatory elements, such as transcription factors and miRNAs, were targeted in the significant enrichment result. This work highlights the advantage of this methodology for functional prediction of genes not previously associated with scale- and feather trait-related modules.

Resting State Network Topology of the Ferret Brain

PubMed Central

Zhou, Zhe Charles; Salzwedel, Andrew P.; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K.; Gilmore, John H.; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-01-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4 tesla MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. PMID:27596024

Firmware Modification Analysis in Programmable Logic Controllers

DTIC Science & Technology

2014-03-27

security and operational requirements [18, 19]. Money is a factor for the DOD but not a driving one. With private industry, money is a primary influential... functions in the original firmware. A proof-of-concept experiment demonstrates the functionality of the analysis tool using different firmware versions...Opcode Difference Comparison . . . . . . . . . . . . . . 37 3.1.2.3 Function Difference Comparison . . . . . . . . . . . . . 37 3.1.2.4 Call Graph

An Analysis of the Effects of Functional Communication and a Voice Output Communication Aid for a Child with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Olive, Melissa L.; Lang, Russell B.; Davis, Tonya N.

2008-01-01

The purpose of this study was to examine the effects of Functional Communication Training (FCT) and a Voice Output Communication Aid (VOCA) on the challenging behavior and language development of a 4-year-old girl with autism spectrum disorder. The participant's mother implemented modified functional analysis (FA) and intervention procedures in…

A functional approach to movement analysis and error identification in sports and physical education

PubMed Central

Hossner, Ernst-Joachim; Schiebl, Frank; Göhner, Ulrich

2015-01-01

In a hypothesis-and-theory paper, a functional approach to movement analysis in sports is introduced. In this approach, contrary to classical concepts, it is not anymore the “ideal” movement of elite athletes that is taken as a template for the movements produced by learners. Instead, movements are understood as the means to solve given tasks that in turn, are defined by to-be-achieved task goals. A functional analysis comprises the steps of (1) recognizing constraints that define the functional structure, (2) identifying sub-actions that subserve the achievement of structure-dependent goals, (3) explicating modalities as specifics of the movement execution, and (4) assigning functions to actions, sub-actions and modalities. Regarding motor-control theory, a functional approach can be linked to a dynamical-system framework of behavioral shaping, to cognitive models of modular effect-related motor control as well as to explicit concepts of goal setting and goal achievement. Finally, it is shown that a functional approach is of particular help for sports practice in the context of structuring part practice, recognizing functionally equivalent task solutions, finding innovative technique alternatives, distinguishing errors from style, and identifying root causes of movement errors. PMID:26441717

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family.

PubMed

Danisman, Selahattin; van Dijk, Aalt D J; Bimbo, Andrea; van der Wal, Froukje; Hennig, Lars; de Folter, Stefan; Angenent, Gerco C; Immink, Richard G H

2013-12-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein-protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein-protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

PubMed Central

Danisman, Selahattin; de Folter, Stefan; Immink, Richard G. H.

2013-01-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein–protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein–protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family. PMID:24129704

Fine-Granularity Functional Interaction Signatures for Characterization of Brain Conditions

PubMed Central

Hu, Xintao; Zhu, Dajiang; Lv, Peili; Li, Kaiming; Han, Junwei; Wang, Lihong; Shen, Dinggang; Guo, Lei; Liu, Tianming

2014-01-01

In the human brain, functional activity occurs at multiple spatial scales. Current studies on functional brain networks and their alterations in brain diseases via resting-state functional magnetic resonance imaging (rs-fMRI) are generally either at local scale (regionally confined analysis and inter-regional functional connectivity analysis) or at global scale (graph theoretic analysis). In contrast, inferring functional interaction at fine-granularity sub-network scale has not been adequately explored yet. Here our hypothesis is that functional interaction measured at fine-granularity subnetwork scale can provide new insight into the neural mechanisms of neurological and psychological conditions, thus offering complementary information for healthy and diseased population classification. In this paper, we derived fine-granularity functional interaction (FGFI) signatures in subjects with Mild Cognitive Impairment (MCI) and Schizophrenia by diffusion tensor imaging (DTI) and rsfMRI, and used patient-control classification experiments to evaluate the distinctiveness of the derived FGFI features. Our experimental results have shown that the FGFI features alone can achieve comparable classification performance compared with the commonly used inter-regional connectivity features. However, the classification performance can be substantially improved when FGFI features and inter-regional connectivity features are integrated, suggesting the complementary information achieved from the FGFI signatures. PMID:23319242

Clinical indicators of paraplegia underplay universal spinal cord neuronal injury from transient aortic occlusion.

PubMed

Bell, Marshall T; Puskas, Ferenc; Bennett, Daine T; Cleveland, Joseph C; Herson, Paco S; Mares, Joshua M; Meng, Xainzhong; Weyant, Michael J; Fullerton, David A; Brett Reece, T

2015-08-27

Paraplegia following complex aortic intervention relies on crude evaluation of lower extremity strength such as whether the patient can lift their legs or flex the ankle. Little attention has been given to the possible long-term neurologic sequelae following these procedures in patients appearing functionally normal. We hypothesize that mice subjected to minimal ischemic time will have functional and histological changes despite the gross appearance of normal function. Male mice underwent 3 min of aortic occlusion (n=14) or sham surgery (n=4) via a median sternotomy. Neurologic function was graded by Basso Motor Score (BMS) preoperatively and at 24h intervals after reperfusion. Mice appearing functionally normal and sham mice were placed on a walking beam and recorded on high-definition, for single-frame motion analysis. After 96 hrs, spinal cords were removed for histological analysis. Following 3 min of ischemia, functional outcomes were split evenly with either mice displaying almost normal function n=7 or near complete paraplegia n=7. Additionally, single-frame motion analysis revealed significant changes in gait. Histologically, there was a significant stepwise reduction of neuronal viability, with even the normal function ischemic group demonstrating significant loss of neurons. Despite the appearance of normal function, temporary ischemia induced marked cyto-architectural changes and neuronal degeneration. Furthermore high-definition gait analysis revealed significant changes in gait and activity following thoracic aortic occlusion. These data suggest that all patients undergoing procedures, even with short ischemic times, may have spinal cord injury that is not evident clinically. Copyright © 2015 Elsevier B.V. All rights reserved.

Neurobiological changes of schizotypy: evidence from both volume-based morphometric analysis and resting-state functional connectivity.

PubMed

Wang, Yi; Yan, Chao; Yin, Da-zhi; Fan, Ming-xia; Cheung, Eric F C; Pantelis, Christos; Chan, Raymond C K

2015-03-01

The current study sought to examine the underlying brain changes in individuals with high schizotypy by integrating networks derived from brain structural and functional imaging. Individuals with high schizotypy (n = 35) and low schizotypy (n = 34) controls were screened using the Schizotypal Personality Questionnaire and underwent brain structural and resting-state functional magnetic resonance imaging on a 3T scanner. Voxel-based morphometric analysis and graph theory-based functional network analysis were conducted. Individuals with high schizotypy showed reduced gray matter (GM) density in the insula and the dorsolateral prefrontal gyrus. The graph theoretical analysis showed that individuals with high schizotypy showed similar global properties in their functional networks as low schizotypy individuals. Several hubs of the functional network were identified in both groups, including the insula, the lingual gyrus, the postcentral gyrus, and the rolandic operculum. More hubs in the frontal lobe and fewer hubs in the occipital lobe were identified in individuals with high schizotypy. By comparing the functional connectivity between clusters with abnormal GM density and the whole brain, individuals with high schizotypy showed weaker functional connectivity between the left insula and the putamen, but stronger connectivity between the cerebellum and the medial frontal gyrus. Taken together, our findings suggest that individuals with high schizotypy present changes in terms of GM and resting-state functional connectivity, especially in the frontal lobe. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Quantifying Individual Brain Connectivity with Functional Principal Component Analysis for Networks.

PubMed

Petersen, Alexander; Zhao, Jianyang; Carmichael, Owen; Müller, Hans-Georg

2016-09-01

In typical functional connectivity studies, connections between voxels or regions in the brain are represented as edges in a network. Networks for different subjects are constructed at a given graph density and are summarized by some network measure such as path length. Examining these summary measures for many density values yields samples of connectivity curves, one for each individual. This has led to the adoption of basic tools of functional data analysis, most commonly to compare control and disease groups through the average curves in each group. Such group differences, however, neglect the variability in the sample of connectivity curves. In this article, the use of functional principal component analysis (FPCA) is demonstrated to enrich functional connectivity studies by providing increased power and flexibility for statistical inference. Specifically, individual connectivity curves are related to individual characteristics such as age and measures of cognitive function, thus providing a tool to relate brain connectivity with these variables at the individual level. This individual level analysis opens a new perspective that goes beyond previous group level comparisons. Using a large data set of resting-state functional magnetic resonance imaging scans, relationships between connectivity and two measures of cognitive function-episodic memory and executive function-were investigated. The group-based approach was implemented by dichotomizing the continuous cognitive variable and testing for group differences, resulting in no statistically significant findings. To demonstrate the new approach, FPCA was implemented, followed by linear regression models with cognitive scores as responses, identifying significant associations of connectivity in the right middle temporal region with both cognitive scores.

GOATS - Orbitology Component

NASA Technical Reports Server (NTRS)

Haber, Benjamin M.; Green, Joseph J.

2010-01-01

The GOATS Orbitology Component software was developed to specifically address the concerns presented by orbit analysis tools that are often written as stand-alone applications. These applications do not easily interface with standard JPL first-principles analysis tools, and have a steep learning curve due to their complicated nature. This toolset is written as a series of MATLAB functions, allowing seamless integration into existing JPL optical systems engineering modeling and analysis modules. The functions are completely open, and allow for advanced users to delve into and modify the underlying physics being modeled. Additionally, this software module fills an analysis gap, allowing for quick, high-level mission analysis trades without the need for detailed and complicated orbit analysis using commercial stand-alone tools. This software consists of a series of MATLAB functions to provide for geometric orbit-related analysis. This includes propagation of orbits to varying levels of generalization. In the simplest case, geosynchronous orbits can be modeled by specifying a subset of three orbit elements. The next case is a circular orbit, which can be specified by a subset of four orbit elements. The most general case is an arbitrary elliptical orbit specified by all six orbit elements. These orbits are all solved geometrically, under the basic problem of an object in circular (or elliptical) orbit around a rotating spheroid. The orbit functions output time series ground tracks, which serve as the basis for more detailed orbit analysis. This software module also includes functions to track the positions of the Sun, Moon, and arbitrary celestial bodies specified by right ascension and declination. Also included are functions to calculate line-of-sight geometries to ground-based targets, angular rotations and decompositions, and other line-of-site calculations. The toolset allows for the rapid execution of orbit trade studies at the level of detail required for the early stage of mission concept development.

Identification of BRCA1 missense substitutions that confer partial functional activity: potential moderate risk variants?

PubMed Central

Lovelock, Paul K; Spurdle, Amanda B; Mok, Myth TS; Farrugia, Daniel J; Lakhani, Sunil R; Healey, Sue; Arnold, Stephen; Buchanan, Daniel; Investigators, kConFab; Couch, Fergus J; Henderson, Beric R; Goldgar, David E; Tavtigian, Sean V; Chenevix-Trench, Georgia; Brown, Melissa A

2007-01-01

Introduction Many of the DNA sequence variants identified in the breast cancer susceptibility gene BRCA1 remain unclassified in terms of their potential pathogenicity. Both multifactorial likelihood analysis and functional approaches have been proposed as a means to elucidate likely clinical significance of such variants, but analysis of the comparative value of these methods for classifying all sequence variants has been limited. Methods We have compared the results from multifactorial likelihood analysis with those from several functional analyses for the four BRCA1 sequence variants A1708E, G1738R, R1699Q, and A1708V. Results Our results show that multifactorial likelihood analysis, which incorporates sequence conservation, co-inheritance, segregation, and tumour immunohistochemical analysis, may improve classification of variants. For A1708E, previously shown to be functionally compromised, analysis of oestrogen receptor, cytokeratin 5/6, and cytokeratin 14 tumour expression data significantly strengthened the prediction of pathogenicity, giving a posterior probability of pathogenicity of 99%. For G1738R, shown to be functionally defective in this study, immunohistochemistry analysis confirmed previous findings of inconsistent 'BRCA1-like' phenotypes for the two tumours studied, and the posterior probability for this variant was 96%. The posterior probabilities of R1699Q and A1708V were 54% and 69%, respectively, only moderately suggestive of increased risk. Interestingly, results from functional analyses suggest that both of these variants have only partial functional activity. R1699Q was defective in foci formation in response to DNA damage and displayed intermediate transcriptional transactivation activity but showed no evidence for centrosome amplification. In contrast, A1708V displayed an intermediate transcriptional transactivation activity and a normal foci formation response in response to DNA damage but induced centrosome amplification. Conclusion These data highlight the need for a range of functional studies to be performed in order to identify variants with partially compromised function. The results also raise the possibility that A1708V and R1699Q may be associated with a low or moderate risk of cancer. While data pooling strategies may provide more information for multifactorial analysis to improve the interpretation of the clinical significance of these variants, it is likely that the development of current multifactorial likelihood approaches and the consideration of alternative statistical approaches will be needed to determine whether these individually rare variants do confer a low or moderate risk of breast cancer. PMID:18036263

Accurate evaluation and analysis of functional genomics data and methods

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2016-01-01

The development of technology capable of inexpensively performing large-scale measurements of biological systems has generated a wealth of data. Integrative analysis of these data holds the promise of uncovering gene function, regulation, and, in the longer run, understanding complex disease. However, their analysis has proved very challenging, as it is difficult to quickly and effectively assess the relevance and accuracy of these data for individual biological questions. Here, we identify biases that present challenges for the assessment of functional genomics data and methods. We then discuss evaluation methods that, taken together, begin to address these issues. We also argue that the funding of systematic data-driven experiments and of high-quality curation efforts will further improve evaluation metrics so that they more-accurately assess functional genomics data and methods. Such metrics will allow researchers in the field of functional genomics to continue to answer important biological questions in a data-driven manner. PMID:22268703

Method for matching customer and manufacturer positions for metal product parameters standardization

NASA Astrophysics Data System (ADS)

Polyakova, Marina; Rubin, Gennadij; Danilova, Yulija

2018-04-01

Decision making is the main stage of regulation the relations between customer and manufacturer during the design the demands of norms in standards. It is necessary to match the positions of the negotiating sides in order to gain the consensus. In order to take into consideration the differences of customer and manufacturer estimation of the object under standardization process it is obvious to use special methods of analysis. It is proposed to establish relationships between product properties and its functions using functional-target analysis. The special feature of this type of functional analysis is the consideration of the research object functions and properties. It is shown on the example of hexagonal head crew the possibility to establish links between its functions and properties. Such approach allows obtaining a quantitative assessment of the closeness the positions of customer and manufacturer at decision making during the standard norms establishment.

Factorial structure and psychometric properties of a brief version of the Reminiscence Functions Scale with Chinese older adults.

PubMed

Lou, Vivian W Q; Choy, Jacky C P

2014-05-01

The current study aims to examine the factorial structure and psychometric properties of a brief version of the Reminiscence Functions Scale (RFS), a 14-item assessment tool of reminiscence functions, with Chinese older adults. The scale, covering four reminiscence functions (boredom reduction, bitterness revival, problem solving, and identity) was translated from English into Chinese and administered to older adults (N=675). Confirmatory factor analysis and hierarchical confirmatory factor analysis were conducted to examine its factorial structure, and its psychometric properties and criterion validity were examined. Confirmatory factor analysis supports a second-order model comprising one second-order factor and four first-order factors of RFS. The Cronbach's alpha of the subscales ranged from 0.75 to 0.90. The brief RFS contains a second-order factorial structure. Its psychometric properties support it as a sound instrument for measuring reminiscence functions among Chinese older adults.

Variational Methods in Design Optimization and Sensitivity Analysis for Two-Dimensional Euler Equations

NASA Technical Reports Server (NTRS)

Ibrahim, A. H.; Tiwari, S. N.; Smith, R. E.

1997-01-01

Variational methods (VM) sensitivity analysis employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

Functional Job Analysis: An Annotated Bibliography. Methods for Manpower Analysis No. 10.

ERIC Educational Resources Information Center

Fine, Sidney A.; And Others

The bibliography provides a chronological survey of the development, growth, and application of the concept of Functional Job Analysis (FJA) which provides for the formulation of qualifications of workers and the requirements of jobs in the same terms so that the one can be equated with measures of the other. An introductory section discusses FJA,…

Failure Mode/Mechanism Distributions

DTIC Science & Technology

1991-09-01

circuits , hybrids, discrete semiconductors, microwave devices, optoelectronics and nonelectronic parts employed in military, space, industrial and...FMEA may be performed as a hardware analysis, a functional analysis, or a combination analysis and is ideally initiated at the part, circuit or...by a single replaceable module , a separate FMEA could be performed on the internal functions of the module , viewing the module as a system. The level

A Comparison of Functional Models for Use in the Function-Failure Design Method

NASA Technical Reports Server (NTRS)

Stock, Michael E.; Stone, Robert B.; Tumer, Irem Y.

2006-01-01

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models.

EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

PubMed

Delorme, Arnaud; Makeig, Scott

2004-03-15

We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.

Applying meta-pathway analyses through metagenomics to identify the functional properties of the major bacterial communities of a single spontaneous cocoa bean fermentation process sample.

