Modelling crop yield in Iberia under drought conditions

NASA Astrophysics Data System (ADS)

Ribeiro, Andreia; Páscoa, Patrícia; Russo, Ana; Gouveia, Célia

2017-04-01

The improved assessment of the cereal yield and crop loss under drought conditions are essential to meet the increasing economy demands. The growing frequency and severity of the extreme drought conditions in the Iberian Peninsula (IP) has been likely responsible for negative impacts on agriculture, namely on crop yield losses. Therefore, a continuous monitoring of vegetation activity and a reliable estimation of drought impacts is crucial to contribute for the agricultural drought management and development of suitable information tools. This works aims to assess the influence of drought conditions in agricultural yields over the IP, considering cereal yields from mainly rainfed agriculture for the provinces with higher productivity. The main target is to develop a strategy to model drought risk on agriculture for wheat yield at a province level. In order to achieve this goal a combined assessment was made using a drought indicator (Standardized Precipitation Evapotranspiration Index, SPEI) to evaluate drought conditions together with a widely used vegetation index (Normalized Difference Vegetation Index, NDVI) to monitor vegetation activity. A correlation analysis between detrended wheat yield and SPEI was performed in order to assess the vegetation response to each time scale of drought occurrence and also identify the moment of the vegetative cycle when the crop yields are more vulnerable to drought conditions. The time scales and months of SPEI, together with the months of NDVI, better related with wheat yield were chosen to perform a multivariate regression analysis to simulate crop yield. Model results are satisfactory and highlighted the usefulness of such analysis in the framework of developing a drought risk model for crop yields. In terms of an operational point of view, the results aim to contribute to an improved understanding of crop yield management under dry conditions, particularly adding substantial information on the advantages of combining vegetation and hydro-meteorological drought indices for the assessment of cereal yield. Moreover, the present study will provide some guidance on user's decision making process in agricultural practices in the IP, assisting farmers in deciding whether to purchase crop insurance. Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e a Tecnologia, Portugal) under project IMDROFLOOD (WaterJPI/0004/2014). Ana Russo thanks FCT for granted support (SFRH/BPD/99757/2014). Andreia Ribeiro also thanks FCT for grant PD/BD/114481/2016.

GIS-Based Multi-Criteria Analysis for Arabica Coffee Expansion in Rwanda

PubMed Central

Nzeyimana, Innocent; Hartemink, Alfred E.; Geissen, Violette

2014-01-01

The Government of Rwanda is implementing policies to increase the area of Arabica coffee production. Information on the suitable areas for sustainably growing Arabica coffee is still scarce. This study aimed to analyze suitable areas for Arabica coffee production. We analyzed the spatial distribution of actual and potential production zones for Arabica coffee, their productivity levels and predicted potential yields. We used a geographic information system (GIS) for a weighted overlay analysis to assess the major production zones of Arabica coffee and their qualitative productivity indices. Actual coffee yields were measured in the field and were used to assess potential productivity zones and yields using ordinary kriging with ArcGIS software. The production of coffee covers about 32 000 ha, or 2.3% of all cultivated land in the country. The major zones of production are the Kivu Lake Borders, Central Plateau, Eastern Plateau, and Mayaga agro-ecological zones, where coffee is mainly cultivated on moderate slopes. In the highlands, coffee is grown on steep slopes that can exceed 55%. About 21% percent of the country has a moderate yield potential, ranging between 1.0 and 1.6 t coffee ha−1, and 70% has a low yield potential (<1.0 t coffee ha−1). Only 9% of the country has a high yield potential of 1.6–2.4 t coffee ha−1. Those areas are found near Lake Kivu where the dominant soil Orders are Inceptisols and Ultisols. Moderate yield potential is found in the Birunga (volcano), Congo-Nile watershed Divide, Impala and Imbo zones. Low-yield regions (<1 t ha−1) occur in the eastern semi-dry lowlands, Central Plateau, Eastern Plateau, Buberuka Highlands, and Mayaga zones. The weighted overlay analysis and ordinary kriging indicated a large spatial variability of potential productivity indices. Increasing the area and productivity of coffee in Rwanda thus has considerable potential. PMID:25299459

The Modification of Mars Fluvial Surfaces

NASA Technical Reports Server (NTRS)

Bourke, M. C.; Zimbelman, J. R.; Finnegan, D.; Banerdt, B.

2001-01-01

The identification of fluvial deposits on Mars is impaired by modifying geological processes. An analysis of surface patterns of superimposed dunes and channels in paleoflood environments in Washington State and Australia can yield information on buried surfaces. Additional information is contained in the original extended abstract.

Early lactation production, health, and welfare characteristics of cows selected for extended lactation.