PubMed

Illeghems, Koen; Weckx, Stefan; De Vuyst, Luc

2015-09-01

A high-resolution functional metagenomic analysis of a representative single sample of a Brazilian spontaneous cocoa bean fermentation process was carried out to gain insight into its bacterial community functioning. By reconstruction of microbial meta-pathways based on metagenomic data, the current knowledge about the metabolic capabilities of bacterial members involved in the cocoa bean fermentation ecosystem was extended. Functional meta-pathway analysis revealed the distribution of the metabolic pathways between the bacterial members involved. The metabolic capabilities of the lactic acid bacteria present were most associated with the heterolactic fermentation and citrate assimilation pathways. The role of Enterobacteriaceae in the conversion of substrates was shown through the use of the mixed-acid fermentation and methylglyoxal detoxification pathways. Furthermore, several other potential functional roles for Enterobacteriaceae were indicated, such as pectinolysis and citrate assimilation. Concerning acetic acid bacteria, metabolic pathways were partially reconstructed, in particular those related to responses toward stress, explaining their metabolic activities during cocoa bean fermentation processes. Further, the in-depth metagenomic analysis unveiled functionalities involved in bacterial competitiveness, such as the occurrence of CRISPRs and potential bacteriocin production. Finally, comparative analysis of the metagenomic data with bacterial genomes of cocoa bean fermentation isolates revealed the applicability of the selected strains as functional starter cultures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Functional relevance for type 1 diabetes mellitus-associated genetic variants by using integrative analyses.

PubMed

Qiu, Ying-Hua; Deng, Fei-Yan; Tang, Zai-Xiang; Jiang, Zhen-Huan; Lei, Shu-Feng

2015-10-01

Type 1 diabetes mellitus (type 1 DM) is an autoimmune disease. Although genome-wide association studies (GWAS) and meta-analyses have successfully identified numerous type 1 DM-associated susceptibility loci, the underlying mechanisms for these susceptibility loci are currently largely unclear. Based on publicly available datasets, we performed integrative analyses (i.e., integrated gene relationships among implicated loci, differential gene expression analysis, functional prediction and functional annotation clustering analysis) and combined with expression quantitative trait loci (eQTL) results to further explore function mechanisms underlying the associations between genetic variants and type 1 DM. Among a total of 183 type 1 DM-associated SNPs, eQTL analysis showed that 17 SNPs with cis-regulated eQTL effects on 9 genes. All the 9 eQTL genes enrich in immune-related pathways or Gene Ontology (GO) terms. Functional prediction analysis identified 5 SNPs located in transcription factor (TF) binding sites. Of the 9 eQTL genes, 6 (TAP2, HLA-DOB, HLA-DQB1, HLA-DQA1, HLA-DRB5 and CTSH) were differentially expressed in type 1 DM-associated related cells. Especially, rs3825932 in CTSH has integrative functional evidence supporting the association with type 1 DM. These findings indicated that integrative analyses can yield important functional information to link genetic variants and type 1 DM. Copyright © 2015 American Society for Histocompatibility and Immunogenetics. Published by Elsevier Inc. All rights reserved.

Resting-state functional brain connectivity: lessons from functional near-infrared spectroscopy.

PubMed

Niu, Haijing; He, Yong

2014-04-01

Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain's low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.

Assessment of protein set coherence using functional annotations

PubMed Central

Chagoyen, Monica; Carazo, Jose M; Pascual-Montano, Alberto

2008-01-01

Background Analysis of large-scale experimental datasets frequently produces one or more sets of proteins that are subsequently mined for functional interpretation and validation. To this end, a number of computational methods have been devised that rely on the analysis of functional annotations. Although current methods provide valuable information (e.g. significantly enriched annotations, pairwise functional similarities), they do not specifically measure the degree of homogeneity of a protein set. Results In this work we present a method that scores the degree of functional homogeneity, or coherence, of a set of proteins on the basis of the global similarity of their functional annotations. The method uses statistical hypothesis testing to assess the significance of the set in the context of the functional space of a reference set. As such, it can be used as a first step in the validation of sets expected to be homogeneous prior to further functional interpretation. Conclusion We evaluate our method by analysing known biologically relevant sets as well as random ones. The known relevant sets comprise macromolecular complexes, cellular components and pathways described for Saccharomyces cerevisiae, which are mostly significantly coherent. Finally, we illustrate the usefulness of our approach for validating 'functional modules' obtained from computational analysis of protein-protein interaction networks. Matlab code and supplementary data are available at PMID:18937846

Nationwide analysis of adrenocortical carcinoma reveals higher perioperative morbidity in functional tumors.

PubMed

Parikh, Punam P; Rubio, Gustavo A; Farra, Josefina C; Lew, John I

2017-08-25

Current adrenalectomy outcomes for functional adrenocortical carcinoma (ACC) remain unclear. This study examines nationwide in-hospital post-adrenalectomy outcomes for ACC. A retrospective analysis of the Nationwide Inpatient Sample database (2006-2011) to identify unilateral adrenalectomy patients for functional or nonfunctional ACC was performed. Patient demographics, comorbidities and postoperative outcomes were evaluated by t-test, Chi-square and multivariate regression. Of 2199 patients who underwent adrenalectomy, 87% had nonfunctional and 13% had functional ACC (86% hypercortisolism, 16% hyperaldosteronism, 4% hyperandrogenism). Functional ACC patients had significantly more comorbidities, and experienced certain postoperative complications more frequently including wound issues, adrenocortical insufficiency and acute kidney injury with longer hospital stay compared to nonfunctional ACC (P < 0.01). On multivariate analysis, functional ACC was an independent prognosticator for wound complications (28.1, 95%CI 4.59-176.6). Patients with functional ACC manifest significant comorbidities with certain in-hospital complications. Such high-risk patients require appropriate preoperative medical optimization prior to adrenalectomy. Patients with functional adrenocortical carcinoma (ACC) have significant preoperative comorbidities and experience higher rates of certain postoperative complications including wound complications, hematoma formation, adrenal insufficiency, pulmonary embolism and acute kidney injury. Functional ACC patients also necessitate longer hospitalizations. These patients should undergo appropriate preoperative counseling in preparation for adrenalectomy. Copyright © 2017 Elsevier Inc. All rights reserved.

Rasch validation of the Arabic version of the lower extremity functional scale.

PubMed

Alnahdi, Ali H

2018-02-01

The purpose of this study was to examine the internal construct validity of the Arabic version of the Lower Extremity Functional Scale (20-item Arabic LEFS) using Rasch analysis. Patients (n = 170) with lower extremity musculoskeletal dysfunction were recruited. Rasch analysis of 20-item Arabic LEFS was performed. Once the initial Rasch analysis indicated that the 20-item Arabic LEFS did not fit the Rasch model, follow-up analyses were conducted to improve the fit of the scale to the Rasch measurement model. These modifications included removing misfitting individuals, changing item scoring structure, removing misfitting items, addressing bias caused by response dependency between items and differential item functioning (DIF). Initial analysis indicated deviation of the 20-item Arabic LEFS from the Rasch model. Disordered thresholds in eight items and response dependency between six items were detected with the scale as a whole did not meet the requirement of unidimensionality. Refinements led to a 15-item Arabic LEFS that demonstrated excellent internal consistency (person separation index [PSI] = 0.92) and satisfied all the requirement of the Rasch model. Rasch analysis did not support the 20-item Arabic LEFS as a unidimensional measure of lower extremity function. The refined 15-item Arabic LEFS met all the requirement of the Rasch model and hence is a valid objective measure of lower extremity function. The Rasch-validated 15-item Arabic LEFS needs to be further tested in an independent sample to confirm its fit to the Rasch measurement model. Implications for Rehabilitation The validity of the 20-item Arabic Lower Extremity Functional Scale to measure lower extremity function is not supported. The 15-item Arabic version of the LEFS is a valid measure of lower extremity function and can be used to quantify lower extremity function in patients with lower extremity musculoskeletal disorders.

Nutritional intervention as part of functional rehabilitation in older people with reduced functional ability: a systematic review and meta-analysis of randomised controlled studies.

PubMed

Beck, A M; Dent, E; Baldwin, C

2016-12-01

Nutritional intervention is increasingly recognised as having an important role in functional rehabilitation for older people. Nonetheless, a greater understanding of the functional benefit of nutritional interventions is needed. A systematic review and meta-analysis examined randomised controlled trials (RCTs) published between 2007 and 2014 with the aim of determining whether nutritional intervention combined with rehabilitation benefited older people with reduced functional ability. Six electronic databases were searched. RCTs including people aged 65 years and older with reduced physical, social and/or cognitive function were included. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed, and gradepro computer software (http://gradepro.org) was used for the quality assessment of critical and important outcomes. Included studies considered to be clinical homogenous were combined in a meta-analysis. Of the 788 studies screened, five were identified for inclusion. Nutritional intervention given with functional rehabilitation improved energy and protein intake, although it failed to provide any improvement in final body weight, hand-grip strength or muscle strength. There was no difference between groups in the critical outcomes; balance, cognition, activities of daily living and mortality at long-term follow-up. Nutritional intervention given with functional rehabilitation was associated with an increased likelihood of both mortality (odds ratio = 1.77; 95% confidence interval = 1.13-2.76) and hospitalisation (odds ratio = 2.29; 95% confidence interval = 1.10-4.79) during the intervention. Meta-analysis of the baseline data showed that, overall, the intervention cohort had a lower body weight and cognition. This meta-analysis highlights concerns regarding the quality of the randomisation of participants at baseline. Future high-quality research is essential to establish whether older people with loss of functional abilities can benefit from nutritional intervention. © 2016 The British Dietetic Association Ltd.

Development of the Functional Flow Block Diagram for the J-2X Rocket Engine System

NASA Technical Reports Server (NTRS)

White, Thomas; Stoller, Sandra L.; Greene, WIlliam D.; Christenson, Rick L.; Bowen, Barry C.

2007-01-01

The J-2X program calls for the upgrade of the Apollo-era Rocketdyne J-2 engine to higher power levels, using new materials and manufacturing techniques, and with more restrictive safety and reliability requirements than prior human-rated engines in NASA history. Such requirements demand a comprehensive systems engineering effort to ensure success. Pratt & Whitney Rocketdyne system engineers performed a functional analysis of the engine to establish the functional architecture. J-2X functions were captured in six major operational blocks. Each block was divided into sub-blocks or states. In each sub-block, functions necessary to perform each state were determined. A functional engine schematic consistent with the fidelity of the system model was defined for this analysis. The blocks, sub-blocks, and functions were sequentially numbered to differentiate the states in which the function were performed and to indicate the sequence of events. The Engine System was functionally partitioned, to provide separate and unique functional operators. Establishing unique functional operators as work output of the System Architecture process is novel in Liquid Propulsion Engine design. Each functional operator was described such that its unique functionality was identified. The decomposed functions were then allocated to the functional operators both of which were the inputs to the subsystem or component performance specifications. PWR also used a novel approach to identify and map the engine functional requirements to customer-specified functions. The final result was a comprehensive Functional Flow Block Diagram (FFBD) for the J-2X Engine System, decomposed to the component level and mapped to all functional requirements. This FFBD greatly facilitates component specification development, providing a well-defined trade space for functional trades at the subsystem and component level. It also provides a framework for function-based failure modes and effects analysis (FMEA), and a rigorous baseline for the functional architecture.

Ion-selective electrodes in organic elemental and functional group analysis: a review

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

Selig, W.

1977-11-08

The literature on the use of ion-selective electrodes in organic elemental and functional group analysis is surveyed in some detail. The survey is complete through Chemical Abstracts, Vol. 83 (1975). 40 figures, 52 tables, 236 references.

Functional data analysis of sleeping energy expenditure

USDA-ARS?s Scientific Manuscript database

Adequate sleep is crucial during childhood for metabolic health, and physical and cognitive development. Inadequate sleep can disrupt metabolic homeostasis and alter sleeping energy expenditure (SEE). Functional data analysis methods were applied to SEE data to elucidate the population structure of ...

Parameter Transient Behavior Analysis on Fault Tolerant Control System

NASA Technical Reports Server (NTRS)

Belcastro, Christine (Technical Monitor); Shin, Jong-Yeob

2003-01-01

In a fault tolerant control (FTC) system, a parameter varying FTC law is reconfigured based on fault parameters estimated by fault detection and isolation (FDI) modules. FDI modules require some time to detect fault occurrences in aero-vehicle dynamics. This paper illustrates analysis of a FTC system based on estimated fault parameter transient behavior which may include false fault detections during a short time interval. Using Lyapunov function analysis, the upper bound of an induced-L2 norm of the FTC system performance is calculated as a function of a fault detection time and the exponential decay rate of the Lyapunov function.

A novel analysis method for near infrared spectroscopy based on Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Zhou, Zhenyu; Yang, Hongyu; Liu, Yun; Ruan, Zongcai; Luo, Qingming; Gong, Hui; Lu, Zuhong

2007-05-01

Near Infrared Imager (NIRI) has been widely used to access the brain functional activity non-invasively. We use a portable, multi-channel and continuous-wave NIR topography instrument to measure the concentration changes of each hemoglobin species and map cerebral cortex functional activation. By extracting some essential features from the BOLD signals, optical tomography is able to be a new way of neuropsychological studies. Fourier spectral analysis provides a common framework for examining the distribution of global energy in the frequency domain. However, this method assumes that the signal should be stationary, which limits its application in non-stationary system. The hemoglobin species concentration changes are of such kind. In this work we develop a new signal processing method using Hilbert-Huang transform to perform spectral analysis of the functional NIRI signals. Compared with wavelet based multi-resolution analysis (MRA), we demonstrated the extraction of task related signal for observation of activation in the prefrontal cortex (PFC) in vision stimulation experiment. This method provides a new analysis tool for functional NIRI signals. Our experimental results show that the proposed approach provides the unique method for reconstructing target signal without losing original information and enables us to understand the episode of functional NIRI more precisely.

Study of space shuttle orbiter system management computer function. Volume 1: Analysis, baseline design

NASA Technical Reports Server (NTRS)

1975-01-01

A system analysis of the shuttle orbiter baseline system management (SM) computer function is performed. This analysis results in an alternative SM design which is also described. The alternative design exhibits several improvements over the baseline, some of which are increased crew usability, improved flexibility, and improved growth potential. The analysis consists of two parts: an application assessment and an implementation assessment. The former is concerned with the SM user needs and design functional aspects. The latter is concerned with design flexibility, reliability, growth potential, and technical risk. The system analysis is supported by several topical investigations. These include: treatment of false alarms, treatment of off-line items, significant interface parameters, and a design evaluation checklist. An in-depth formulation of techniques, concepts, and guidelines for design of automated performance verification is discussed.

Enhanced electrochemical nanoring electrode for analysis of cytosol in single cells.

PubMed

Zhuang, Lihong; Zuo, Huanzhen; Wu, Zengqiang; Wang, Yu; Fang, Danjun; Jiang, Dechen

2014-12-02

A microelectrode array has been applied for single cell analysis with relatively high throughput; however, the cells were typically cultured on the microelectrodes under cell-size microwell traps leading to the difficulty in the functionalization of an electrode surface for higher detection sensitivity. Here, nanoring electrodes embedded under the microwell traps were fabricated to achieve the isolation of the electrode surface and the cell support, and thus, the electrode surface can be modified to obtain enhanced electrochemical sensitivity for single cell analysis. Moreover, the nanometer-sized electrode permitted a faster diffusion of analyte to the surface for additional improvement in the sensitivity, which was evidenced by the electrochemical characterization and the simulation. To demonstrate the concept of the functionalized nanoring electrode for single cell analysis, the electrode surface was deposited with prussian blue to detect intracellular hydrogen peroxide at a single cell. Hundreds of picoamperes were observed on our functionalized nanoring electrode exhibiting the enhanced electrochemical sensitivity. The success in the achievement of a functionalized nanoring electrode will benefit the development of high throughput single cell electrochemical analysis.

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

Learning Time-Varying Coverage Functions

PubMed Central

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2015-01-01

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

Learning Time-Varying Coverage Functions.

PubMed

Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

2014-12-08

Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data.

Representation of the Physiological Factors Contributing to Postflight Changes in Functional Performance Using Motion Analysis Software

NASA Technical Reports Server (NTRS)

Parks, Kelsey

2010-01-01

Astronauts experience changes in multiple physiological systems due to exposure to the microgravity conditions of space flight. To understand how changes in physiological function influence functional performance, a testing procedure has been developed that evaluates both astronaut postflight functional performance and related physiological changes. Astronauts complete seven functional and physiological tests. The objective of this project is to use motion tracking and digitizing software to visually display the postflight decrement in the functional performance of the astronauts. The motion analysis software will be used to digitize astronaut data videos into stick figure videos to represent the astronauts as they perform the Functional Tasks Tests. This project will benefit NASA by allowing NASA scientists to present data of their neurological studies without revealing the identities of the astronauts.

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Assessing and Treating Stereotypical Behaviors in Classrooms Using a Functional Approach

ERIC Educational Resources Information Center

Bruhn, Allison L.; Balint-Langel, Kinga; Troughton, Leonard; Langan, Sean; Lodge, Kelsey; Kortemeyer, Sara

2015-01-01

For years, the assumption has been that stereotypical behaviors functioned only to provide sensory or automatic reinforcement. However, these behaviors also may serve social functions. Given the unsettled debate, functional behavior assessment and functional analysis can be used to identify the exact function of stereotypical behavior and design…

Functional Analysis of HIV/AIDS Stigma: Consensus or Divergence?

ERIC Educational Resources Information Center

Hosseinzadeh, Hassan; Hossain, Syeda Zakia

2011-01-01

Functional theory proposes that attitudes may serve a variety of purposes for individuals. This study aimed to determine whether stigmatized attitudes toward HIV/AIDS serve the same function for all (consensus function) or serve different functions for different individuals (divergence function) by assessing various aspects of HIV/AIDS stigma…

Response function of modulated grid Faraday cup plasma instruments

NASA Technical Reports Server (NTRS)

Barnett, A.; Olbert, S.

1986-01-01

Modulated grid Faraday cup plasma analyzers are a very useful tool for making in situ measurements of space plasmas. One of their great attributes is that their simplicity permits their angular response function to be calculated theoretically. An expression is derived for this response function by computing the trajectories of the charged particles inside the cup. The Voyager plasma science experiment is used as a specific example. Two approximations to the rigorous response function useful for data analysis are discussed. Multisensor analysis of solar wind data indicates that the formulas represent the true cup response function for all angles of incidence with a maximum error of only a few percent.

Towards tests of quark-hadron duality with functional analysis and spectral function data

NASA Astrophysics Data System (ADS)

Boito, Diogo; Caprini, Irinel

2017-04-01

The presence of terms that violate quark-hadron duality in the expansion of QCD Green's functions is a generally accepted fact. Recently, a new approach was proposed for the study of duality violations (DVs), which exploits the existence of a rigorous lower bound on the functional distance, measured in a certain norm, between a "true" correlator and its approximant calculated theoretically along a contour in the complex energy plane. In the present paper, we pursue the investigation of functional-analysis-based tests towards their application to real spectral function data. We derive a closed analytic expression for the minimal functional distance based on the general weighted L2 norm and discuss its relation with the distance measured in the L∞ norm. Using fake data sets obtained from a realistic toy model in which we allow for covariances inspired from the publicly available ALEPH spectral functions, we obtain, by Monte Carlo simulations, the statistical distribution of the strength parameter that measures the magnitude of the DV term added to the usual operator product expansion. The results show that, if the region with large errors near the end point of the spectrum in τ decays is excluded, the functional-analysis-based tests using either L2 or L∞ norms are able to detect, in a statistically significant way, the presence of DVs in realistic spectral function pseudodata.

Assessing prescription drug abuse using functional principal component analysis (FPCA) of wastewater data.

PubMed

Salvatore, Stefania; Røislien, Jo; Baz-Lomba, Jose A; Bramness, Jørgen G

2017-03-01

Wastewater-based epidemiology is an alternative method for estimating the collective drug use in a community. We applied functional data analysis, a statistical framework developed for analysing curve data, to investigate weekly temporal patterns in wastewater measurements of three prescription drugs with known abuse potential: methadone, oxazepam and methylphenidate, comparing them to positive and negative control drugs. Sewage samples were collected in February 2014 from a wastewater treatment plant in Oslo, Norway. The weekly pattern of each drug was extracted by fitting of generalized additive models, using trigonometric functions to model the cyclic behaviour. From the weekly component, the main temporal features were then extracted using functional principal component analysis. Results are presented through the functional principal components (FPCs) and corresponding FPC scores. Clinically, the most important weekly feature of the wastewater-based epidemiology data was the second FPC, representing the difference between average midweek level and a peak during the weekend, representing possible recreational use of a drug in the weekend. Estimated scores on this FPC indicated recreational use of methylphenidate, with a high weekend peak, but not for methadone and oxazepam. The functional principal component analysis uncovered clinically important temporal features of the weekly patterns of the use of prescription drugs detected from wastewater analysis. This may be used as a post-marketing surveillance method to monitor prescription drugs with abuse potential. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Extending bicluster analysis to annotate unclassified ORFs and predict novel functional modules using expression data

PubMed Central

Bryan, Kenneth; Cunningham, Pádraig

2008-01-01

Background Microarrays have the capacity to measure the expressions of thousands of genes in parallel over many experimental samples. The unsupervised classification technique of bicluster analysis has been employed previously to uncover gene expression correlations over subsets of samples with the aim of providing a more accurate model of the natural gene functional classes. This approach also has the potential to aid functional annotation of unclassified open reading frames (ORFs). Until now this aspect of biclustering has been under-explored. In this work we illustrate how bicluster analysis may be extended into a 'semi-supervised' ORF annotation approach referred to as BALBOA. Results The efficacy of the BALBOA ORF classification technique is first assessed via cross validation and compared to a multi-class k-Nearest Neighbour (kNN) benchmark across three independent gene expression datasets. BALBOA is then used to assign putative functional annotations to unclassified yeast ORFs. These predictions are evaluated using existing experimental and protein sequence information. Lastly, we employ a related semi-supervised method to predict the presence of novel functional modules within yeast. Conclusion In this paper we demonstrate how unsupervised classification methods, such as bicluster analysis, may be extended using of available annotations to form semi-supervised approaches within the gene expression analysis domain. We show that such methods have the potential to improve upon supervised approaches and shed new light on the functions of unclassified ORFs and their co-regulation. PMID:18831786

Systematic inference of functional phosphorylation events in yeast metabolism.

PubMed

Chen, Yu; Wang, Yonghong; Nielsen, Jens

2017-07-01

Protein phosphorylation is a post-translational modification that affects proteins by changing their structure and conformation in a rapid and reversible way, and it is an important mechanism for metabolic regulation in cells. Phosphoproteomics enables high-throughput identification of phosphorylation events on metabolic enzymes, but identifying functional phosphorylation events still requires more detailed biochemical characterization. Therefore, development of computational methods for investigating unknown functions of a large number of phosphorylation events identified by phosphoproteomics has received increased attention. We developed a mathematical framework that describes the relationship between phosphorylation level of a metabolic enzyme and the corresponding flux through the enzyme. Using this framework, it is possible to quantitatively estimate contribution of phosphorylation events to flux changes. We showed that phosphorylation regulation analysis, combined with a systematic workflow and correlation analysis, can be used for inference of functional phosphorylation events in steady and dynamic conditions, respectively. Using this analysis, we assigned functionality to phosphorylation events of 17 metabolic enzymes in the yeast Saccharomyces cerevisiae , among which 10 are novel. Phosphorylation regulation analysis cannot only be extended for inference of other functional post-translational modifications but also be a promising scaffold for multi-omics data integration in systems biology. Matlab codes for flux balance analysis in this study are available in Supplementary material. yhwang@ecust.edu.cn or nielsenj@chalmers.se. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

A database system to support image algorithm evaluation

NASA Technical Reports Server (NTRS)

Lien, Y. E.

1977-01-01

The design is given of an interactive image database system IMDB, which allows the user to create, retrieve, store, display, and manipulate images through the facility of a high-level, interactive image query (IQ) language. The query language IQ permits the user to define false color functions, pixel value transformations, overlay functions, zoom functions, and windows. The user manipulates the images through generic functions. The user can direct images to display devices for visual and qualitative analysis. Image histograms and pixel value distributions can also be computed to obtain a quantitative analysis of images.

Development of Flight Safety Prediction Methodology for U. S. Naval Safety Center. Revision 1

DTIC Science & Technology

1970-02-01

Safety Center. The methodology develoned encompassed functional analysis of the F-4J aircraft, assessment of the importance of safety- sensitive ... Sensitivity ... ....... . 4-8 V 4.5 Model Implementation ........ ......... . 4-10 4.5.1 Functional Analysis ..... ........... . 4-11 4. 5. 2 Major...Function Sensitivity Assignment ........ ... 4-13 i 4.5.3 Link Dependency Assignment ... ......... . 4-14 4.5.4 Computer Program for Sensitivity

A Decision Analysis Framework for Evaluation of Helmet Mounted Display Alternatives for Fighter Aircraft

DTIC Science & Technology

2014-12-26

additive value function, which assumes mutual preferential independence (Gregory S. Parnell, 2013). In other words, this method can be used if the... additive value function method to calculate the aggregate value of multiple objectives. Step 9 : Sensitivity Analysis Once the global values are...gravity metric, the additive method will be applied using equal weights for each axis value function. Pilot Satisfaction (Usability) As expressed

To the systematization of failure analysis for perturbed systems (in German)

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

Haller, U.

1974-01-01

The paper investigates the reliable functioning of complex technical systems. Of main importance is the question of how the functioning of technical systems which may fail or whose design still has some faults can be determined in the very earliest planning stages. The present paper is to develop a functioning schedule and to look for possible methods of systematic failure analysis of systems with stochastic failures. (RW/AK)

Do Tasks Make a Difference? Accounting for Heterogeneity of Performance of Children with Reading Difficulties on Tasks of Executive Function: Findings from a Meta-Analysis

ERIC Educational Resources Information Center

Booth, Josephine N.; Boyle, James M. E.; Kelly, Steve W.

2010-01-01

Research studies have implicated executive functions in reading difficulties (RD). But while some studies have found children with RD to be impaired on tasks of executive function other studies report unimpaired performance. A meta-analysis was carried out to determine whether these discrepant findings can be accounted for by differences in the…

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

PubMed

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

Association between the Type of Workplace and Lung Function in Copper Miners

PubMed Central

Gruszczyński, Leszek; Wojakowska, Anna; Ścieszka, Marek; Turczyn, Barbara; Schmidt, Edward

2016-01-01

The aim of the analysis was to retrospectively assess changes in lung function in copper miners depending on the type of workplace. In the groups of 225 operators, 188 welders, and 475 representatives of other jobs, spirometry was performed at the start of employment and subsequently after 10, 20, and 25 years of work. Spirometry Longitudinal Data Analysis software was used to estimate changes in group means for FEV1 and FVC. Multiple linear regression analysis was used to assess an association between workplace and lung function. Lung function assessed on the basis of calculation of longitudinal FEV1 (FVC) decline was similar in all studied groups. However, multiple linear regression model used in cross-sectional analysis revealed an association between workplace and lung function. In the group of welders, FEF75 was lower in comparison to operators and other miners as early as after 10 years of work. Simultaneously, in smoking welders, the FEV1/FVC ratio was lower than in nonsmokers (p < 0,05). The interactions between type of workplace and smoking (p < 0,05) in their effect on FVC, FEV1, PEF, and FEF50 were shown. Among underground working copper miners, the group of smoking welders is especially threatened by impairment of lung ventilatory function. PMID:27274987

Computational analysis of microRNA function in heart development.

PubMed

Liu, Ganqiang; Ding, Min; Chen, Jiajia; Huang, Jinyan; Wang, Haiyun; Jing, Qing; Shen, Bairong

2010-09-01

Emerging evidence suggests that specific spatio-temporal microRNA (miRNA) expression is required for heart development. In recent years, hundreds of miRNAs have been discovered. In contrast, functional annotations are available only for a very small fraction of these regulatory molecules. In order to provide a global perspective for the biologists who study the relationship between differentially expressed miRNAs and heart development, we employed computational analysis to uncover the specific cellular processes and biological pathways targeted by miRNAs in mouse heart development. Here, we utilized Gene Ontology (GO) categories, KEGG Pathway, and GeneGo Pathway Maps as a gene functional annotation system for miRNA target enrichment analysis. The target genes of miRNAs were found to be enriched in functional categories and pathway maps in which miRNAs could play important roles during heart development. Meanwhile, we developed miRHrt (http://sysbio.suda.edu.cn/mirhrt/), a database aiming to provide a comprehensive resource of miRNA function in regulating heart development. These computational analysis results effectively illustrated the correlation of differentially expressed miRNAs with cellular functions and heart development. We hope that the identified novel heart development-associated pathways and the database presented here would facilitate further understanding of the roles and mechanisms of miRNAs in heart development.

Describing Function Techniques for the Non-Linear Analysis of the Dynamics of a Rail Vehicle Wheelset

DOT National Transportation Integrated Search

1975-07-01

The describing function method of analysis is applied to investigate the influence of parametric variations on wheelset critical velocity. In addition, the relationship between the amplitude of sustained lateral oscillations and critical speed is der...

Using the Rasch Measurement Model in Psychometric Analysis of the Family Effectiveness Measure

PubMed Central

McCreary, Linda L.; Conrad, Karen M.; Conrad, Kendon J.; Scott, Christy K; Funk, Rodney R.; Dennis, Michael L.

2013-01-01

Background Valid assessment of family functioning can play a vital role in optimizing client outcomes. Because family functioning is influenced by family structure, socioeconomic context, and culture, existing measures of family functioning--primarily developed with nuclear, middle class European American families--may not be valid assessments of families in diverse populations. The Family Effectiveness Measure was developed to address this limitation. Objectives To test the Family Effectiveness Measure with data from a primarily low-income African American convenience sample, using the Rasch measurement model. Method A sample of 607 adult women completed the measure. Rasch analysis was used to assess unidimensionality, response category functioning, item fit, person reliability, differential item functioning by race and parental status, and item hierarchy. Criterion-related validity was tested using correlations with five other variables related to family functioning. Results The Family Effectiveness Measure measures two separate constructs: The effective family functioning construct was a psychometrically sound measure of the target construct that was more efficient due to the deletion of 22 items. The ineffective family functioning construct consisted of 16 of those deleted items but was not as strong psychometrically. Items in both constructs evidenced no differential item functioning by race. Criterion-related validity was supported for both. Discussion In contrast to the prevailing conceptualization that family functioning is a single construct, assessed by positively and negatively worded items, use of the Rasch analysis suggested the existence of two constructs. While the effective family functioning is a strong and efficient measure of family functioning, the ineffective family functioning will require additional item development and psychometric testing. PMID:23636342

Extracting a shape function for a signal with intra-wave frequency modulation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

How a submarine returns to periscope depth: analysing complex socio-technical systems using Cognitive Work Analysis.

PubMed

Stanton, Neville A; Bessell, Kevin

2014-01-01

This paper presents the application of Cognitive Work Analysis to the description of the functions, situations, activities, decisions, strategies, and competencies of a Trafalgar class submarine when performing the function of returning to periscope depth. All five phases of Cognitive Work Analysis are presented, namely: Work Domain Analysis, Control Task Analysis, Strategies Analysis, Social Organisation and Cooperation Analysis, and Worker Competencies Analysis. Complex socio-technical systems are difficult to analyse but Cognitive Work Analysis offers an integrated way of analysing complex systems with the core of functional means-ends analysis underlying all of the other representations. The joined-up analysis offers a coherent framework for understanding how socio-technical systems work. Data were collected through observation and interviews at different sites across the UK. The resultant representations present a statement of how the work domain and current activities are configured in this complex socio-technical system. This is intended to provide a baseline, from which all future conceptions of the domain may be compared. The strength of the analysis is in the multiple representations from which the constraints acting on the work may be analysed. Future research needs to challenge the assumptions behind these constraints in order to develop new ways of working. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

The Importance of Form in Skinner's Analysis of Verbal Behavior and a Further Step

ERIC Educational Resources Information Center

Vargas, E. A.

2013-01-01

A series of quotes from B. F. Skinner illustrates the importance of form in his analysis of verbal behavior. In that analysis, form plays an important part in contingency control. Form and function complement each other. Function, the array of variables that control a verbal utterance, dictates the meaning of a specified form; form, as stipulated…

Functional regression method for whole genome eQTL epistasis analysis with sequencing data.

PubMed

Xu, Kelin; Jin, Li; Xiong, Momiao

2017-05-18

Epistasis plays an essential rule in understanding the regulation mechanisms and is an essential component of the genetic architecture of the gene expressions. However, interaction analysis of gene expressions remains fundamentally unexplored due to great computational challenges and data availability. Due to variation in splicing, transcription start sites, polyadenylation sites, post-transcriptional RNA editing across the entire gene, and transcription rates of the cells, RNA-seq measurements generate large expression variability and collectively create the observed position level read count curves. A single number for measuring gene expression which is widely used for microarray measured gene expression analysis is highly unlikely to sufficiently account for large expression variation across the gene. Simultaneously analyzing epistatic architecture using the RNA-seq and whole genome sequencing (WGS) data poses enormous challenges. We develop a nonlinear functional regression model (FRGM) with functional responses where the position-level read counts within a gene are taken as a function of genomic position, and functional predictors where genotype profiles are viewed as a function of genomic position, for epistasis analysis with RNA-seq data. Instead of testing the interaction of all possible pair-wises SNPs, the FRGM takes a gene as a basic unit for epistasis analysis, which tests for the interaction of all possible pairs of genes and use all the information that can be accessed to collectively test interaction between all possible pairs of SNPs within two genome regions. By large-scale simulations, we demonstrate that the proposed FRGM for epistasis analysis can achieve the correct type 1 error and has higher power to detect the interactions between genes than the existing methods. The proposed methods are applied to the RNA-seq and WGS data from the 1000 Genome Project. The numbers of pairs of significantly interacting genes after Bonferroni correction identified using FRGM, RPKM and DESeq were 16,2361, 260 and 51, respectively, from the 350 European samples. The proposed FRGM for epistasis analysis of RNA-seq can capture isoform and position-level information and will have a broad application. Both simulations and real data analysis highlight the potential for the FRGM to be a good choice of the epistatic analysis with sequencing data.

CM-DataONE: A Framework for collaborative analysis of climate model output

NASA Astrophysics Data System (ADS)

Xu, Hao; Bai, Yuqi; Li, Sha; Dong, Wenhao; Huang, Wenyu; Xu, Shiming; Lin, Yanluan; Wang, Bin

2015-04-01

CM-DataONE is a distributed collaborative analysis framework for climate model data which aims to break through the data access barriers of increasing file size and to accelerate research process. As data size involved in project such as the fifth Coupled Model Intercomparison Project (CMIP5) has reached petabytes, conventional methods for analysis and diagnosis of model outputs have been rather time-consuming and redundant. CM-DataONE is developed for data publishers and researchers from relevant areas. It can enable easy access to distributed data and provide extensible analysis functions based on tools such as NCAR Command Language, NetCDF Operators (NCO) and Climate Data Operators (CDO). CM-DataONE can be easily installed, configured, and maintained. The main web application has two separate parts which communicate with each other through APIs based on HTTP protocol. The analytic server is designed to be installed in each data node while a data portal can be configured anywhere and connect to a nearest node. Functions such as data query, analytic task submission, status monitoring, visualization and product downloading are provided to end users by data portal. Data conform to CMIP5 Model Output Format in each peer node can be scanned by the server and mapped to a global information database. A scheduler included in the server is responsible for task decomposition, distribution and consolidation. Analysis functions are always executed where data locate. Analysis function package included in the server has provided commonly used functions such as EOF analysis, trend analysis and time series. Functions are coupled with data by XML descriptions and can be easily extended. Various types of results can be obtained by users for further studies. This framework has significantly decreased the amount of data to be transmitted and improved efficiency in model intercomparison jobs by supporting online analysis and multi-node collaboration. To end users, data query is therefore accelerated and the size of data to be downloaded is reduced. Methodology can be easily shared among scientists, avoiding unnecessary replication. Currently, a prototype of CM-DataONE has been deployed on two data nodes of Tsinghua University.