PubMed

Lehmann, J O; Mogensen, L; Kristensen, T

2017-02-01

Some cows are able to achieve relatively high milk yields during extended lactations beyond 305 d in milk, and farmers may be able to use this potential by selecting the most suitable cows for an extended lactation. However, the decision to postpone insemination has to rely on information available in early lactation. The main objectives of this study were, therefore, to assess the association between the information available in early lactation and the relative milk production of cows on extended lactation, and to investigate if this information can be used to differentiate time of first insemination between cows. Data came from 4 Danish private herds practicing extended lactation in which some cows are selected to have a delayed time of planned first insemination. Average herd size varied from 93 to 157 cows, and milk yield varied from 7,842 to 12,315 kg of energy-corrected milk (ECM) per cow per year across herds. The analysis was based on 422 completed extended lactations (427 ± 87 d), and each lactation was assigned to 1 of 3 (low, medium, and high) milk performance groups (MPG) within parity group within herd based on a standardized lactation yield. For cows in the high MPG, peak ECM yield, and ECM yield at dry off were significantly greater, the relative reduction in milk yield between 60 and 305 d in milk was significantly smaller, and a smaller proportion had a body condition score (scale: 1-5) at dry off of 3.5 or greater compared with cows in low MPG. Previous lactation days in milk at peak ECM yield and ECM yield at dry off were higher, the relative reduction in milk yield between 60 and 305 d in milk was smaller, and the number of inseminations per conception was higher for multiparous cows in high MPG compared with low. Current lactation ECM yield at second and third milk recording were greater for cows in high MPG compared with low. A principal component analysis indicated that variables related to fertility, diseases, and milk yield explained most of the total variation between primiparous cows, whereas variables related to milk yield, fertility, and days in milk at peak yield were the most dominating for multiparous cows. Our study indicated that milk yields in previous lactation and at second and third milk recording correlate well with milk production potential, and therefore, may be promising indicators when selecting the most suitable cows for extended lactation. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Seasonal critical concentration and relationships of uppermost fully expanded leaf phosphorus and potassium status with biomass and yield traits at maturity in soybean

USDA-ARS?s Scientific Manuscript database

Analysis of uppermost fully expanded leaves is useful to detect deficiency of mineral nutrients such as phosphorus (P) and potassium (K) in soybean. Although, the leaf P or K status aids in fertilizer management, information on their seasonal association with the growth and yield traits at maturity ...

A Study of Supervisor and Employee Perceptions of Work Attitudes in Information Age Manufacturing Industries

ERIC Educational Resources Information Center

Azam, Md. Shafiqul; Brauchle, Paul E.

2003-01-01

The self-perceived work ethic of industrial employees in information jobs (N=304) and non-information jobs (N=277), and employees' work ethic as assessed by their supervisors, were examined using the Occupational Work Ethic Inventory (OWEI). A Principle Components Analysis yielded four factors (Teamwork, Dependability, Ambition and Self-Control)…

Yield Gap, Indigenous Nutrient Supply and Nutrient Use Efficiency for Maize in China.

PubMed

Xu, Xinpeng; Liu, Xiaoyan; He, Ping; Johnston, Adrian M; Zhao, Shicheng; Qiu, Shaojun; Zhou, Wei

2015-01-01

Great achievements have been attained in agricultural production of China, while there are still many difficulties and challenges ahead that call for put more efforts to overcome to guarantee food security and protect environment simultaneously. Analyzing yield gap and nutrient use efficiency will help develop and inform agricultural policies and strategies to increase grain yield. On-farm datasets from 2001 to 2012 with 1,971 field experiments for maize (Zea mays L.) were collected in four maize agro-ecological regions of China, and the optimal management (OPT), farmers' practice (FP), a series of nutrient omission treatments were used to analyze yield gap, nutrient use efficiency and indigenous nutrient supply by adopting meta-analysis and ANOVA analysis. Across all sites, the average yield gap between OPT and FP was 0.7 t ha-1, the yield response to nitrogen (N), phosphorus (P), and potassium (K) were 1.8, 1.0, and 1.2 t ha-1, respectively. The soil indigenous nutrient supply of N, P, and K averaged 139.9, 33.7, and 127.5 kg ha-1, respectively. As compared to FP, the average recovery efficiency (RE) of N, P, and K with OPT increased by percentage point of 12.2, 5.5, and 6.5, respectively. This study indicated that there would be considerable potential to further improve yield and nutrient use efficiency in China, and will help develop and inform agricultural policies and strategies, while some management measures such as soil, plant and nutrient are necessary and integrate with advanced knowledge and technologies.

Yield Gap, Indigenous Nutrient Supply and Nutrient Use Efficiency for Maize in China

PubMed Central

Xu, Xinpeng; Liu, Xiaoyan; He, Ping; Johnston, Adrian M.; Zhao, Shicheng; Qiu, Shaojun; Zhou, Wei

2015-01-01

Great achievements have been attained in agricultural production of China, while there are still many difficulties and challenges ahead that call for put more efforts to overcome to guarantee food security and protect environment simultaneously. Analyzing yield gap and nutrient use efficiency will help develop and inform agricultural policies and strategies to increase grain yield. On-farm datasets from 2001 to 2012 with 1,971 field experiments for maize (Zea mays L.) were collected in four maize agro-ecological regions of China, and the optimal management (OPT), farmers’ practice (FP), a series of nutrient omission treatments were used to analyze yield gap, nutrient use efficiency and indigenous nutrient supply by adopting meta-analysis and ANOVA analysis. Across all sites, the average yield gap between OPT and FP was 0.7 t ha-1, the yield response to nitrogen (N), phosphorus (P), and potassium (K) were 1.8, 1.0, and 1.2 t ha-1, respectively. The soil indigenous nutrient supply of N, P, and K averaged 139.9, 33.7, and 127.5 kg ha-1, respectively. As compared to FP, the average recovery efficiency (RE) of N, P, and K with OPT increased by percentage point of 12.2, 5.5, and 6.5, respectively. This study indicated that there would be considerable potential to further improve yield and nutrient use efficiency in China, and will help develop and inform agricultural policies and strategies, while some management measures such as soil, plant and nutrient are necessary and integrate with advanced knowledge and technologies. PMID:26484543

Factors related to well yield in the fractured-bedrock aquifer of New Hampshire

USGS Publications Warehouse

Moore, Richard Bridge; Schwartz, Gregory E.; Clark, Stewart F.; Walsh, Gregory J.; Degnan, James R.