The use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

Variational Methods in Sensitivity Analysis and Optimization for Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Ibrahim, A. H.; Hou, G. J.-W.; Tiwari, S. N. (Principal Investigator)

1996-01-01

Variational methods (VM) sensitivity analysis, which is the continuous alternative to the discrete sensitivity analysis, is employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The determination of the sensitivity derivatives of the performance index or functional entails the coupled solutions of the state and costate equations. As the stable and converged numerical solution of the costate equations with their boundary conditions are a priori unknown, numerical stability analysis is performed on both the state and costate equations. Thereafter, based on the amplification factors obtained by solving the generalized eigenvalue equations, the stability behavior of the costate equations is discussed and compared with the state (Euler) equations. The stability analysis of the costate equations suggests that the converged and stable solution of the costate equation is possible only if the computational domain of the costate equations is transformed to take into account the reverse flow nature of the costate equations. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

Chemical-genetic profile analysis in yeast suggests that a previously uncharacterized open reading frame, YBR261C, affects protein synthesis

PubMed Central

Alamgir, Md; Eroukova, Veronika; Jessulat, Matthew; Xu, Jianhua; Golshani, Ashkan

2008-01-01

Background Functional genomics has received considerable attention in the post-genomic era, as it aims to identify function(s) for different genes. One way to study gene function is to investigate the alterations in the responses of deletion mutants to different stimuli. Here we investigate the genetic profile of yeast non-essential gene deletion array (yGDA, ~4700 strains) for increased sensitivity to paromomycin, which targets the process of protein synthesis. Results As expected, our analysis indicated that the majority of deletion strains (134) with increased sensitivity to paromomycin, are involved in protein biosynthesis. The remaining strains can be divided into smaller functional categories: metabolism (45), cellular component biogenesis and organization (28), DNA maintenance (21), transport (20), others (38) and unknown (39). These may represent minor cellular target sites (side-effects) for paromomycin. They may also represent novel links to protein synthesis. One of these strains carries a deletion for a previously uncharacterized ORF, YBR261C, that we term TAE1 for Translation Associated Element 1. Our focused follow-up experiments indicated that deletion of TAE1 alters the ribosomal profile of the mutant cells. Also, gene deletion strain for TAE1 has defects in both translation efficiency and fidelity. Miniaturized synthetic genetic array analysis further indicates that TAE1 genetically interacts with 16 ribosomal protein genes. Phenotypic suppression analysis using TAE1 overexpression also links TAE1 to protein synthesis. Conclusion We show that a previously uncharacterized ORF, YBR261C, affects the process of protein synthesis and reaffirm that large-scale genetic profile analysis can be a useful tool to study novel gene function(s). PMID:19055778

Chemical-genetic profile analysis in yeast suggests that a previously uncharacterized open reading frame, YBR261C, affects protein synthesis.

PubMed

Alamgir, Md; Eroukova, Veronika; Jessulat, Matthew; Xu, Jianhua; Golshani, Ashkan

2008-12-03

Functional genomics has received considerable attention in the post-genomic era, as it aims to identify function(s) for different genes. One way to study gene function is to investigate the alterations in the responses of deletion mutants to different stimuli. Here we investigate the genetic profile of yeast non-essential gene deletion array (yGDA, approximately 4700 strains) for increased sensitivity to paromomycin, which targets the process of protein synthesis. As expected, our analysis indicated that the majority of deletion strains (134) with increased sensitivity to paromomycin, are involved in protein biosynthesis. The remaining strains can be divided into smaller functional categories: metabolism (45), cellular component biogenesis and organization (28), DNA maintenance (21), transport (20), others (38) and unknown (39). These may represent minor cellular target sites (side-effects) for paromomycin. They may also represent novel links to protein synthesis. One of these strains carries a deletion for a previously uncharacterized ORF, YBR261C, that we term TAE1 for Translation Associated Element 1. Our focused follow-up experiments indicated that deletion of TAE1 alters the ribosomal profile of the mutant cells. Also, gene deletion strain for TAE1 has defects in both translation efficiency and fidelity. Miniaturized synthetic genetic array analysis further indicates that TAE1 genetically interacts with 16 ribosomal protein genes. Phenotypic suppression analysis using TAE1 overexpression also links TAE1 to protein synthesis. We show that a previously uncharacterized ORF, YBR261C, affects the process of protein synthesis and reaffirm that large-scale genetic profile analysis can be a useful tool to study novel gene function(s).

A simulator for evaluating methods for the detection of lesion-deficit associations

NASA Technical Reports Server (NTRS)

Megalooikonomou, V.; Davatzikos, C.; Herskovits, E. H.

2000-01-01

Although much has been learned about the functional organization of the human brain through lesion-deficit analysis, the variety of statistical and image-processing methods developed for this purpose precludes a closed-form analysis of the statistical power of these systems. Therefore, we developed a lesion-deficit simulator (LDS), which generates artificial subjects, each of which consists of a set of functional deficits, and a brain image with lesions; the deficits and lesions conform to predefined distributions. We used probability distributions to model the number, sizes, and spatial distribution of lesions, to model the structure-function associations, and to model registration error. We used the LDS to evaluate, as examples, the effects of the complexities and strengths of lesion-deficit associations, and of registration error, on the power of lesion-deficit analysis. We measured the numbers of recovered associations from these simulated data, as a function of the number of subjects analyzed, the strengths and number of associations in the statistical model, the number of structures associated with a particular function, and the prior probabilities of structures being abnormal. The number of subjects required to recover the simulated lesion-deficit associations was found to have an inverse relationship to the strength of associations, and to the smallest probability in the structure-function model. The number of structures associated with a particular function (i.e., the complexity of associations) had a much greater effect on the performance of the analysis method than did the total number of associations. We also found that registration error of 5 mm or less reduces the number of associations discovered by approximately 13% compared to perfect registration. The LDS provides a flexible framework for evaluating many aspects of lesion-deficit analysis.

The analysis of mathematics teachers' learning on algebra function limit material based on teaching experience difference

NASA Astrophysics Data System (ADS)

Ma'rufi, Budayasa, I. Ketut; Juniati, Dwi

2017-08-01

The aim of this study was to describe the analysis of mathematics teachers' learning on algebra function limit material based on teaching experience difference. The purpose of this study is to describe the analysis of mathematics teacher's learning on limit algebraic functions in terms of the differences of teaching experience. Learning analysis focused on Pedagogical Content Knowledge (PCK) of teachers in mathematics on limit algebraic functions related to the knowledge of pedagogy. PCK of teachers on limit algebraic function is a type of specialized knowledge for teachers on how to teach limit algebraic function that can be understood by students. Subjects are two high school mathematics teacher who has difference of teaching experience they are one Novice Teacher (NP) and one Experienced Teacher (ET). Data are collected through observation of learning in the class, videos of learning, and then analyzed using qualitative analysis. Teacher's knowledge of Pedagogic defined as a knowledge and understanding of teacher about planning and organizing of learning, and application of learning strategy. The research results showed that the Knowledge of Pedagogy on subject NT in mathematics learning on the material of limit function algebra showed that the subject NT tended to describe procedurally, without explaining the reasons why such steps were used, asking questions which tended to be monotonous not be guiding and digging deeper, and less varied in the use of learning strategies while subject ET gave limited guidance and opportunities to the students to find their own answers, exploit the potential of students to answer questions, provide an opportunity for students to interact and work in groups, and subject ET tended to combine conceptual and procedural explanation.

Long-Term Exposure to Primary Traffic Pollutants and Lung Function in Children: Cross-Sectional Study and Meta-Analysis.

PubMed

Barone-Adesi, Francesco; Dent, Jennifer E; Dajnak, David; Beevers, Sean; Anderson, H Ross; Kelly, Frank J; Cook, Derek G; Whincup, Peter H

2015-01-01

There is widespread concern about the possible health effects of traffic-related air pollution. Nitrogen dioxide (NO2) is a convenient marker of primary pollution. We investigated the associations between lung function and current residential exposure to a range of air pollutants (particularly NO2, NO, NOx and particulate matter) in London children. Moreover, we placed the results for NO2 in context with a meta-analysis of published estimates of the association. Associations between primary traffic pollutants and lung function were investigated in 4884 children aged 9-10 years who participated in the Child Heart and Health Study in England (CHASE). A systematic literature search identified 13 studies eligible for inclusion in a meta-analysis. We combined results from the meta-analysis with the distribution of the values of FEV1 in CHASE to estimate the prevalence of children with abnormal lung function (FEV1<80% of predicted value) expected under different scenarios of NO2 exposure. In CHASE, there were non-significant inverse associations between all pollutants except ozone and both FEV1 and FVC. In the meta-analysis, a 10 μg/m3 increase in NO2 was associated with an 8 ml lower FEV1 (95% CI: -14 to -1 ml; p: 0.016). The observed effect was not modified by a reported asthma diagnosis. On the basis of these results, a 10 μg/m3 increase in NO2 level would translate into a 7% (95% CI: 4% to 12%) increase of the prevalence of children with abnormal lung function. Exposure to traffic pollution may cause a small overall reduction in lung function and increase the prevalence of children with clinically relevant declines in lung function.

A Functional Varying-Coefficient Single-Index Model for Functional Response Data

PubMed Central

Li, Jialiang; Huang, Chao; Zhu, Hongtu

2016-01-01

Motivated by the analysis of imaging data, we propose a novel functional varying-coefficient single index model (FVCSIM) to carry out the regression analysis of functional response data on a set of covariates of interest. FVCSIM represents a new extension of varying-coefficient single index models for scalar responses collected from cross-sectional and longitudinal studies. An efficient estimation procedure is developed to iteratively estimate varying coefficient functions, link functions, index parameter vectors, and the covariance function of individual functions. We systematically examine the asymptotic properties of all estimators including the weak convergence of the estimated varying coefficient functions, the asymptotic distribution of the estimated index parameter vectors, and the uniform convergence rate of the estimated covariance function and their spectrum. Simulation studies are carried out to assess the finite-sample performance of the proposed procedure. We apply FVCSIM to investigating the development of white matter diffusivities along the corpus callosum skeleton obtained from Alzheimer’s Disease Neuroimaging Initiative (ADNI) study. PMID:29200540

A Functional Varying-Coefficient Single-Index Model for Functional Response Data.

PubMed

Li, Jialiang; Huang, Chao; Zhu, Hongtu

2017-01-01

Motivated by the analysis of imaging data, we propose a novel functional varying-coefficient single index model (FVCSIM) to carry out the regression analysis of functional response data on a set of covariates of interest. FVCSIM represents a new extension of varying-coefficient single index models for scalar responses collected from cross-sectional and longitudinal studies. An efficient estimation procedure is developed to iteratively estimate varying coefficient functions, link functions, index parameter vectors, and the covariance function of individual functions. We systematically examine the asymptotic properties of all estimators including the weak convergence of the estimated varying coefficient functions, the asymptotic distribution of the estimated index parameter vectors, and the uniform convergence rate of the estimated covariance function and their spectrum. Simulation studies are carried out to assess the finite-sample performance of the proposed procedure. We apply FVCSIM to investigating the development of white matter diffusivities along the corpus callosum skeleton obtained from Alzheimer's Disease Neuroimaging Initiative (ADNI) study.

TWave: High-Order Analysis of Functional MRI

PubMed Central

Barnathan, Michael; Megalooikonomou, Vasileios; Faloutsos, Christos; Faro, Scott; Mohamed, Feroze B.

2011-01-01

The traditional approach to functional image analysis models images as matrices of raw voxel intensity values. Although such a representation is widely utilized and heavily entrenched both within neuroimaging and in the wider data mining community, the strong interactions among space, time, and categorical modes such as subject and experimental task inherent in functional imaging yield a dataset with “high-order” structure, which matrix models are incapable of exploiting. Reasoning across all of these modes of data concurrently requires a high-order model capable of representing relationships between all modes of the data in tandem. We thus propose to model functional MRI data using tensors, which are high-order generalizations of matrices equivalent to multidimensional arrays or data cubes. However, several unique challenges exist in the high-order analysis of functional medical data: naïve tensor models are incapable of exploiting spatiotemporal locality patterns, standard tensor analysis techniques exhibit poor efficiency, and mixtures of numeric and categorical modes of data are very often present in neuroimaging experiments. Formulating the problem of image clustering as a form of Latent Semantic Analysis and using the WaveCluster algorithm as a baseline, we propose a comprehensive hybrid tensor and wavelet framework for clustering, concept discovery, and compression of functional medical images which successfully addresses these challenges. Our approach reduced runtime and dataset size on a 9.3 GB finger opposition motor task fMRI dataset by up to 98% while exhibiting improved spatiotemporal coherence relative to standard tensor, wavelet, and voxel-based approaches. Our clustering technique was capable of automatically differentiating between the frontal areas of the brain responsible for task-related habituation and the motor regions responsible for executing the motor task, in contrast to a widely used fMRI analysis program, SPM, which only detected the latter region. Furthermore, our approach discovered latent concepts suggestive of subject handedness nearly 100x faster than standard approaches. These results suggest that a high-order model is an integral component to accurate scalable functional neuroimaging. PMID:21729758

Multiresolution Analysis by Infinitely Differentiable Compactly Supported Functions

DTIC Science & Technology

1992-09-01

Math. Surveys 45:1 (1990), 87-120. [I] (;. Strang and G. Fix, A Fourier analysis of the finite element variational method. C.I.M.F. I 1 Ciclo 1971, in Constructi’c Aspects of Functional Analyszs ed. G. Geymonat 1973, 793-840. 10

Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution

PubMed Central

Braberg, Hannes; Moehle, Erica A.; Shales, Michael; Guthrie, Christine; Krogan, Nevan J.

2014-01-01

We have achieved a residue-level resolution of genetic interaction mapping – a technique that measures how the function of one gene is affected by the alteration of a second gene – by analyzing point mutations. Here, we describe how to interpret point mutant genetic interactions, and outline key applications for the approach, including interrogation of protein interaction interfaces and active sites, and examination of post-translational modifications. Genetic interaction analysis has proven effective for characterizing cellular processes; however, to date, systematic high-throughput genetic interaction screens have relied on gene deletions or knockdowns, which limits the resolution of gene function analysis and poses problems for multifunctional genes. Our point mutant approach addresses these issues, and further provides a tool for in vivo structure-function analysis that complements traditional biophysical methods. We also discuss the potential for genetic interaction mapping of point mutations in human cells and its application to personalized medicine. PMID:24842270

Symmetric functions and wavefunctions of XXZ-type six-vertex models and elliptic Felderhof models by Izergin-Korepin analysis

NASA Astrophysics Data System (ADS)

Motegi, Kohei

2018-05-01

We present a method to analyze the wavefunctions of six-vertex models by extending the Izergin-Korepin analysis originally developed for domain wall boundary partition functions. First, we apply the method to the case of the basic wavefunctions of the XXZ-type six-vertex model. By giving the Izergin-Korepin characterization of the wavefunctions, we show that these wavefunctions can be expressed as multiparameter deformations of the quantum group deformed Grothendieck polynomials. As a second example, we show that the Izergin-Korepin analysis is effective for analysis of the wavefunctions for a triangular boundary and present the explicit forms of the symmetric functions representing these wavefunctions. As a third example, we apply the method to the elliptic Felderhof model which is a face-type version and an elliptic extension of the trigonometric Felderhof model. We show that the wavefunctions can be expressed as one-parameter deformations of an elliptic analog of the Vandermonde determinant and elliptic symmetric functions.

Analysis of Online Composite Mirror Descent Algorithm.

PubMed

Lei, Yunwen; Zhou, Ding-Xuan

2017-03-01

We study the convergence of the online composite mirror descent algorithm, which involves a mirror map to reflect the geometry of the data and a convex objective function consisting of a loss and a regularizer possibly inducing sparsity. Our error analysis provides convergence rates in terms of properties of the strongly convex differentiable mirror map and the objective function. For a class of objective functions with Hölder continuous gradients, the convergence rates of the excess (regularized) risk under polynomially decaying step sizes have the order [Formula: see text] after [Formula: see text] iterates. Our results improve the existing error analysis for the online composite mirror descent algorithm by avoiding averaging and removing boundedness assumptions, and they sharpen the existing convergence rates of the last iterate for online gradient descent without any boundedness assumptions. Our methodology mainly depends on a novel error decomposition in terms of an excess Bregman distance, refined analysis of self-bounding properties of the objective function, and the resulting one-step progress bounds.

Big Bang Bifurcation Analysis and Allee Effect in Generic Growth Functions

NASA Astrophysics Data System (ADS)

Leonel Rocha, J.; Taha, Abdel-Kaddous; Fournier-Prunaret, D.

2016-06-01

The main purpose of this work is to study the dynamics and bifurcation properties of generic growth functions, which are defined by the population size functions of the generic growth equation. This family of unimodal maps naturally incorporates a principal focus of ecological and biological research: the Allee effect. The analysis of this kind of extinction phenomenon allows to identify a class of Allee’s functions and characterize the corresponding Allee’s effect region and Allee’s bifurcation curve. The bifurcation analysis is founded on the performance of fold and flip bifurcations. The dynamical behavior is rich with abundant complex bifurcation structures, the big bang bifurcations of the so-called “box-within-a-box” fractal type being the most outstanding. Moreover, these bifurcation cascades converge to different big bang bifurcation curves with distinct kinds of boxes, where for the corresponding parameter values several attractors are associated. To the best of our knowledge, these results represent an original contribution to clarify the big bang bifurcation analysis of continuous 1D maps.

Microbial genome analysis: the COG approach.

PubMed

Galperin, Michael Y; Kristensen, David M; Makarova, Kira S; Wolf, Yuri I; Koonin, Eugene V

2017-09-14

For the past 20 years, the Clusters of Orthologous Genes (COG) database had been a popular tool for microbial genome annotation and comparative genomics. Initially created for the purpose of evolutionary classification of protein families, the COG have been used, apart from straightforward functional annotation of sequenced genomes, for such tasks as (i) unification of genome annotation in groups of related organisms; (ii) identification of missing and/or undetected genes in complete microbial genomes; (iii) analysis of genomic neighborhoods, in many cases allowing prediction of novel functional systems; (iv) analysis of metabolic pathways and prediction of alternative forms of enzymes; (v) comparison of organisms by COG functional categories; and (vi) prioritization of targets for structural and functional characterization. Here we review the principles of the COG approach and discuss its key advantages and drawbacks in microbial genome analysis. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Analysis/forecast experiments with a flow-dependent correlation function using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Carus, H.; Nestler, M. S.

1986-01-01

The use of a flow-dependent correlation function to improve the accuracy of an optimum interpolation (OI) scheme is examined. The development of the correlation function for the OI analysis scheme used for numerical weather prediction is described. The scheme uses a multivariate surface analysis over the oceans to model the pressure-wind error cross-correlation and it has the ability to use an error correlation function that is flow- and geographically-dependent. A series of four-day data assimilation experiments, conducted from January 5-9, 1979, were used to investigate the effect of the different features of the OI scheme (error correlation) on forecast skill for the barotropic lows and highs. The skill of the OI was compared with that of a successive correlation method (SCM) of analysis. It is observed that the largest difference in the correlation statistics occurred in barotropic and baroclinic lows and highs. The comparison reveals that the OI forecasts were more accurate than the SCM forecasts.

Parameter Estimation of Actuators for Benchmark Active Control Technology (BACT) Wind Tunnel Model with Analysis of Wear and Aerodynamic Loading Effects

NASA Technical Reports Server (NTRS)

Waszak, Martin R.; Fung, Jimmy

1998-01-01

This report describes the development of transfer function models for the trailing-edge and upper and lower spoiler actuators of the Benchmark Active Control Technology (BACT) wind tunnel model for application to control system analysis and design. A simple nonlinear least-squares parameter estimation approach is applied to determine transfer function parameters from frequency response data. Unconstrained quasi-Newton minimization of weighted frequency response error was employed to estimate the transfer function parameters. An analysis of the behavior of the actuators over time to assess the effects of wear and aerodynamic load by using the transfer function models is also presented. The frequency responses indicate consistent actuator behavior throughout the wind tunnel test and only slight degradation in effectiveness due to aerodynamic hinge loading. The resulting actuator models have been used in design, analysis, and simulation of controllers for the BACT to successfully suppress flutter over a wide range of conditions.

A phylogenetic analysis of normal modes evolution in enzymes and its relationship to enzyme function

PubMed Central

Lai, Jason; Jin, Jing; Kubelka, Jan; Liberles, David A.

2012-01-01

Since the dynamic nature of protein structures is essential for enzymatic function, it is expected that the functional evolution can be inferred from the changes in the protein dynamics. However, dynamics can also diverge neutrally with sequence substitution between enzymes without changes of function. In this study, a phylogenetic approach is implemented to explore the relationship between enzyme dynamics and function through evolutionary history. Protein dynamics are described by normal mode analysis based on a simplified harmonic potential force field applied to the reduced Cα representation of the protein structure while enzymatic function is described by Enzyme Commission (EC) numbers. Similarity of the binding pocket dynamics at each branch of the protein family’s phylogeny was analyzed in two ways: 1) explicitly by quantifying the normal mode overlap calculated for the reconstructed ancestral proteins at each end and 2) implicitly using a diffusion model to obtain the reconstructed lineage-specific changes in the normal modes. Both explicit and implicit ancestral reconstruction identified generally faster rates of change in dynamics compared with the expected change from neutral evolution at the branches of potential functional divergences for the alpha-amylase, D-isomer specific 2-hydroxyacid dehydrogenase, and copper-containing amine oxidase protein families. Normal modes analysis added additional information over just comparing the RMSD of static structures. However, the branch-specific changes were not statistically significant compared to background function-independent neutral rates of change of dynamic properties and blind application of the analysis would not enable prediction of changes in enzyme specificity. PMID:22651983

A phylogenetic analysis of normal modes evolution in enzymes and its relationship to enzyme function.

PubMed

Lai, Jason; Jin, Jing; Kubelka, Jan; Liberles, David A

2012-09-21

Since the dynamic nature of protein structures is essential for enzymatic function, it is expected that functional evolution can be inferred from the changes in protein dynamics. However, dynamics can also diverge neutrally with sequence substitution between enzymes without changes of function. In this study, a phylogenetic approach is implemented to explore the relationship between enzyme dynamics and function through evolutionary history. Protein dynamics are described by normal mode analysis based on a simplified harmonic potential force field applied to the reduced C(α) representation of the protein structure while enzymatic function is described by Enzyme Commission numbers. Similarity of the binding pocket dynamics at each branch of the protein family's phylogeny was analyzed in two ways: (1) explicitly by quantifying the normal mode overlap calculated for the reconstructed ancestral proteins at each end and (2) implicitly using a diffusion model to obtain the reconstructed lineage-specific changes in the normal modes. Both explicit and implicit ancestral reconstruction identified generally faster rates of change in dynamics compared with the expected change from neutral evolution at the branches of potential functional divergences for the α-amylase, D-isomer-specific 2-hydroxyacid dehydrogenase, and copper-containing amine oxidase protein families. Normal mode analysis added additional information over just comparing the RMSD of static structures. However, the branch-specific changes were not statistically significant compared to background function-independent neutral rates of change of dynamic properties and blind application of the analysis would not enable prediction of changes in enzyme specificity. Copyright © 2012 Elsevier Ltd. All rights reserved.

Shedding light into the function of the earliest vertebrate skeleton

NASA Astrophysics Data System (ADS)

Martinez-Perez, Carlos; Purnell, Mark; Rayfield, Emily; Donoghue, Philip

2016-04-01

Conodonts are an extinct group of jawless vertebrates, the first in our evolutionary lineage to develop a biomineralized skeleton. As such, the conodont skeleton is of great significance because of the insights it provides concerning the biology and function of the primitive vertebrate skeleton. Conodont function has been debated for a century and a half on the basis of its paleocological importance in the Palaezoic ecosystems. However, due to the lack of extanct close representatives and the small size of the conodont element (under a milimiter in length) strongly limited their functional analysis, traditional restricted to analogy. More recently, qualitative approaches have been developed, facilitating tests of element function based on occlusal performance and analysis of microwear and microstructure. In this work we extend these approaches using novel quantitative experimental methods including Synchrotron Radiation X-ray Tomographic Microscopy or Finite Element Analysis to test hypotheses of conodont function. The development of high resolution virtual models of conodont elements, together with biomechanical approaches using Finite Element analysis, informed by occlusal and microwear analyses, provided conclusive support to test hypothesis of structural adaptation within the crown tissue microstructure, showing a close topological co-variation patterns of compressive and tensile stress distribution with different crystallite orientation. In addition, our computational analyses strongly support a tooth-like function for many conodont species. Above all, our study establishes a framework (experimental approach) in which the functional ecology of conodonts can be read from their rich taxonomy and phylogeny, representing an important attempt to understand the role of this abundant and diverse clade in the Phanerozoic marine ecosystems.

Baseline Cardiopulmonary Function as an Independent Prognostic Factor for Survival of Inoperable Non-Small-Cell Lung Cancer After Concurrent Chemoradiotherapy: A Single-Center Analysis of 161 Cases

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

Semrau, Sabine, E-mail: sabine.semrau@uk-erlangen.d; Department of Radiation Therapy, University of Rostock, Suedring, Rostock; Klautke, Gunther

2011-01-01

Purpose: Little is known about the effects of cardiopulmonary function on the prognosis of concurrent chemoradiotherapy in patients with inoperable non-small-cell lung cancer (NSCLC). Methods and Materials: A retrospective analysis of the effects of tumor- and patient-related factors and parameters of cardiopulmonary function and heart morphology on the feasibility, toxicity, and prognosis was performed. Results: Cardiopulmonary function had no effect on the toxicity or feasibility of treatment; effects on survival were observed in the univariate analysis. Median survival varied as follows: cardiac function: 13.0 {+-} 1.6 months for left ventricular ejection fraction (LVEF) > 50% vs. 10.0 {+-} 1.9 monthsmore » for LVEF {<=} 50% (p = 0.003); pulmonary function: 16.0 {+-} 0.6 months for no lung function deficits (vital capacity [VC]{>=} 60%, forced expiratory volume in 1 s {>=} 80%, and diffusing capacity of the lung for carbon monoxide (DLCO) {>=}60%) vs. 14.0 {+-} 1.5 months for one or two function deficits vs. 8.0 {+-} 1.5 months for three lung function deficits (p = 0.001); T stage: 19.0 {+-} 3.1 months for rcT0/cT1/cT2 vs. 12.0 {+-} 0.8 months for cT3/cT4 (p = 0.039); and age: 11.0 {+-} 1.5 months for <60 years vs. 18.0 {+-} 2.5 months for 60-69 years vs. 12.0 {+-} 1.2 months for {>=}70 years (p = 0.008). Prognostic factors identified in the multivariate analysis were LVEF {<=}50% (p = 0.043; hazard ratio [HR], 1.74), reduced pulmonary function (p = 0.001; HR, 1.71 or 5.05) and T stage (p = 0.026; HR: 1.71). Conclusions: In addition to T-stage, cardiac and pulmonary function variables affected the survival of non-small-cell lung cancer patients after chemoradiotherapy.« less

Fusing modeling techniques to support domain analysis for reuse opportunities identification

NASA Technical Reports Server (NTRS)

Hall, Susan Main; Mcguire, Eileen

1993-01-01

Functional modeling techniques or object-oriented graphical representations, which are more useful to someone trying to understand the general design or high level requirements of a system? For a recent domain analysis effort, the answer was a fusion of popular modeling techniques of both types. By using both functional and object-oriented techniques, the analysts involved were able to lean on their experience in function oriented software development, while taking advantage of the descriptive power available in object oriented models. In addition, a base of familiar modeling methods permitted the group of mostly new domain analysts to learn the details of the domain analysis process while producing a quality product. This paper describes the background of this project and then provides a high level definition of domain analysis. The majority of this paper focuses on the modeling method developed and utilized during this analysis effort.

A framework for joint image-and-shape analysis

NASA Astrophysics Data System (ADS)

Gao, Yi; Tannenbaum, Allen; Bouix, Sylvain

2014-03-01

Techniques in medical image analysis are many times used for the comparison or regression on the intensities of images. In general, the domain of the image is a given Cartesian grids. Shape analysis, on the other hand, studies the similarities and differences among spatial objects of arbitrary geometry and topology. Usually, there is no function defined on the domain of shapes. Recently, there has been a growing needs for defining and analyzing functions defined on the shape space, and a coupled analysis on both the shapes and the functions defined on them. Following this direction, in this work we present a coupled analysis for both images and shapes. As a result, the statistically significant discrepancies in both the image intensities as well as on the underlying shapes are detected. The method is applied on both brain images for the schizophrenia and heart images for atrial fibrillation patients.

Functional phylogenomics analysis of bacteria and archaea using consistent genome annotation with UniFam

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

Chai, Juanjuan; Kora, Guruprasad; Ahn, Tae-Hyuk

2014-10-09

To supply some background, phylogenetic studies have provided detailed knowledge on the evolutionary mechanisms of genes and species in Bacteria and Archaea. However, the evolution of cellular functions, represented by metabolic pathways and biological processes, has not been systematically characterized. Many clades in the prokaryotic tree of life have now been covered by sequenced genomes in GenBank. This enables a large-scale functional phylogenomics study of many computationally inferred cellular functions across all sequenced prokaryotes. Our results show a total of 14,727 GenBank prokaryotic genomes were re-annotated using a new protein family database, UniFam, to obtain consistent functional annotations for accuratemore » comparison. The functional profile of a genome was represented by the biological process Gene Ontology (GO) terms in its annotation. The GO term enrichment analysis differentiated the functional profiles between selected archaeal taxa. 706 prokaryotic metabolic pathways were inferred from these genomes using Pathway Tools and MetaCyc. The consistency between the distribution of metabolic pathways in the genomes and the phylogenetic tree of the genomes was measured using parsimony scores and retention indices. The ancestral functional profiles at the internal nodes of the phylogenetic tree were reconstructed to track the gains and losses of metabolic pathways in evolutionary history. In conclusion, our functional phylogenomics analysis shows divergent functional profiles of taxa and clades. Such function-phylogeny correlation stems from a set of clade-specific cellular functions with low parsimony scores. On the other hand, many cellular functions are sparsely dispersed across many clades with high parsimony scores. These different types of cellular functions have distinct evolutionary patterns reconstructed from the prokaryotic tree.« less

Optimum sensitivity derivatives of objective functions in nonlinear programming

NASA Technical Reports Server (NTRS)

Barthelemy, J.-F. M.; Sobieszczanski-Sobieski, J.

1983-01-01

The feasibility of eliminating second derivatives from the input of optimum sensitivity analyses of optimization problems is demonstrated. This elimination restricts the sensitivity analysis to the first-order sensitivity derivatives of the objective function. It is also shown that when a complete first-order sensitivity analysis is performed, second-order sensitivity derivatives of the objective function are available at little additional cost. An expression is derived whose application to linear programming is presented.

Analysis of sequence repeats of proteins in the PDB.

PubMed

Mary Rajathei, David; Selvaraj, Samuel

2013-12-01

Internal repeats in protein sequences play a significant role in the evolution of protein structure and function. Applications of different bioinformatics tools help in the identification and characterization of these repeats. In the present study, we analyzed sequence repeats in a non-redundant set of proteins available in the Protein Data Bank (PDB). We used RADAR for detecting internal repeats in a protein, PDBeFOLD for assessing structural similarity, PDBsum for finding functional involvement and Pfam for domain assignment of the repeats in a protein. Through the analysis of sequence repeats, we found that identity of the sequence repeats falls in the range of 20-40% and, the superimposed structures of the most of the sequence repeats maintain similar overall folding. Analysis sequence repeats at the functional level reveals that most of the sequence repeats are involved in the function of the protein through functionally involved residues in the repeat regions. We also found that sequence repeats in single and two domain proteins often contained conserved sequence motifs for the function of the domain. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of Activity-based Cost Functions for Cellulase, Invertase, and Other Enzymes

NASA Astrophysics Data System (ADS)

Stowers, Chris C.; Ferguson, Elizabeth M.; Tanner, Robert D.

As enzyme chemistry plays an increasingly important role in the chemical industry, cost analysis of these enzymes becomes a necessity. In this paper, we examine the aspects that affect the cost of enzymes based upon enzyme activity. The basis for this study stems from a previously developed objective function that quantifies the tradeoffs in enzyme purification via the foam fractionation process (Cherry et al., Braz J Chem Eng 17:233-238, 2000). A generalized cost function is developed from our results that could be used to aid in both industrial and lab scale chemical processing. The generalized cost function shows several nonobvious results that could lead to significant savings. Additionally, the parameters involved in the operation and scaling up of enzyme processing could be optimized to minimize costs. We show that there are typically three regimes in the enzyme cost analysis function: the low activity prelinear region, the moderate activity linear region, and high activity power-law region. The overall form of the cost analysis function appears to robustly fit the power law form.

Progressing from initially ambiguous functional analyses: three case examples.

PubMed

Tiger, Jeffrey H; Fisher, Wayne W; Toussaint, Karen A; Kodak, Tiffany

2009-01-01

Most often functional analyses are initiated using a standard set of test conditions, similar to those described by Iwata, Dorsey, Slifer, Bauman, and Richman [Iwata, B. A., Dorsey, M. F., Slifer, K. J., Bauman, K. E., & Richman, G. S. (1994). Toward a functional analysis of self-injury. Journal of Applied Behavior Analysis, 27, 197-209 (Reprinted from Analysis and Intervention in Developmental Disabilities, 2, 3-20, 1982)]. These test conditions involve the careful manipulation of motivating operations, discriminative stimuli, and reinforcement contingencies to determine the events related to the occurrence and maintenance of problem behavior. Some individuals display problem behavior that is occasioned and reinforced by idiosyncratic or otherwise unique combinations of environmental antecedents and consequences of behavior, which are unlikely to be detected using these standard assessment conditions. For these individuals, modifications to the standard test conditions or the inclusion of novel test conditions may result in clearer assessment outcomes. The current study provides three case examples of individuals whose functional analyses were initially undifferentiated; however, modifications to the standard conditions resulted in the identification of behavioral functions and the implementation of effective function-based treatments.

Opportunities and methodological challenges in EEG and MEG resting state functional brain network research.

PubMed

van Diessen, E; Numan, T; van Dellen, E; van der Kooi, A W; Boersma, M; Hofman, D; van Lutterveld, R; van Dijk, B W; van Straaten, E C W; Hillebrand, A; Stam, C J

2015-08-01

Electroencephalogram (EEG) and magnetoencephalogram (MEG) recordings during resting state are increasingly used to study functional connectivity and network topology. Moreover, the number of different analysis approaches is expanding along with the rising interest in this research area. The comparison between studies can therefore be challenging and discussion is needed to underscore methodological opportunities and pitfalls in functional connectivity and network studies. In this overview we discuss methodological considerations throughout the analysis pipeline of recording and analyzing resting state EEG and MEG data, with a focus on functional connectivity and network analysis. We summarize current common practices with their advantages and disadvantages; provide practical tips, and suggestions for future research. Finally, we discuss how methodological choices in resting state research can affect the construction of functional networks. When taking advantage of current best practices and avoid the most obvious pitfalls, functional connectivity and network studies can be improved and enable a more accurate interpretation and comparison between studies. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Characteristics of locomotion, muscle strength, and muscle tissue in regenerating rat skeletal muscles.