2002-01-01

The New Hampshire Bedrock Aquifer Assessment was designed to provide information that can be used by communities, industry, professional consultants, and other interests to evaluate the ground-water development potential of the fractured-bedrock aquifer in the State. The assessment was done at statewide, regional, and well field scales to identify relations that potentially could increase the success in locating high-yield water supplies in the fractured-bedrock aquifer. statewide, data were collected for well construction and yield information, bedrock lithology, surficial geology, lineaments, topography, and various derivatives of these basic data sets. Regionally, geologic, fracture, and lineament data were collected for the Pinardville and Windham quadrangles in New Hampshire. The regional scale of the study examined the degree to which predictive well-yield relations, developed as part of the statewide reconnaissance investigation, could be improved by use of quadrangle-scale geologic mapping. Beginning in 1984, water-well contractors in the State were required to report detailed information on newly constructed wells to the New Hampshire Department of Environmental Services (NHDES). The reports contain basic data on well construction, including six characteristics used in this study?well yield, well depth, well use, method of construction, date drilled, and depth to bedrock (or length of casing). The NHDES has determined accurate georeferenced locations for more than 20,000 wells reported since 1984. The availability of this large data set provided an opportunity for a statistical analysis of bedrock-well yields. Well yields in the database ranged from zero to greater than 500 gallons per minute (gal/min). Multivariate regression was used as the primary statistical method of analysis because it is the most efficient tool for predicting a single variable with many potentially independent variables. The dependent variable that was explored in this study was the natural logarithm (ln) of the reported well yield. One complication with using well yield as a dependent variable is that yield also is a function of demand. An innovative statistical technique that involves the use of instrumental variables was implemented to compensate for the effect of demand on well yield. Results of the multivariate-regression model show that a variety of factors are either positively or negatively related to well yields. Using instrumental variables, well depth is positively related to total well yield. Other factors that were found to be positively related to well yield include (1) distance to the nearest waterbody; (2) size of the drainage area upgradient of a well; (3) well location in swales or valley bottoms in the Massabesic Gneiss Complex and Breakfast Hill Granite; (4) well proximity to lineaments, identified using high-altitude (1:80,000-scale) aerial photography, which are correlated with the primary fracture direction (regional analysis); (5) use of a cable tool rig for well drilling; and (6) wells drilled for commercial or public supply. Factors negatively related to well yields include sites underlain by foliated plutons, sites on steep slopes sites at high elevations, and sites on hilltops. Additionally, seven detailed geologic map units, identified during the detailed geologic mapping of the Pinardville and Windham quadrangles, were found to be positively or negatively related to well yields. Twenty-four geologic map units, depicted on the Bedrock Geologic Map of New Hampshire, also were found to be positively or negatively related to well yields. Maps or geographic information system (GIS) data sets identifying areas of various yield probabilities clearly display model results. Probability criteria developed in this investigation can be used to select areas where other techniques, such as geophysical techniques, can be applied to more closely identify potential drilling sites for high-yielding

75 FR 7412 - Reporting Information Regarding Falsification of Data

Federal Register 2010, 2011, 2012, 2013, 2014

2010-02-19

... concomitant medications or treatments; omitting data so that a statistical analysis yields a result that would..., results, statistics, items of information, or statements made by individuals. This proposed rule would..., Bureau of Labor Statistics ( www.bls.gov/oes/current/naics4_325400.htm ); compliance officer wage rate...

Technologies Enabling Scientific Exploration of Asteroids and Moons

NASA Astrophysics Data System (ADS)

Shaw, A.; Fulford, P.; Chappell, L.

2016-12-01

Scientific exploration of moons and asteroids is enabled by several key technologies that yield topographic information, allow excavation of subsurface materials, and allow delivery of higher-mass scientific payloads to moons and asteroids. These key technologies include lidar systems, robotics, and solar-electric propulsion spacecraft buses. Many of these technologies have applications for a variety of planetary targets. Lidar systems yield high-resolution shape models of asteroids and moons. These shape models can then be combined with radio science information to yield insight into density and internal structure. Further, lidar systems allow investigation of topographic surface features, large and small, which yields information on regolith properties. Robotic arms can be used for a variety of purposes, especially to support excavation, revealing subsurface material and acquiring material from depth for either in situ analysis or sample return. Robotic arms with built-in force sensors can also be used to gauge the strength of materials as a function of depth, yielding insight into regolith physical properties. Mobility systems allow scientific exploration of multiple sites, and also yield insight into regolith physical properties due to the interaction of wheels with regolith. High-power solar electric propulsion (SEP) spacecraft bus systems allow more science instruments to be included on missions given their ability to support greater payload mass. In addition, leveraging a cost-effective commercially-built SEP spacecraft bus can significantly reduce mission cost.

Relationship between rice yield and climate variables in southwest Nigeria using multiple linear regression and support vector machine analysis

NASA Astrophysics Data System (ADS)

Oguntunde, Philip G.; Lischeid, Gunnar; Dietrich, Ottfried

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

Bayesian imperfect information analysis for clinical recurrent data

PubMed Central

Chang, Chih-Kuang; Chang, Chi-Chang

2015-01-01

In medical research, clinical practice must often be undertaken with imperfect information from limited resources. This study applied Bayesian imperfect information-value analysis to realistic situations to produce likelihood functions and posterior distributions, to a clinical decision-making problem for recurrent events. In this study, three kinds of failure models are considered, and our methods illustrated with an analysis of imperfect information from a trial of immunotherapy in the treatment of chronic granulomatous disease. In addition, we present evidence toward a better understanding of the differing behaviors along with concomitant variables. Based on the results of simulations, the imperfect information value of the concomitant variables was evaluated and different realistic situations were compared to see which could yield more accurate results for medical decision-making. PMID:25565853

Assessment of cluster yield components by image analysis.

PubMed

Diago, Maria P; Tardaguila, Javier; Aleixos, Nuria; Millan, Borja; Prats-Montalban, Jose M; Cubero, Sergio; Blasco, Jose

2015-04-01

Berry weight, berry number and cluster weight are key parameters for yield estimation for wine and tablegrape industry. Current yield prediction methods are destructive, labour-demanding and time-consuming. In this work, a new methodology, based on image analysis was developed to determine cluster yield components in a fast and inexpensive way. Clusters of seven different red varieties of grapevine (Vitis vinifera L.) were photographed under laboratory conditions and their cluster yield components manually determined after image acquisition. Two algorithms based on the Canny and the logarithmic image processing approaches were tested to find the contours of the berries in the images prior to berry detection performed by means of the Hough Transform. Results were obtained in two ways: by analysing either a single image of the cluster or using four images per cluster from different orientations. The best results (R(2) between 69% and 95% in berry detection and between 65% and 97% in cluster weight estimation) were achieved using four images and the Canny algorithm. The model's capability based on image analysis to predict berry weight was 84%. The new and low-cost methodology presented here enabled the assessment of cluster yield components, saving time and providing inexpensive information in comparison with current manual methods. © 2014 Society of Chemical Industry.

Global Synthesis of Drought Effects on Maize and Wheat Production

PubMed Central

Daryanto, Stefani; Wang, Lixin; Jacinthe, Pierre-André

2016-01-01

Drought has been a major cause of agricultural disaster, yet how it affects the vulnerability of maize and wheat production in combination with several co-varying factors (i.e., phenological phases, agro-climatic regions, soil texture) remains unclear. Using a data synthesis approach, this study aims to better characterize the effects of those co-varying factors with drought and to provide critical information on minimizing yield loss. We collected data from peer-reviewed publications between 1980 and 2015 which examined maize and wheat yield responses to drought using field experiments. We performed unweighted analysis using the log response ratio to calculate the bootstrapped confidence limits of yield responses and calculated drought sensitivities with regards to those co-varying factors. Our results showed that yield reduction varied with species, with wheat having lower yield reduction (20.6%) compared to maize (39.3%) at approximately 40% water reduction. Maize was also more sensitive to drought than wheat, particularly during reproductive phase and equally sensitive in the dryland and non-dryland regions. While no yield difference was observed among regions or different soil texture, wheat cultivation in the dryland was more prone to yield loss than in the non-dryland region. Informed by these results, we discuss potential causes and possible approaches that may minimize drought impacts. PMID:27223810

Analysis of Building 839: Carlisle Barracks, Pennsylvania

DTIC Science & Technology

2013-09-01

within prehistory or history is made clear.”101 A historic property is determined as either significant or not significant by applying standardized...yielded, or is likely to yield, information important in prehistory or history. 3.3 Significance Eligibility to the NRHP is based upon...given period in history or prehistory . The workmanship of Building 839 is evident in the mortar joints of the brick walls (Figure 53), the rake boards

Characteristics of Information Agencies (Libraries) and Information Agents (Librarians) in Highly Productive Computer Software and Services Companies: The Key to Growth and Survival?

ERIC Educational Resources Information Center

Carroll, Margaret Aby; Chandler, Yvonne J.

This study examines whether an analysis of characteristics of libraries or information centers and librarians in highly productive companies yields operational models and standards that can improve their efficiency and effectiveness and their parent organization's productivity. Data was collected using an e-mail survey instrument sent to 500 large…

Analysis of Chi-square Automatic Interaction Detection (CHAID) and Classification and Regression Tree (CRT) for Classification of Corn Production

NASA Astrophysics Data System (ADS)

Susanti, Yuliana; Zukhronah, Etik; Pratiwi, Hasih; Respatiwulan; Sri Sulistijowati, H.

2017-11-01

To achieve food resilience in Indonesia, food diversification by exploring potentials of local food is required. Corn is one of alternating staple food of Javanese society. For that reason, corn production needs to be improved by considering the influencing factors. CHAID and CRT are methods of data mining which can be used to classify the influencing variables. The present study seeks to dig up information on the potentials of local food availability of corn in regencies and cities in Java Island. CHAID analysis yields four classifications with accuracy of 78.8%, while CRT analysis yields seven classifications with accuracy of 79.6%.