PubMed

Iwata, Akira; Fuchioka, Satoshi; Hiraoka, Koichi; Masuhara, Mitsuhiko; Kami, Katsuya

2010-05-01

Although numerous studies have aimed to elucidate the mechanisms used to repair the structure and function of injured skeletal muscles, it remains unclear how and when movement recovers following damage. We performed a temporal analysis to characterize the changes in movement, muscle function, and muscle structure after muscle injury induced by the drop-mass technique. At each time-point, movement recovery was determined by ankle kinematic analysis of locomotion, and functional recovery was represented by isometric force. As a histological analysis, the cross-sectional area of myotubes was measured to examine structural regeneration. The dorsiflexion angle of the ankle, as assessed by kinematic analysis of locomotion, increased after injury and then returned to control levels by day 14 post-injury. The isometric force returned to normal levels by day 21 post-injury. However, the size of the myotubes did not reach normal levels, even at day 21 post-injury. These results indicate that recovery of locomotion occurs prior to recovery of isometric force and that functional recovery occurs earlier than structural regeneration. Thus, it is suggested that recovery of the movement and function of injured skeletal muscles might be insufficient as markers for estimating the degree of neuromuscular system reconstitution.

Methods to evaluate functional nerve recovery in adult rats: walking track analysis, video analysis and the withdrawal reflex.

PubMed

Dijkstra, J R; Meek, M F; Robinson, P H; Gramsbergen, A

2000-03-15

The aim of this study was to compare different methods for the evaluation of functional nerve recovery. Three groups of adult male Wistar rats were studied. In group A, a 12-mm gap between nerve ends was bridged by an autologous nerve graft; in rats of group B we performed a crush lesion of the sciatic nerve and group C consisted of non-operated control rats. The withdrawal reflex, elicited by an electric stimulus, was used to evaluate the recovery of sensory nerve function. To investigate motor nerve recovery we analyzed the walking pattern. Three different methods were used to obtain data for footprint analysis: photographic paper with thickened film developer on the paws, normal white paper with finger paint, and video recordings. The footprints were used to calculate the sciatic function index (SFI). From the video recordings, we also analyzed stepcycles. The withdrawal reflex is a convenient and reproducible test for the evaluation of global sensory nerve recovery. Recording walking movements on video and the analysis of footplacing is a perfect although time-consuming method for the evaluation of functional aspects of motor nerve recovery.

Growth Type and Functional Trajectories: An Empirical Study of Urban Expansion in Nanjing, China

PubMed Central

Yuan, Feng

2016-01-01

Drawing upon the Landsat satellite images of Nanjing from 1985, 1995, 2001, 2007, and 2013, this paper integrates the convex hull analysis and common edge analysis at double scales, and develops a comprehensive matrix analysis to distinguish the different types of urban land expansion. The results show that Nanjing experienced rapid urban expansion, dominated by a mix of residential and manufacturing land from 1985 to 2013, which in turn has promoted Nanjing’s shift from a compact mononuclear city to a polycentric one. Spatial patterns of three specific types of growth, namely infilling, extension, and enclave were quite different in four consecutive periods. These patterns result primarily from the existing topographic constraints, as well as government-oriented urban planning and policies. By intersecting the function maps, we also reveal the functional evolution of newly-developed urban land. Moreover, both self-enhancing and mutual promotion of the newly developed functions are surveyed over the last decade. Our study confirms that the integration of a multi-scale method and multi-perspective analysis, such as the spatiotemporal patterns and functional evolution, helps us to better understand the rapid urban growth in China. PMID:26845155

Advanced functionality for radio analysis in the Offline software framework of the Pierre Auger Observatory

NASA Astrophysics Data System (ADS)

Abreu, P.; Aglietta, M.; Ahn, E. J.; Albuquerque, I. F. M.; Allard, D.; Allekotte, I.; Allen, J.; Allison, P.; Alvarez Castillo, J.; Alvarez-Muñiz, J.; Ambrosio, M.; Aminaei, A.; Anchordoqui, L.; Andringa, S.; Antičić, T.; Aramo, C.; Arganda, E.; Arqueros, F.; Asorey, H.; Assis, P.; Aublin, J.; Ave, M.; Avenier, M.; Avila, G.; Bäcker, T.; Balzer, M.; Barber, K. B.; Barbosa, A. F.; Bardenet, R.; Barroso, S. L. C.; Baughman, B.; Beatty, J. J.; Becker, B. R.; Becker, K. H.; Bellido, J. A.; Benzvi, S.; Berat, C.; Bertou, X.; Biermann, P. L.; Billoir, P.; Blanco, F.; Blanco, M.; Bleve, C.; Blümer, H.; Boháčová, M.; Boncioli, D.; Bonifazi, C.; Bonino, R.; Borodai, N.; Brack, J.; Brogueira, P.; Brown, W. C.; Bruijn, R.; Buchholz, P.; Bueno, A.; Burton, R. E.; Caballero-Mora, K. S.; Caramete, L.; Caruso, R.; Castellina, A.; Cataldi, G.; Cazon, L.; Cester, R.; Chauvin, J.; Chiavassa, A.; Chinellato, J. A.; Chou, A.; Chudoba, J.; Clay, R. W.; Coluccia, M. R.; Conceição, R.; Contreras, F.; Cook, H.; Cooper, M. J.; Coppens, J.; Cordier, A.; Cotti, U.; Coutu, S.; Covault, C. E.; Creusot, A.; Criss, A.; Cronin, J.; Curutiu, A.; Dagoret-Campagne, S.; Dallier, R.; Dasso, S.; Daumiller, K.; Dawson, B. R.; de Almeida, R. M.; de Domenico, M.; de Donato, C.; de Jong, S. J.; de La Vega, G.; de Mello Junior, W. J. M.; de Mello Neto, J. R. T.; de Mitri, I.; de Souza, V.; de Vries, K. D.; Decerprit, G.; Del Peral, L.; Deligny, O.; Dembinski, H.; Denkiewicz, A.; di Giulio, C.; Diaz, J. C.; Díaz Castro, M. L.; Diep, P. N.; Dobrigkeit, C.; D'Olivo, J. C.; Dong, P. N.; Dorofeev, A.; Dos Anjos, J. C.; Dova, M. T.; D'Urso, D.; Dutan, I.; Ebr, J.; Engel, R.; Erdmann, M.; Escobar, C. O.; Etchegoyen, A.; Facal San Luis, P.; Falcke, H.; Farrar, G.; Fauth, A. C.; Fazzini, N.; Ferguson, A. P.; Ferrero, A.; Fick, B.; Filevich, A.; Filipčič, A.; Fliescher, S.; Fracchiolla, C. E.; Fraenkel, E. D.; Fröhlich, U.; Fuchs, B.; Gamarra, R. F.; Gambetta, S.; García, B.; García Gámez, D.; Garcia-Pinto, D.; Gascon, A.; Gemmeke, H.; Gesterling, K.; Ghia, P. L.; Giaccari, U.; Giller, M.; Glass, H.; Gold, M. S.; Golup, G.; Gomez Albarracin, F.; Gómez Berisso, M.; Gonçalves, P.; Gonzalez, D.; Gonzalez, J. G.; Gookin, B.; Góra, D.; Gorgi, A.; Gouffon, P.; Gozzini, S. R.; Grashorn, E.; Grebe, S.; Griffith, N.; Grigat, M.; Grillo, A. F.; Guardincerri, Y.; Guarino, F.; Guedes, G. P.; Hague, J. D.; Hansen, P.; Harari, D.; Harmsma, S.; Harton, J. L.; Haungs, A.; Hebbeker, T.; Heck, D.; Herve, A. E.; Hojvat, C.; Holmes, V. C.; Homola, P.; Hörandel, J. R.; Horneffer, A.; Hrabovský, M.; Huege, T.; Insolia, A.; Ionita, F.; Italiano, A.; Jiraskova, S.; Kadija, K.; Kampert, K. H.; Karhan, P.; Karova, T.; Kasper, P.; Kégl, B.; Keilhauer, B.; Keivani, A.; Kelley, J. L.; Kemp, E.; Kieckhafer, R. M.; Klages, H. O.; Kleifges, M.; Kleinfeller, J.; Knapp, J.; Koang, D.-H.; Kotera, K.; Krohm, N.; Krömer, O.; Kruppke-Hansen, D.; Kuehn, F.; Kuempel, D.; Kulbartz, J. K.; Kunka, N.; La Rosa, G.; Lachaud, C.; Lautridou, P.; Leão, M. S. A. B.; Lebrun, D.; Lebrun, P.; Leigui de Oliveira, M. A.; Lemiere, A.; Letessier-Selvon, A.; Lhenry-Yvon, I.; Link, K.; López, R.; Lopez Agüera, A.; Louedec, K.; Lozano Bahilo, J.; Lucero, A.; Ludwig, M.; Lyberis, H.; Macolino, C.; Maldera, S.; Mandat, D.; Mantsch, P.; Mariazzi, A. G.; Marin, V.; Maris, I. C.; Marquez Falcon, H. R.; Marsella, G.; Martello, D.; Martin, L.; Martínez Bravo, O.; Mathes, H. J.; Matthews, J.; Matthews, J. A. J.; Matthiae, G.; Maurizio, D.; Mazur, P. O.; Medina-Tanco, G.; Melissas, M.; Melo, D.; Menichetti, E.; Menshikov, A.; Mertsch, P.; Meurer, C.; Mićanović, S.; Micheletti, M. I.; Miller, W.; Miramonti, L.; Mollerach, S.; Monasor, M.; Monnier Ragaigne, D.; Montanet, F.; Morales, B.; Morello, C.; Moreno, E.; Moreno, J. C.; Morris, C.; Mostafá, M.; Moura, C. A.; Mueller, S.; Muller, M. A.; Müller, G.; Münchmeyer, M.; Mussa, R.; Navarra, G.; Navarro, J. L.; Navas, S.; Necesal, P.; Nellen, L.; Nelles, A.; Nhung, P. T.; Nierstenhoefer, N.; Nitz, D.; Nosek, D.; Nožka, L.; Nyklicek, M.; Oehlschläger, J.; Olinto, A.; Oliva, P.; Olmos-Gilbaja, V. M.; Ortiz, M.; Pacheco, N.; Pakk Selmi-Dei, D.; Palatka, M.; Pallotta, J.; Palmieri, N.; Parente, G.; Parizot, E.; Parra, A.; Parrisius, J.; Parsons, R. D.; Pastor, S.; Paul, T.; Pech, M.; PeĶala, J.; Pelayo, R.; Pepe, I. M.; Perrone, L.; Pesce, R.; Petermann, E.; Petrera, S.; Petrinca, P.; Petrolini, A.; Petrov, Y.; Petrovic, J.; Pfendner, C.; Phan, N.; Piegaia, R.; Pierog, T.; Pieroni, P.; Pimenta, M.; Pirronello, V.; Platino, M.; Ponce, V. H.; Pontz, M.; Privitera, P.; Prouza, M.; Quel, E. J.; Rautenberg, J.; Ravel, O.; Ravignani, D.; Revenu, B.; Ridky, J.; Risse, M.; Ristori, P.; Rivera, H.; Riviére, C.; Rizi, V.; Robledo, C.; Rodrigues de Carvalho, W.; Rodriguez, G.; Rodriguez Martino, J.; Rodriguez Rojo, J.; Rodriguez-Cabo, I.; Rodríguez-Frías, M. D.; Ros, G.; Rosado, J.; Rossler, T.; Roth, M.; Rouillé-D'Orfeuil, B.; Roulet, E.; Rovero, A. C.; Rühle, C.; Salamida, F.; Salazar, H.; Salina, G.; Sánchez, F.; Santander, M.; Santo, C. E.; Santos, E.; Santos, E. M.; Sarazin, F.; Sarkar, S.; Sato, R.; Scharf, N.; Scherini, V.; Schieler, H.; Schiffer, P.; Schmidt, A.; Schmidt, F.; Schmidt, T.; Scholten, O.; Schoorlemmer, H.; Schovancova, J.; Schovánek, P.; Schroeder, F.; Schulte, S.; Schuster, D.; Sciutto, S. J.; Scuderi, M.; Segreto, A.; Semikoz, D.; Settimo, M.; Shadkam, A.; Shellard, R. C.; Sidelnik, I.; Sigl, G.; Śmiałkowski, A.; Šmída, R.; Snow, G. R.; Sommers, P.; Sorokin, J.; Spinka, H.; Squartini, R.; Stapleton, J.; Stasielak, J.; Stephan, M.; Stutz, A.; Suarez, F.; Suomijärvi, T.; Supanitsky, A. D.; Šuša, T.; Sutherland, M. S.; Swain, J.; Szadkowski, Z.; Szuba, M.; Tamashiro, A.; Tapia, A.; Taşcău, O.; Tcaciuc, R.; Tegolo, D.; Thao, N. T.; Thomas, D.; Tiffenberg, J.; Timmermans, C.; Tiwari, D. K.; Tkaczyk, W.; Todero Peixoto, C. J.; Tomé, B.; Tonachini, A.; Travnicek, P.; Tridapalli, D. B.; Tristram, G.; Trovato, E.; Tueros, M.; Ulrich, R.; Unger, M.; Urban, M.; Valdés Galicia, J. F.; Valiño, I.; Valore, L.; van den Berg, A. M.; Vargas Cárdenas, B.; Vázquez, J. R.; Vázquez, R. A.; Veberič, D.; Verzi, V.; Videla, M.; Villaseñor, L.; Wahlberg, H.; Wahrlich, P.; Wainberg, O.; Warner, D.; Watson, A. A.; Weber, M.; Weidenhaupt, K.; Weindl, A.; Westerhoff, S.; Whelan, B. J.; Wieczorek, G.; Wiencke, L.; Wilczyńska, B.; Wilczyński, H.; Will, M.; Williams, C.; Winchen, T.; Winders, L.; Winnick, M. G.; Wommer, M.; Wundheiler, B.; Yamamoto, T.; Younk, P.; Yuan, G.; Zamorano, B.; Zas, E.; Zavrtanik, D.; Zavrtanik, M.; Zaw, I.; Zepeda, A.; Ziolkowski, M.

2011-04-01

The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs “radio-hybrid” measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluorescence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features of the radio extension implemented in the Auger Offline framework. Its functionality has achieved a high degree of sophistication and offers advanced features such as vectorial reconstruction of the electric field, advanced signal processing algorithms, a transparent and efficient handling of FFTs, a very detailed simulation of detector effects, and the read-in of multiple data formats including data from various radio simulation codes. The source code of this radio functionality can be made available to interested parties on request.

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Resting state network topology of the ferret brain.

PubMed

Zhou, Zhe Charles; Salzwedel, Andrew P; Radtke-Schuller, Susanne; Li, Yuhui; Sellers, Kristin K; Gilmore, John H; Shih, Yen-Yu Ian; Fröhlich, Flavio; Gao, Wei

2016-12-01

Resting state functional magnetic resonance imaging (rsfMRI) has emerged as a versatile tool for non-invasive measurement of functional connectivity patterns in the brain. RsfMRI brain dynamics in rodents, non-human primates, and humans share similar properties; however, little is known about the resting state functional connectivity patterns in the ferret, an animal model with high potential for developmental and cognitive translational study. To address this knowledge-gap, we performed rsfMRI on anesthetized ferrets using a 9.4T MRI scanner, and subsequently performed group-level independent component analysis (gICA) to identify functionally connected brain networks. Group-level ICA analysis revealed distributed sensory, motor, and higher-order networks in the ferret brain. Subsequent connectivity analysis showed interconnected higher-order networks that constituted a putative default mode network (DMN), a network that exhibits altered connectivity in neuropsychiatric disorders. Finally, we assessed ferret brain topological efficiency using graph theory analysis and found that the ferret brain exhibits small-world properties. Overall, these results provide additional evidence for pan-species resting-state networks, further supporting ferret-based studies of sensory and cognitive function. Copyright © 2016 Elsevier Inc. All rights reserved.

Comments on Skinner's grammar

PubMed Central

Mabry, John H.

1993-01-01

The strong tradition of “school room” grammars may have had a negative influence on the reception given a functional analysis of verbal behavior, both within and without the field of behavior analysis. Some of the failings of those traditional grammars, and their largely prescriptive nature were outlined through reference to other critics, and conflicting views. Skinner's own treatment of grammatical issues was presented, emphasizing his view of a functional unit and his use of the autoclitic and intraverbal functions to describe alternatives to a formal or structural analysis. Finally, the relevance of stimulus control variables to some recurring questions about verbal behavior and, specifically grammar, were mentioned. PMID:22477082

SASS wind ambiguity removal by direct minimization. II - Use of smoothness and dynamical constraints

NASA Technical Reports Server (NTRS)

Hoffman, R. N.

1984-01-01

A variational analysis method (VAM) is used to remove the ambiguity of the Seasat-A Satellite Scatterometer (SASS) winds. The VAM yields the best fit to the data by minimizing an objective function S which is a measure of the lack of fit. The SASS data are described and the function S and the analysis procedure are defined. Analyses of a single ship report which are analogous to Green's functions are presented. The analysis procedure is tuned and its sensitivity is described using the QE II storm. The procedure is then applied to a case study of September 6, 1978, south of Japan.

Bragg-cell receiver study

NASA Technical Reports Server (NTRS)

Wilson, Lonnie A.

1987-01-01

Bragg-cell receivers are employed in specialized Electronic Warfare (EW) applications for the measurement of frequency. Bragg-cell receiver characteristics are fully characterized for simple RF emitter signals. This receiver is early in its development cycle when compared to the IFM receiver. Functional mathematical models are derived and presented in this report for the Bragg-cell receiver. Theoretical analysis is presented and digital computer signal processing results are presented for the Bragg-cell receiver. Probability density function analysis are performed for output frequency. Probability density function distributions are observed to depart from assumed distributions for wideband and complex RF signals. This analysis is significant for high resolution and fine grain EW Bragg-cell receiver systems.