Climatic and technological ceilings for Chinese rice stagnation based on yield gaps and yield trend pattern analysis.

PubMed

Zhang, Tianyi; Yang, Xiaoguang; Wang, Hesong; Li, Yong; Ye, Qing

2014-04-01

Climatic or technological ceilings could cause yield stagnation. Thus, identifying the principal reasons for yield stagnation within the context of the local climate and socio-economic conditions are essential for informing regional agricultural policies. In this study, we identified the climatic and technological ceilings for seven rice-production regions in China based on yield gaps and on a yield trend pattern analysis for the period 1980-2010. The results indicate that 54.9% of the counties sampled experienced yield stagnation since the 1980. The potential yield ceilings in northern and eastern China decreased to a greater extent than in other regions due to the accompanying climate effects of increases in temperature and decreases in radiation. This may be associated with yield stagnation and halt occurring in approximately 49.8-57.0% of the sampled counties in these areas. South-western China exhibited a promising scope for yield improvement, showing the greatest yield gap (30.6%), whereas the yields were stagnant in 58.4% of the sampled counties. This finding suggests that efforts to overcome the technological ceiling must be given priority so that the available exploitable yield gap can be achieved. North-eastern China, however, represents a noteworthy exception. In the north-central area of this region, climate change has increased the yield potential ceiling, and this increase has been accompanied by the most rapid increase in actual yield: 1.02 ton ha(-1) per decade. Therefore, north-eastern China shows a great potential for rice production, which is favoured by the current climate conditions and available technology level. Additional environmentally friendly economic incentives might be considered in this region. © 2013 John Wiley & Sons Ltd.

Planning an Information System for a Small College. AIR Forum Paper 1978.

ERIC Educational Resources Information Center

Toombs, William; Sagaria, Mary Ann

Data collection and analyses of college records and interviewing provided a cross-sectional view of data flow and information transmission in a small college. The micro-analysis of interview data, forms, and reports yielded a picture of functional relationships, clarified loci of decision making, and stipulated functions served by data items.…

Decentralized modal identification using sparse blind source separation

NASA Astrophysics Data System (ADS)

Sadhu, A.; Hazra, B.; Narasimhan, S.; Pandey, M. D.

2011-12-01

Popular ambient vibration-based system identification methods process information collected from a dense array of sensors centrally to yield the modal properties. In such methods, the need for a centralized processing unit capable of satisfying large memory and processing demands is unavoidable. With the advent of wireless smart sensor networks, it is now possible to process information locally at the sensor level, instead. The information at the individual sensor level can then be concatenated to obtain the global structure characteristics. A novel decentralized algorithm based on wavelet transforms to infer global structure mode information using measurements obtained using a small group of sensors at a time is proposed in this paper. The focus of the paper is on algorithmic development, while the actual hardware and software implementation is not pursued here. The problem of identification is cast within the framework of under-determined blind source separation invoking transformations of measurements to the time-frequency domain resulting in a sparse representation. The partial mode shape coefficients so identified are then combined to yield complete modal information. The transformations are undertaken using stationary wavelet packet transform (SWPT), yielding a sparse representation in the wavelet domain. Principal component analysis (PCA) is then performed on the resulting wavelet coefficients, yielding the partial mixing matrix coefficients from a few measurement channels at a time. This process is repeated using measurements obtained from multiple sensor groups, and the results so obtained from each group are concatenated to obtain the global modal characteristics of the structure.

Application guide for AFINCH (Analysis of Flows in Networks of Channels) described by NHDPlus

USGS Publications Warehouse

Holtschlag, David J.

2009-01-01

AFINCH (Analysis of Flows in Networks of CHannels) is a computer application that can be used to generate a time series of monthly flows at stream segments (flowlines) and water yields for catchments defined in the National Hydrography Dataset Plus (NHDPlus) value-added attribute system. AFINCH provides a basis for integrating monthly flow data from streamgages, water-use data, monthly climatic data, and land-cover characteristics to estimate natural monthly water yields from catchments by user-defined regression equations. Images of monthly water yields for active streamgages are generated in AFINCH and provide a basis for detecting anomalies in water yields, which may be associated with undocumented flow diversions or augmentations. Water yields are multiplied by the drainage areas of the corresponding catchments to estimate monthly flows. Flows from catchments are accumulated downstream through the streamflow network described by the stream segments. For stream segments where streamgages are active, ratios of measured to accumulated flows are computed. These ratios are applied to upstream water yields to proportionally adjust estimated flows to match measured flows. Flow is conserved through the NHDPlus network. A time series of monthly flows can be generated for stream segments that average about 1-mile long, or monthly water yields from catchments that average about 1 square mile. Estimated monthly flows can be displayed within AFINCH, examined for nonstationarity, and tested for monotonic trends. Monthly flows also can be used to estimate flow-duration characteristics at stream segments. AFINCH generates output files of monthly flows and water yields that are compatible with ArcMap, a geographical information system analysis and display environment. Chloropleth maps of monthly water yield and flow can be generated and analyzed within ArcMap by joining NHDPlus data structures with AFINCH output. Matlab code for the AFINCH application is presented.

Estimates of general combining ability in Hevea breeding at the Rubber Research Institute of Malaysia : I. Phases II and III A.

PubMed

Tan, H

1977-01-01

Estimates of general combining ability of parents for yield and girth obtained separately from seedlings and their corresponding clonal families in Phases II and IIIA of the RRIM breeding programme are compared. A highly significant positive correlation (r = 0.71***) is found between GCA estimates from seedling and clonal families for yield in Phase IIIA, but not in Phase II (r = -0.03(NS)) nor for girth (r= -0.27(NS)) in Phase IIIA. The correlations for Phase II yield and Phase IIIA girth, however, improve when the GCA estimates based on small sample size or reversed rankings are excluded.When the best selections (based on present clonal and seedling information) are compared, all five of the parents top-ranking for yield are common in Phase IIIA but only two parents are common for yield and girth in Phases II and IIIA respectively. However, only one parent for yield in Phase II and two parents for girth in Phase IIIA would, if selected on clonal performance, have been omitted from the top ranking selections made by previous workers using seedling information.These findings, therefore, justify the choice of parents based on GCA estimates for yield obtained from seedling performance. Similar justification cannot be offered for girth, for which analysis is confounded by uninterpretable site and seasonal effects.

SADA: Ecological Risk Based Decision Support System for Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

Remotely sensed rice yield prediction using multi-temporal NDVI data derived from NOAA's-AVHRR.

PubMed

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha(-1). Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly.

Remotely Sensed Rice Yield Prediction Using Multi-Temporal NDVI Data Derived from NOAA's-AVHRR

PubMed Central

Huang, Jingfeng; Wang, Xiuzhen; Li, Xinxing; Tian, Hanqin; Pan, Zhuokun

2013-01-01

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implementation of provincial rice-yield predictions. The technique requires the collection of remotely sensed data over an adequate time frame and a corresponding record of the region's crop yields. Longer normalized-difference-vegetation-index (NDVI) time series are preferable to shorter ones for the purposes of rice-yield prediction because the well-contrasted seasons in a longer time series provide the opportunity to build regression models with a wide application range. A regression analysis of the yield versus the year indicated an annual gain in the rice yield of 50 to 128 kg ha−1. Stepwise regression models for the remotely sensed rice-yield predictions have been developed for five typical rice-growing provinces in China. The prediction models for the remotely sensed rice yield indicated that the influences of the NDVIs on the rice yield were always positive. The association between the predicted and observed rice yields was highly significant without obvious outliers from 1982 to 2004. Independent validation found that the overall relative error is approximately 5.82%, and a majority of the relative errors were less than 5% in 2005 and 2006, depending on the study area. The proposed models can be used in an operational context to predict rice yields at the provincial level in China. The methodologies described in the present paper can be applied to any crop for which a sufficient time series of NDVI data and the corresponding historical yield information are available, as long as the historical yield increases significantly. PMID:23967112

Multi-Phenomenological Analysis of the 12 August 2015 Tianjin, China Chemical Explosion

NASA Astrophysics Data System (ADS)

Pasyanos, M.; Kim, K.; Park, J.; Stump, B. W.; Hayward, C.; Che, I. Y.; Zhao, L.; Myers, S. C.

2016-12-01

We perform a multi-phenomenological analysis of the massive near-surface chemical explosions that occurred in Tianjin, China on 12 August 2015. A recent assessment of these events was performed by Zhao et al. (2016) using local (< 100 km) seismic data. This study considers a regional assessment of the same sequence in the absence of having any local data. We provide additional insight by combining regional seismic analysis with the use of infrasound signals and an assessment of the event crater. Event locations using infrasound signals recorded at Korean and IMS arrays are estimated based on the Bayesian Infrasonic Source Location (BISL) method (Modrak et al., 2010), and improved with azimuthal corrections using a raytracing (Blom and Waxler, 2012) and the Ground-to-Space (G2S) atmospheric models (Drob et al., 2003). The location information provided from the infrasound signals is then merged with the regional seismic arrivals to produce a joint event location. The yields of the events are estimated from seismic and infrasonic observations. Seismic waveform envelope method (Pasyanos et al., 2012) including the free surface effect (Pasyanos and Ford, 2015) is applied to regional seismic signals. Waveform inversion method (Kim and Rodgers, 2016) is used for infrasound signals. A combination of the seismic and acoustic signals can provide insights on the energy partitioning and break the tradeoffs between the yield and the depth/height of explosions, resulting in a more robust estimation of event yield. The yield information from the different phenomenologies are combined through the use of likelihood functions.

Assessing roadway contributions to stormwater flows, concentrations, and loads with the StreamStats application

USGS Publications Warehouse

Stonewall, Adam; Granato, Gregory E.; Haluska, Tana L.

2018-01-01

The Oregon Department of Transportation (ODOT) and other state departments of transportation need quantitative information about the percentages of different land cover categories above any given stream crossing in the state to assess and address roadway contributions to water-quality impairments and resulting total maximum daily loads. The U.S. Geological Survey, in cooperation with ODOT and the FHWA, added roadway and land cover information to the online StreamStats application to facilitate analysis of stormwater runoff contributions from different land covers. Analysis of 25 delineated basins with drainage areas of about 100 mi2 indicates the diversity of land covers in the Willamette Valley, Oregon. On average, agricultural, developed, and undeveloped land covers comprise 15%, 2.3%, and 82% of these basin areas. On average, these basins contained about 10 mi of state highways and 222 mi of non-state roads. The Stochastic Empirical Loading and Dilution Model was used with available water-quality data to simulate long-term yields of total phosphorus from highways, non-highway roadways, and agricultural, developed, and undeveloped areas. These yields were applied to land cover areas obtained from StreamStats for the Willamette River above Wilsonville, Oregon. This analysis indicated that highway yields were larger than yields from other land covers because highway runoff concentrations were higher than other land covers and the highway is fully impervious. However, the total highway area was a fraction of the other land covers. Accordingly, highway runoff mitigation measures can be effective for managing water quality locally, they may have limited effect on achieving basin-wide stormwater reduction goals.