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

NASA Technical Reports Server (NTRS)

Carter, M. C.; Madison, M. W.

1973-01-01

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

Soybean kinome: functional classification and gene expression patterns

PubMed Central

Liu, Jinyi; Chen, Nana; Grant, Joshua N.; Cheng, Zong-Ming (Max); Stewart, C. Neal; Hewezi, Tarek

2015-01-01

The protein kinase (PK) gene family is one of the largest and most highly conserved gene families in plants and plays a role in nearly all biological functions. While a large number of genes have been predicted to encode PKs in soybean, a comprehensive functional classification and global analysis of expression patterns of this large gene family is lacking. In this study, we identified the entire soybean PK repertoire or kinome, which comprised 2166 putative PK genes, representing 4.67% of all soybean protein-coding genes. The soybean kinome was classified into 19 groups, 81 families, and 122 subfamilies. The receptor-like kinase (RLK) group was remarkably large, containing 1418 genes. Collinearity analysis indicated that whole-genome segmental duplication events may have played a key role in the expansion of the soybean kinome, whereas tandem duplications might have contributed to the expansion of specific subfamilies. Gene structure, subcellular localization prediction, and gene expression patterns indicated extensive functional divergence of PK subfamilies. Global gene expression analysis of soybean PK subfamilies revealed tissue- and stress-specific expression patterns, implying regulatory functions over a wide range of developmental and physiological processes. In addition, tissue and stress co-expression network analysis uncovered specific subfamilies with narrow or wide interconnected relationships, indicative of their association with particular or broad signalling pathways, respectively. Taken together, our analyses provide a foundation for further functional studies to reveal the biological and molecular functions of PKs in soybean. PMID:25614662

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Factors Associated with Postpartum Maternal Functioning in Women with Positive Screens for Depression.

PubMed

Barkin, Jennifer L; Wisner, Katherine L; Bromberger, Joyce T; Beach, Scott R; Wisniewski, Stephen R

2016-07-01

Functional assessment may represent a valuable addition to postpartum depression screening, providing a more thorough characterization of the mother's health and quality of life. To the authors' knowledge, this analysis represents the first examination of postpartum maternal functioning, as measured by a patient-centered validated tool aimed at ascertainment of functional status explicitly, and its clinical and sociodemographic correlates. A total of 189 women recruited from a large, urban women's hospital in the northeastern United States who both (1) screened positive for depression between 4 and 6 weeks postpartum and (2) completed a subsequent home (baseline) visit between October 1, 2008, and September 4, 2009, were included in this analysis. Multiple linear regression was conducted to ascertain which clinical and sociodemographic variables were independently associated with maternal functioning. The multivariate analysis revealed independent associations between bipolar status, atypical depression, depression score (17-item Hamilton Rating Scale for Depression), and insurance type with postpartum maternal functioning. The beta coefficient for bipolar status indicates that on average we would expect those with bipolar disorder to have maternal functioning scores that are 5.6 points less than those without bipolar disorder. Healthcare providers treating postpartum women with complicating mental health conditions should be cognizant of the potential ramifications on maternal functioning. Impaired functioning in the maternal role is likely to impact child development, although the precise nature of this relationship is yet to be elucidated.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

MaxEnt, second variation, and generalized statistics

NASA Astrophysics Data System (ADS)

Plastino, A.; Rocca, M. C.

2015-10-01

There are two kinds of Tsallis-probability distributions: heavy tail ones and compact support distributions. We show here, by appeal to functional analysis' tools, that for lower bound Hamiltonians, the second variation's analysis of the entropic functional guarantees that the heavy tail q-distribution constitutes a maximum of Tsallis' entropy. On the other hand, in the compact support instance, a case by case analysis is necessary in order to tackle the issue.

The Shock and Vibration Digest. Volume 14, Number 8

DTIC Science & Technology

1982-08-01

generating interest in averaged transfer functions. Broadband transfer functions are derived using the methods of statistical energy analysis (SEA...Accelerometer, Endevco Corp., San Juan Capis- trano,CA(1982). 7. Lyon, R.H., Statistical Energy Analysis of Dy- namical Systems, MIT Press, Cambridge, MA...A fairly new technique known as statistical energy analysis , or SEA, [35-44] has been useful for many problems of noise transmission. The difficulty

Project FAST: [Functional Analysis Systems Training]: Adopter/Facilitator Information.

ERIC Educational Resources Information Center

Essexville-Hampton Public Schools, MI.

Presented is adopter/facilitator information of Project FAST (Functional Analysis Systems Training) to provide educational and support services to learning disordered children and their regular elementary teachers. Briefly described are the three schools in the Essexville-Hampton (Michigan) school district; objectives of the program; program…

Stylistic Patterns in Language Teaching Research Articles: A Multidimensional Analysis

ERIC Educational Resources Information Center

Kitjaroenpaiboon, Woravit; Getkham, Kanyarat

2016-01-01

This paper presents the results of a multidimensional analysis to investigate stylistic patterns and their communicative functions in language teaching research articles. The findings were that language teaching research articles contained six stylistic patterns and communicative functions. Pattern I consisted of seven salient positive features…

Functional Analysis and Treatment of Noncompliance by Preschool Children

ERIC Educational Resources Information Center

Wilder, David A.; Harris, Carelle; Reagan, Renee; Rasey, Amy

2007-01-01

A functional analysis showed that noncompliance occurred most often for 2 preschoolers when it resulted in termination of a preferred activity, suggesting that noncompliance was maintained by positive reinforcement. A differential reinforcement procedure, which involved contingent access to coupons that could be exchanged for uninterrupted access…

77 FR 65913 - Privacy Act of 1974: Systems of Records.

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-31

... performing clerical, stenographic, or data analysis functions, or by reproduction of records by electronic or... performing clerical, stenographic, or data analysis functions, or by reproduction of records by electronic or... Services (OGIS) National Archives and Records Administration, in connection with mediation of FOIA requests...

Hand function evaluation: a factor analysis study.

PubMed

Jarus, T; Poremba, R

1993-05-01

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

Probing the Xenopus laevis inner ear transcriptome for biological function

PubMed Central

2012-01-01

Background The senses of hearing and balance depend upon mechanoreception, a process that originates in the inner ear and shares features across species. Amphibians have been widely used for physiological studies of mechanotransduction by sensory hair cells. In contrast, much less is known of the genetic basis of auditory and vestibular function in this class of animals. Among amphibians, the genus Xenopus is a well-characterized genetic and developmental model that offers unique opportunities for inner ear research because of the amphibian capacity for tissue and organ regeneration. For these reasons, we implemented a functional genomics approach as a means to undertake a large-scale analysis of the Xenopus laevis inner ear transcriptome through microarray analysis. Results Microarray analysis uncovered genes within the X. laevis inner ear transcriptome associated with inner ear function and impairment in other organisms, thereby supporting the inclusion of Xenopus in cross-species genetic studies of the inner ear. The use of gene categories (inner ear tissue; deafness; ion channels; ion transporters; transcription factors) facilitated the assignment of functional significance to probe set identifiers. We enhanced the biological relevance of our microarray data by using a variety of curation approaches to increase the annotation of the Affymetrix GeneChip® Xenopus laevis Genome array. In addition, annotation analysis revealed the prevalence of inner ear transcripts represented by probe set identifiers that lack functional characterization. Conclusions We identified an abundance of targets for genetic analysis of auditory and vestibular function. The orthologues to human genes with known inner ear function and the highly expressed transcripts that lack annotation are particularly interesting candidates for future analyses. We used informatics approaches to impart biologically relevant information to the Xenopus inner ear transcriptome, thereby addressing the impediment imposed by insufficient gene annotation. These findings heighten the relevance of Xenopus as a model organism for genetic investigations of inner ear organogenesis, morphogenesis, and regeneration. PMID:22676585

A confirmative clinimetric analysis of the 36-item Family Assessment Device.

PubMed

Timmerby, Nina; Cosci, Fiammetta; Watson, Maggie; Csillag, Claudio; Schmitt, Florence; Steck, Barbara; Bech, Per; Thastum, Mikael

2018-02-07

The Family Assessment Device (FAD) is a 60-item questionnaire widely used to evaluate self-reported family functioning. However, the factor structure as well as the number of items has been questioned. A shorter and more user-friendly version of the original FAD-scale, the 36-item FAD, has therefore previously been proposed, based on findings in a nonclinical population of adults. We aimed in this study to evaluate the brief 36-item version of the FAD in a clinical population. Data from a European multinational study, examining factors associated with levels of family functioning in adult cancer patients' families, were used. Both healthy and ill parents completed the 60-item version FAD. The psychometric analyses conducted were Principal Component Analysis and Mokken-analysis. A total of 564 participants were included. Based on the psychometric analysis we confirmed that the 36-item version of the FAD has robust psychometric properties and can be used in clinical populations. The present analysis confirmed that the 36-item version of the FAD (18 items assessing 'well-being' and 18 items assessing 'dysfunctional' family function) is a brief scale where the summed total score is a valid measure of the dimensions of family functioning. This shorter version of the FAD is, in accordance with the concept of 'measurement-based care', an easy to use scale that could be considered when the aim is to evaluate self-reported family functioning.

A Reverse-Genetics Mutational Analysis of the Barley HvDWARF Gene Results in Identification of a Series of Alleles and Mutants with Short Stature of Various Degree and Disturbance in BR Biosynthesis Allowing a New Insight into the Process.

PubMed

Gruszka, Damian; Gorniak, Malgorzata; Glodowska, Ewelina; Wierus, Ewa; Oklestkova, Jana; Janeczko, Anna; Maluszynski, Miroslaw; Szarejko, Iwona

2016-04-22

Brassinosteroids (BRs) are plant steroid hormones, regulating a broad range of physiological processes. The largest amount of data related with BR biosynthesis has been gathered in Arabidopsis thaliana, however understanding of this process is far less elucidated in monocot crops. Up to now, only four barley genes implicated in BR biosynthesis have been identified. Two of them, HvDWARF and HvBRD, encode BR-6-oxidases catalyzing biosynthesis of castasterone, but their relation is not yet understood. In the present study, the identification of the HvDWARF genomic sequence, its mutational and functional analysis and characterization of new mutants are reported. Various types of mutations located in different positions within functional domains were identified and characterized. Analysis of their impact on phenotype of the mutants was performed. The identified homozygous mutants show reduced height of various degree and disrupted skotomorphogenesis. Mutational analysis of the HvDWARF gene with the "reverse genetics" approach allowed for its detailed functional analysis at the level of protein functional domains. The HvDWARF gene function and mutants' phenotypes were also validated by measurement of endogenous BR concentration. These results allowed a new insight into the BR biosynthesis in barley.

Investigation of continuous effect modifiers in a meta-analysis on higher versus lower PEEP in patients requiring mechanical ventilation--protocol of the ICEM study.

PubMed

Kasenda, Benjamin; Sauerbrei, Willi; Royston, Patrick; Briel, Matthias

2014-05-20

Categorizing an inherently continuous predictor in prognostic analyses raises several critical methodological issues: dependence of the statistical significance on the number and position of the chosen cut-point(s), loss of statistical power, and faulty interpretation of the results if a non-linear association is incorrectly assumed to be linear. This also applies to a therapeutic context where investigators of randomized clinical trials (RCTs) are interested in interactions between treatment assignment and one or more continuous predictors. Our goal is to apply the multivariable fractional polynomial interaction (MFPI) approach to investigate interactions between continuous patient baseline variables and the allocated treatment in an individual patient data meta-analysis of three RCTs (N = 2,299) from the intensive care field. For each study, MFPI will provide a continuous treatment effect function. Functions from each of the three studies will be averaged by a novel meta-analysis approach for functions. We will plot treatment effect functions separately for each study and also the averaged function. The averaged function with a related confidence interval will provide a suitable basis to assess whether a continuous patient characteristic modifies the treatment comparison and may be relevant for clinical decision-making. The compared interventions will be a higher or lower positive end-expiratory pressure (PEEP) ventilation strategy in patients requiring mechanical ventilation. The continuous baseline variables body mass index, PaO2/FiO2, respiratory compliance, and oxygenation index will be the investigated potential effect modifiers. Clinical outcomes for this analysis will be in-hospital mortality, time to death, time to unassisted breathing, and pneumothorax. This project will be the first meta-analysis to combine continuous treatment effect functions derived by the MFPI procedure separately in each of several RCTs. Such an approach requires individual patient data (IPD). They are available from an earlier IPD meta-analysis using different methods for analysis. This new analysis strategy allows assessing whether treatment effects interact with continuous baseline patient characteristics and avoids categorization-based subgroup analyses. These interaction analyses of the present study will be exploratory in nature. However, they may help to foster future research using the MFPI approach to improve interaction analyses of continuous predictors in RCTs and IPD meta-analyses. This study is registered in PROSPERO (CRD42012003129).

Understanding PGM-free Catalysts by Linking Density Functional Theory Calculations and Structural Analysis: Perspectives and Challenges

DOE PAGES

Gonzales, Ivana; Artyushkova, Kateryna; Atanassov, Plamen

2018-03-13

Here, we discuss perspectives and challenges in applying density functional theory for the calculation of spectroscopic properties of platinum group metal (PGM)-free electrocatalysts for oxygen reduction. More specifically, we discuss recent advances in the density functional theory calculations of core-level shifts in binding energies of N 1s electrons as measured by X-ray photoelectron spectroscopy. The link between the density functional theory calculations, the electrocatalytic performance of the catalysts, and structural analysis using modern spectroscopic techniques is expected to significantly increase our understanding of PGM-free catalysts at the molecular level.

Characterization of technical surfaces by structure function analysis

NASA Astrophysics Data System (ADS)

Kalms, Michael; Kreis, Thomas; Bergmann, Ralf B.

2018-03-01

The structure function is a tool for characterizing technical surfaces that exhibits a number of advantages over Fourierbased analysis methods. So it is optimally suited for analyzing the height distributions of surfaces measured by full-field non-contacting methods. The structure function is thus a useful method to extract global or local criteria like e. g. periodicities, waviness, lay, or roughness to analyze and evaluate technical surfaces. After the definition of line- and area-structure function and offering effective procedures for their calculation this paper presents examples using simulated and measured data of technical surfaces including aircraft parts.

Understanding PGM-free Catalysts by Linking Density Functional Theory Calculations and Structural Analysis: Perspectives and Challenges

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

Gonzales, Ivana; Artyushkova, Kateryna; Atanassov, Plamen

Here, we discuss perspectives and challenges in applying density functional theory for the calculation of spectroscopic properties of platinum group metal (PGM)-free electrocatalysts for oxygen reduction. More specifically, we discuss recent advances in the density functional theory calculations of core-level shifts in binding energies of N 1s electrons as measured by X-ray photoelectron spectroscopy. The link between the density functional theory calculations, the electrocatalytic performance of the catalysts, and structural analysis using modern spectroscopic techniques is expected to significantly increase our understanding of PGM-free catalysts at the molecular level.

Genome-wide analysis of the Dof transcription factor gene family reveals soybean-specific duplicable and functional characteristics.

PubMed

Guo, Yong; Qiu, Li-Juan

2013-01-01

The Dof domain protein family is a classic plant-specific zinc-finger transcription factor family involved in a variety of biological processes. There is great diversity in the number of Dof genes in different plants. However, there are only very limited reports on the characterization of Dof transcription factors in soybean (Glycine max). In the present study, 78 putative Dof genes were identified from the whole-genome sequence of soybean. The predicted GmDof genes were non-randomly distributed within and across 19 out of 20 chromosomes and 97.4% (38 pairs) were preferentially retained duplicate paralogous genes located in duplicated regions of the genome. Soybean-specific segmental duplications contributed significantly to the expansion of the soybean Dof gene family. These Dof proteins were phylogenetically clustered into nine distinct subgroups among which the gene structure and motif compositions were considerably conserved. Comparative phylogenetic analysis of these Dof proteins revealed four major groups, similar to those reported for Arabidopsis and rice. Most of the GmDofs showed specific expression patterns based on RNA-seq data analyses. The expression patterns of some duplicate genes were partially redundant while others showed functional diversity, suggesting the occurrence of sub-functionalization during subsequent evolution. Comprehensive expression profile analysis also provided insights into the soybean-specific functional divergence among members of the Dof gene family. Cis-regulatory element analysis of these GmDof genes suggested diverse functions associated with different processes. Taken together, our results provide useful information for the functional characterization of soybean Dof genes by combining phylogenetic analysis with global gene-expression profiling.

NetGen: a novel network-based probabilistic generative model for gene set functional enrichment analysis.

PubMed

Sun, Duanchen; Liu, Yinliang; Zhang, Xiang-Sun; Wu, Ling-Yun

2017-09-21

High-throughput experimental techniques have been dramatically improved and widely applied in the past decades. However, biological interpretation of the high-throughput experimental results, such as differential expression gene sets derived from microarray or RNA-seq experiments, is still a challenging task. Gene Ontology (GO) is commonly used in the functional enrichment studies. The GO terms identified via current functional enrichment analysis tools often contain direct parent or descendant terms in the GO hierarchical structure. Highly redundant terms make users difficult to analyze the underlying biological processes. In this paper, a novel network-based probabilistic generative model, NetGen, was proposed to perform the functional enrichment analysis. An additional protein-protein interaction (PPI) network was explicitly used to assist the identification of significantly enriched GO terms. NetGen achieved a superior performance than the existing methods in the simulation studies. The effectiveness of NetGen was explored further on four real datasets. Notably, several GO terms which were not directly linked with the active gene list for each disease were identified. These terms were closely related to the corresponding diseases when accessed to the curated literatures. NetGen has been implemented in the R package CopTea publicly available at GitHub ( http://github.com/wulingyun/CopTea/ ). Our procedure leads to a more reasonable and interpretable result of the functional enrichment analysis. As a novel term combination-based functional enrichment analysis method, NetGen is complementary to current individual term-based methods, and can help to explore the underlying pathogenesis of complex diseases.