Information Security Analysis Using Game Theory and Simulation

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

Schlicher, Bob G; Abercrombie, Robert K

Information security analysis can be performed using game theory implemented in dynamic simulations of Agent Based Models (ABMs). Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. Our approach addresses imperfect information and scalability that allows us to also address previous limitations of current stochastic game models. Such models only consider perfect information assuming that the defender is always able to detect attacks; assuming that the state transition probabilities are fixed before the game assuming that the players actions aremore » always synchronous; and that most models are not scalable with the size and complexity of systems under consideration. Our use of ABMs yields results of selected experiments that demonstrate our proposed approach and provides a quantitative measure for realistic information systems and their related security scenarios.« less

ID201202961, DOE S-124,539, Information Security Analysis Using Game Theory and Simulation

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

Abercrombie, Robert K; Schlicher, Bob G

Information security analysis can be performed using game theory implemented in dynamic simulations of Agent Based Models (ABMs). Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. Our approach addresses imperfect information and scalability that allows us to also address previous limitations of current stochastic game models. Such models only consider perfect information assuming that the defender is always able to detect attacks; assuming that the state transition probabilities are fixed before the game assuming that the players actions aremore » always synchronous; and that most models are not scalable with the size and complexity of systems under consideration. Our use of ABMs yields results of selected experiments that demonstrate our proposed approach and provides a quantitative measure for realistic information systems and their related security scenarios.« less

Item Banks for Measuring Emotional Distress from the Patient-Reported Outcomes Measurement Information System (PROMIS[R]): Depression, Anxiety, and Anger

ERIC Educational Resources Information Center

Pilkonis, Paul A.; Choi, Seung W.; Reise, Steven P.; Stover, Angela M.; Riley, William T.; Cella, David

2011-01-01

The authors report on the development and calibration of item banks for depression, anxiety, and anger as part of the Patient-Reported Outcomes Measurement Information System (PROMIS[R]). Comprehensive literature searches yielded an initial bank of 1,404 items from 305 instruments. After qualitative item analysis (including focus groups and…

Image analysis-based modelling for flower number estimation in grapevine.

PubMed

Millan, Borja; Aquino, Arturo; Diago, Maria P; Tardaguila, Javier

2017-02-01

Grapevine flower number per inflorescence provides valuable information that can be used for assessing yield. Considerable research has been conducted at developing a technological tool, based on image analysis and predictive modelling. However, the behaviour of variety-independent predictive models and yield prediction capabilities on a wide set of varieties has never been evaluated. Inflorescence images from 11 grapevine Vitis vinifera L. varieties were acquired under field conditions. The flower number per inflorescence and the flower number visible in the images were calculated manually, and automatically using an image analysis algorithm. These datasets were used to calibrate and evaluate the behaviour of two linear (single-variable and multivariable) and a nonlinear variety-independent model. As a result, the integrated tool composed of the image analysis algorithm and the nonlinear approach showed the highest performance and robustness (RPD = 8.32, RMSE = 37.1). The yield estimation capabilities of the flower number in conjunction with fruit set rate (R 2  = 0.79) and average berry weight (R 2  = 0.91) were also tested. This study proves the accuracy of flower number per inflorescence estimation using an image analysis algorithm and a nonlinear model that is generally applicable to different grapevine varieties. This provides a fast, non-invasive and reliable tool for estimation of yield at harvest. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Temporal changes in climatic variables and their impact on crop yields in southwestern China

NASA Astrophysics Data System (ADS)

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing—a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series ( P < 0.05). Increased sunshine hours were observed during the oilseed rape growth period ( P < 0.05). Rainy days decreased slightly in annual and oilseed rape growth time series ( P < 0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall ( P < 0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity ( P < 0.01). Tobacco yield increased with mean temperature ( P < 0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Temporal changes in climatic variables and their impact on crop yields in southwestern China.

PubMed

Liu, Hong-Bin; Gou, Yu; Wang, Hong-Ye; Li, Hong-Mei; Wu, Wei

2014-08-01

Knowledge of variability in climatic variables changes and its impact on crop yields is important for farmers and policy makers, especially in southwestern China where rainfed agriculture is dominant. In the current study, six climatic parameters (mean temperature, rainfall, relative humidity, sunshine hours, temperature difference, and rainy days) and aggregated yields of three main crops (rice: Oryza sativa L., oilseed rape: Brassica napus L., and tobacco: Nicotiana tabacum L.) during 1985-2010 were collected and analyzed for Chongqing-a large agricultural municipality of China. Climatic variables changes were detected by Mann-Kendall test. Increased mean temperature and temperature difference and decreased relative humidity were found in annual and oilseed rape growth time series (P<0.05). Increased sunshine hours were observed during the oilseed rape growth period (P<0.05). Rainy days decreased slightly in annual and oilseed rape growth time series (P<0.10). Correlation analysis showed that yields of all three crops could benefit from changes in climatic variables in this region. Yield of rice increased with rainfall (P<0.10). Yield of oilseed rape increased with mean temperature and temperature difference but decreased with relative humidity (P<0.01). Tobacco yield increased with mean temperature (P<0.05). Path analysis provided additional information about the importance and contribution paths of climatic variables to crop yields. Temperature difference and sunshine hours had higher direct and indirect effects via other climatic variables on yields of rice and tobacco. Mean temperature, relative humidity, rainy days, and temperature difference had higher direct and indirect effects via others on yield of oilseed rape.