Dynamic physiological modeling for functional diffuse optical tomography

PubMed Central

Diamond, Solomon Gilbert; Huppert, Theodore J.; Kolehmainen, Ville; Franceschini, Maria Angela; Kaipio, Jari P.; Arridge, Simon R.; Boas, David A.

2009-01-01

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n = 10, P < 0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis. PMID:16242967

NbIT - A New Information Theory-Based Analysis of Allosteric Mechanisms Reveals Residues that Underlie Function in the Leucine Transporter LeuT

PubMed Central

LeVine, Michael V.; Weinstein, Harel

2014-01-01

Complex networks of interacting residues and microdomains in the structures of biomolecular systems underlie the reliable propagation of information from an input signal, such as the concentration of a ligand, to sites that generate the appropriate output signal, such as enzymatic activity. This information transduction often carries the signal across relatively large distances at the molecular scale in a form of allostery that is essential for the physiological functions performed by biomolecules. While allosteric behaviors have been documented from experiments and computation, the mechanism of this form of allostery proved difficult to identify at the molecular level. Here, we introduce a novel analysis framework, called N-body Information Theory (NbIT) analysis, which is based on information theory and uses measures of configurational entropy in a biomolecular system to identify microdomains and individual residues that act as (i)-channels for long-distance information sharing between functional sites, and (ii)-coordinators that organize dynamics within functional sites. Application of the new method to molecular dynamics (MD) trajectories of the occluded state of the bacterial leucine transporter LeuT identifies a channel of allosteric coupling between the functionally important intracellular gate and the substrate binding sites known to modulate it. NbIT analysis is shown also to differentiate residues involved primarily in stabilizing the functional sites, from those that contribute to allosteric couplings between sites. NbIT analysis of MD data thus reveals rigorous mechanistic elements of allostery underlying the dynamics of biomolecular systems. PMID:24785005

The Application of Nonstandard Analysis to the Study of Inviscid Shock Wave Jump Conditions

NASA Technical Reports Server (NTRS)

Farassat, F.; Baty, R. S.

1998-01-01

The use of conservation laws in nonconservative form for deriving shock jump conditions by Schwartz distribution theory leads to ambiguous products of generalized functions. Nonstandard analysis is used to define a class of Heaviside functions where the jump from zero to one occurs on an infinitesimal interval. These Heaviside functions differ by their microstructure near x = 0, i.e., by the nature of the rise within the infinitesimal interval it is shown that the conservation laws in nonconservative form can relate the different Heaviside functions used to define jumps in different flow parameters. There are no mathematical or logical ambiguities in the derivation of the jump conditions. An important result is that the microstructure of the Heaviside function of the jump in entropy has a positive peak greater than one within the infinitesimal interval where the jump occurs. This phenomena is known from more sophisticated studies of the structure of shock waves using viscous fluid assumption. However, the present analysis is simpler and more direct.

Radio-science performance analysis software

NASA Astrophysics Data System (ADS)

Morabito, D. D.; Asmar, S. W.

1995-02-01

The Radio Science Systems Group (RSSG) provides various support functions for several flight project radio-science teams. Among these support functions are uplink and sequence planning, real-time operations monitoring and support, data validation, archiving and distribution functions, and data processing and analysis. This article describes the support functions that encompass radio-science data performance analysis. The primary tool used by the RSSG to fulfill this support function is the STBLTY program set. STBLTY is used to reconstruct observable frequencies and calculate model frequencies, frequency residuals, frequency stability in terms of Allan deviation, reconstructed phase, frequency and phase power spectral density, and frequency drift rates. In the case of one-way data, using an ultrastable oscillator (USO) as a frequency reference, the program set computes the spacecraft transmitted frequency and maintains a database containing the in-flight history of the USO measurements. The program set also produces graphical displays. Some examples and discussions on operating the program set on Galileo and Ulysses data will be presented.

Radio-Science Performance Analysis Software

NASA Astrophysics Data System (ADS)

Morabito, D. D.; Asmar, S. W.

1994-10-01

The Radio Science Systems Group (RSSG) provides various support functions for several flight project radio-science teams. Among these support functions are uplink and sequence planning, real-time operations monitoring and support, data validation, archiving and distribution functions, and data processing and analysis. This article describes the support functions that encompass radio science data performance analysis. The primary tool used by the RSSG to fulfill this support function is the STBLTY program set. STBLTY is used to reconstruct observable frequencies and calculate model frequencies, frequency residuals, frequency stability in terms of Allan deviation, reconstructed phase, frequency and phase power spectral density, and frequency drift rates. In the case of one-way data, using an ultrastable oscillator (USO) as a frequency reference, the program set computes the spacecraft transmitted frequency and maintains a database containing the in-flight history of the USO measurements. The program set also produces graphical displays. Some examples and discussion on operating the program set on Galileo and Ulysses data will be presented.

A density difference based analysis of orbital-dependent exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Grabowski, Ireneusz; Teale, Andrew M.; Fabiano, Eduardo; Śmiga, Szymon; Buksztel, Adam; Della Sala, Fabio

2014-03-01

We present a density difference based analysis for a range of orbital-dependent Kohn-Sham functionals. Results for atoms, some members of the neon isoelectronic series and small molecules are reported and compared with ab initio wave function calculations. Particular attention is paid to the quality of approximations to the exchange-only optimised effective potential (OEP) approach: we consider both the localised Hartree-Fock as well as the Krieger-Li-Iafrate methods. Analysis of density differences at the exchange-only level reveals the impact of the approximations on the resulting electronic densities. These differences are further quantified in terms of the ground state energies, frontier orbital energy differences and highest occupied orbital energies obtained. At the correlated level, an OEP approach based on a perturbative second-order correlation energy expression is shown to deliver results comparable with those from traditional wave function approaches, making it suitable for use as a benchmark against which to compare standard density functional approximations.

Enrichment of peptides in serum by C(8)-functionalized magnetic nanoparticles for direct matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis.

PubMed

Yao, Ning; Chen, Hemei; Lin, Huaqing; Deng, Chunhui; Zhang, Xiangmin

2008-03-21

Human serum contains a complex array of proteolytically derived peptides (serum peptidome), which contain biomarkers of preclinical screening and disease diagnosis. Recently, commercial C(8)-functionalized magnetic beads (1-10 microm) were widely applied to the separation and enrichment of peptides in human serum, prior to matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) analysis. In this work, laboratory-prepared C(8)-functionalized magnetic nanoparticles (about 50 nm) were prepared and applied to the fast separation and the enrichment of peptides from serum. At first, the C(8)-magnetic nanoparticles were synthesized by modifying amine-functionalized magnetic nanoparticles with chlorodimethyloctylsilane. These synthesized C(8)-amine-functionalized magnetic particles have excellent magnetic responsibility, high dispersibility and large surface area. Finally, the C(8)-magnetic nanoparticles were successfully applied to fast and efficient enrichment of low-abundance peptides from protein tryptic digestion and human serum followed by MALDI-TOF-MS analysis.

Radio-science performance analysis software

NASA Technical Reports Server (NTRS)

Morabito, D. D.; Asmar, S. W.

1995-01-01

The Radio Science Systems Group (RSSG) provides various support functions for several flight project radio-science teams. Among these support functions are uplink and sequence planning, real-time operations monitoring and support, data validation, archiving and distribution functions, and data processing and analysis. This article describes the support functions that encompass radio-science data performance analysis. The primary tool used by the RSSG to fulfill this support function is the STBLTY program set. STBLTY is used to reconstruct observable frequencies and calculate model frequencies, frequency residuals, frequency stability in terms of Allan deviation, reconstructed phase, frequency and phase power spectral density, and frequency drift rates. In the case of one-way data, using an ultrastable oscillator (USO) as a frequency reference, the program set computes the spacecraft transmitted frequency and maintains a database containing the in-flight history of the USO measurements. The program set also produces graphical displays. Some examples and discussions on operating the program set on Galileo and Ulysses data will be presented.

Performance Analysis of Scientific and Engineering Applications Using MPInside and TAU

NASA Technical Reports Server (NTRS)

Saini, Subhash; Mehrotra, Piyush; Taylor, Kenichi Jun Haeng; Shende, Sameer Suresh; Biswas, Rupak

2010-01-01

In this paper, we present performance analysis of two NASA applications using performance tools like Tuning and Analysis Utilities (TAU) and SGI MPInside. MITgcmUV and OVERFLOW are two production-quality applications used extensively by scientists and engineers at NASA. MITgcmUV is a global ocean simulation model, developed by the Estimating the Circulation and Climate of the Ocean (ECCO) Consortium, for solving the fluid equations of motion using the hydrostatic approximation. OVERFLOW is a general-purpose Navier-Stokes solver for computational fluid dynamics (CFD) problems. Using these tools, we analyze the MPI functions (MPI_Sendrecv, MPI_Bcast, MPI_Reduce, MPI_Allreduce, MPI_Barrier, etc.) with respect to message size of each rank, time consumed by each function, and how ranks communicate. MPI communication is further analyzed by studying the performance of MPI functions used in these two applications as a function of message size and number of cores. Finally, we present the compute time, communication time, and I/O time as a function of the number of cores.

Dexterity: A MATLAB-based analysis software suite for processing and visualizing data from tasks that measure arm or forelimb function.

PubMed

Butensky, Samuel D; Sloan, Andrew P; Meyers, Eric; Carmel, Jason B

2017-07-15

Hand function is critical for independence, and neurological injury often impairs dexterity. To measure hand function in people or forelimb function in animals, sensors are employed to quantify manipulation. These sensors make assessment easier and more quantitative and allow automation of these tasks. While automated tasks improve objectivity and throughput, they also produce large amounts of data that can be burdensome to analyze. We created software called Dexterity that simplifies data analysis of automated reaching tasks. Dexterity is MATLAB software that enables quick analysis of data from forelimb tasks. Through a graphical user interface, files are loaded and data are identified and analyzed. These data can be annotated or graphed directly. Analysis is saved, and the graph and corresponding data can be exported. For additional analysis, Dexterity provides access to custom scripts created by other users. To determine the utility of Dexterity, we performed a study to evaluate the effects of task difficulty on the degree of impairment after injury. Dexterity analyzed two months of data and allowed new users to annotate the experiment, visualize results, and save and export data easily. Previous analysis of tasks was performed with custom data analysis, requiring expertise with analysis software. Dexterity made the tools required to analyze, visualize and annotate data easy to use by investigators without data science experience. Dexterity increases accessibility to automated tasks that measure dexterity by making analysis of large data intuitive, robust, and efficient. Copyright © 2017 Elsevier B.V. All rights reserved.

Using normalization 3D model for automatic clinical brain quantative analysis and evaluation

NASA Astrophysics Data System (ADS)

Lin, Hong-Dun; Yao, Wei-Jen; Hwang, Wen-Ju; Chung, Being-Tau; Lin, Kang-Ping

2003-05-01

Functional medical imaging, such as PET or SPECT, is capable of revealing physiological functions of the brain, and has been broadly used in diagnosing brain disorders by clinically quantitative analysis for many years. In routine procedures, physicians manually select desired ROIs from structural MR images and then obtain physiological information from correspondent functional PET or SPECT images. The accuracy of quantitative analysis thus relies on that of the subjectively selected ROIs. Therefore, standardizing the analysis procedure is fundamental and important in improving the analysis outcome. In this paper, we propose and evaluate a normalization procedure with a standard 3D-brain model to achieve precise quantitative analysis. In the normalization process, the mutual information registration technique was applied for realigning functional medical images to standard structural medical images. Then, the standard 3D-brain model that shows well-defined brain regions was used, replacing the manual ROIs in the objective clinical analysis. To validate the performance, twenty cases of I-123 IBZM SPECT images were used in practical clinical evaluation. The results show that the quantitative analysis outcomes obtained from this automated method are in agreement with the clinical diagnosis evaluation score with less than 3% error in average. To sum up, the method takes advantage of obtaining precise VOIs, information automatically by well-defined standard 3-D brain model, sparing manually drawn ROIs slice by slice from structural medical images in traditional procedure. That is, the method not only can provide precise analysis results, but also improve the process rate for mass medical images in clinical.

A non-linear regression analysis program for describing electrophysiological data with multiple functions using Microsoft Excel.

PubMed

Brown, Angus M

2006-04-01

The objective of this present study was to demonstrate a method for fitting complex electrophysiological data with multiple functions using the SOLVER add-in of the ubiquitous spreadsheet Microsoft Excel. SOLVER minimizes the difference between the sum of the squares of the data to be fit and the function(s) describing the data using an iterative generalized reduced gradient method. While it is a straightforward procedure to fit data with linear functions, and we have previously demonstrated a method of non-linear regression analysis of experimental data based upon a single function, it is more complex to fit data with multiple functions, usually requiring specialized expensive computer software. In this paper we describe an easily understood program for fitting experimentally acquired data, in this case the stimulus-evoked compound action potential from the mouse optic nerve, with multiple Gaussian functions. The program is flexible and can be applied to describe data with a wide variety of user-input functions.

Graph theory analysis of complex brain networks: new concepts in brain mapping applied to neurosurgery.

PubMed

Hart, Michael G; Ypma, Rolf J F; Romero-Garcia, Rafael; Price, Stephen J; Suckling, John

2016-06-01

Neuroanatomy has entered a new era, culminating in the search for the connectome, otherwise known as the brain's wiring diagram. While this approach has led to landmark discoveries in neuroscience, potential neurosurgical applications and collaborations have been lagging. In this article, the authors describe the ideas and concepts behind the connectome and its analysis with graph theory. Following this they then describe how to form a connectome using resting state functional MRI data as an example. Next they highlight selected insights into healthy brain function that have been derived from connectome analysis and illustrate how studies into normal development, cognitive function, and the effects of synthetic lesioning can be relevant to neurosurgery. Finally, they provide a précis of early applications of the connectome and related techniques to traumatic brain injury, functional neurosurgery, and neurooncology.

IQM: An Extensible and Portable Open Source Application for Image and Signal Analysis in Java

PubMed Central

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM’s image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis. PMID:25612319

IQM: an extensible and portable open source application for image and signal analysis in Java.

PubMed

Kainz, Philipp; Mayrhofer-Reinhartshuber, Michael; Ahammer, Helmut

2015-01-01

Image and signal analysis applications are substantial in scientific research. Both open source and commercial packages provide a wide range of functions for image and signal analysis, which are sometimes supported very well by the communities in the corresponding fields. Commercial software packages have the major drawback of being expensive and having undisclosed source code, which hampers extending the functionality if there is no plugin interface or similar option available. However, both variants cannot cover all possible use cases and sometimes custom developments are unavoidable, requiring open source applications. In this paper we describe IQM, a completely free, portable and open source (GNU GPLv3) image and signal analysis application written in pure Java. IQM does not depend on any natively installed libraries and is therefore runnable out-of-the-box. Currently, a continuously growing repertoire of 50 image and 16 signal analysis algorithms is provided. The modular functional architecture based on the three-tier model is described along the most important functionality. Extensibility is achieved using operator plugins, and the development of more complex workflows is provided by a Groovy script interface to the JVM. We demonstrate IQM's image and signal processing capabilities in a proof-of-principle analysis and provide example implementations to illustrate the plugin framework and the scripting interface. IQM integrates with the popular ImageJ image processing software and is aiming at complementing functionality rather than competing with existing open source software. Machine learning can be integrated into more complex algorithms via the WEKA software package as well, enabling the development of transparent and robust methods for image and signal analysis.

Quantitative trait nucleotide analysis using Bayesian model selection.

PubMed

Blangero, John; Goring, Harald H H; Kent, Jack W; Williams, Jeff T; Peterson, Charles P; Almasy, Laura; Dyer, Thomas D

2005-10-01

Although much attention has been given to statistical genetic methods for the initial localization and fine mapping of quantitative trait loci (QTLs), little methodological work has been done to date on the problem of statistically identifying the most likely functional polymorphisms using sequence data. In this paper we provide a general statistical genetic framework, called Bayesian quantitative trait nucleotide (BQTN) analysis, for assessing the likely functional status of genetic variants. The approach requires the initial enumeration of all genetic variants in a set of resequenced individuals. These polymorphisms are then typed in a large number of individuals (potentially in families), and marker variation is related to quantitative phenotypic variation using Bayesian model selection and averaging. For each sequence variant a posterior probability of effect is obtained and can be used to prioritize additional molecular functional experiments. An example of this quantitative nucleotide analysis is provided using the GAW12 simulated data. The results show that the BQTN method may be useful for choosing the most likely functional variants within a gene (or set of genes). We also include instructions on how to use our computer program, SOLAR, for association analysis and BQTN analysis.

Expediting Combinatorial Data Set Analysis by Combining Human and Algorithmic Analysis.

PubMed

Stein, Helge Sören; Jiao, Sally; Ludwig, Alfred

2017-01-09

A challenge in combinatorial materials science remains the efficient analysis of X-ray diffraction (XRD) data and its correlation to functional properties. Rapid identification of phase-regions and proper assignment of corresponding crystal structures is necessary to keep pace with the improved methods for synthesizing and characterizing materials libraries. Therefore, a new modular software called htAx (high-throughput analysis of X-ray and functional properties data) is presented that couples human intelligence tasks used for "ground-truth" phase-region identification with subsequent unbiased verification by an algorithm to efficiently analyze which phases are present in a materials library. Identified phases and phase-regions may then be correlated to functional properties in an expedited manner. For the functionality of htAx to be proven, two previously published XRD benchmark data sets of the materials systems Al-Cr-Fe-O and Ni-Ti-Cu are analyzed by htAx. The analysis of ∼1000 XRD patterns takes less than 1 day with htAx. The proposed method reliably identifies phase-region boundaries and robustly identifies multiphase structures. The method also addresses the problem of identifying regions with previously unpublished crystal structures using a special daisy ternary plot.