Informal Monograph on Riverine Sand Dunes

DTIC Science & Technology

1991-10-01

current deficiencies in the theoretical models are discussed and are concluded to stem from the difficulties inherent to analysis of nonuniform, turbulent...T(x,t) = m[l + crlx(x,t)1[(U - Uc) + Ox(x - 13, - d,t)]n (5) 134 5. (4) and (5) yield 1r(x,b), which is Fourier transformed to yield Bt(k,t) - Tk2 ...is known about the formation, behavior and characteristics of alluvial bed forms, and the principal deficiencies in our knowledge about them. Section

Evaluation of Fifteen Cultivars of Cool-Season Perennial Grasses as Biofuel Feedstocks Using Near-Infrared

DOE PAGES

Payne, Courtney E.; Wolfrum, Edward J.; Nagle, Nicholas J.; ...

2017-06-22

Cool-season (C3) perennial grasses have a long history of cultivation and use as animal forage. This study evaluated 15 cultivars of C3 grasses, when harvested in late June for increased biomass yield, as biofuel feedstocks using near- infrared spectroscopy (NIR) based partial least square (PLS) analysis. These grasses were grown near Iliff, CO, for three growing seasons (2009-2011). The carbohydrate composition and released carbohydrates (total glucose and xylose released from dilute acid pretreatment and enzymatic hydrolysis [EH]) were predicted for samples from the study using NIR/PLS. The results were analyzed from a biofuels perspective, where composition combined with harvest yieldmore » provided information on the carbohydrate yield available for biomass conversion processes, and released carbohydrate yield provided information on the accessibility of those carbohydrates to conversion methods. The range in harvest yields varied more among cultivars (2900 kg ha-1) than did the range in carbohydrate composition (56.0 g kg-1) or released carbohydrates (60.0 g kg-1). When comparing carbohydrate yield to released carbohydrate yield between cultivars, an efficiency as high as 87% release of available carbohydrates was obtained for pubescent wheatgrass [ Thinopyrum intermedium (Host) Barkworth & D.R. Dewey 'Mansaka'], with a low of 71% for hybrid wheatgrass [Elytrigia repens (L.) nevski pseudoroegneria spicata (PURSH) A. Love 'Newhy']. Though hybrid wheatgrass had the lowest release efficiency, its high harvest yield resulted in release of more total carbohydrates than half the other cultivars analyzed. Furthermore, this suggested that harvest yield, carbohydrate release, and carbohydrate composition, together play significant roles in biofuel feedstock evaluation.« less

Evaluation of Fifteen Cultivars of Cool-Season Perennial Grasses as Biofuel Feedstocks Using Near-Infrared

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

Payne, Courtney E.; Wolfrum, Edward J.; Nagle, Nicholas J.

Cool-season (C3) perennial grasses have a long history of cultivation and use as animal forage. This study evaluated 15 cultivars of C3 grasses, when harvested in late June for increased biomass yield, as biofuel feedstocks using near- infrared spectroscopy (NIR) based partial least square (PLS) analysis. These grasses were grown near Iliff, CO, for three growing seasons (2009-2011). The carbohydrate composition and released carbohydrates (total glucose and xylose released from dilute acid pretreatment and enzymatic hydrolysis [EH]) were predicted for samples from the study using NIR/PLS. The results were analyzed from a biofuels perspective, where composition combined with harvest yieldmore » provided information on the carbohydrate yield available for biomass conversion processes, and released carbohydrate yield provided information on the accessibility of those carbohydrates to conversion methods. The range in harvest yields varied more among cultivars (2900 kg ha-1) than did the range in carbohydrate composition (56.0 g kg-1) or released carbohydrates (60.0 g kg-1). When comparing carbohydrate yield to released carbohydrate yield between cultivars, an efficiency as high as 87% release of available carbohydrates was obtained for pubescent wheatgrass [ Thinopyrum intermedium (Host) Barkworth & D.R. Dewey 'Mansaka'], with a low of 71% for hybrid wheatgrass [Elytrigia repens (L.) nevski pseudoroegneria spicata (PURSH) A. Love 'Newhy']. Though hybrid wheatgrass had the lowest release efficiency, its high harvest yield resulted in release of more total carbohydrates than half the other cultivars analyzed. Furthermore, this suggested that harvest yield, carbohydrate release, and carbohydrate composition, together play significant roles in biofuel feedstock evaluation.« less

Soil Water Holding Capacity Mitigates Downside Risk and Volatility in US Rainfed Maize: Time to Invest in Soil Organic Matter?

PubMed Central

Williams, Alwyn; Hunter, Mitchell C.; Kammerer, Melanie; Kane, Daniel A.; Jordan, Nicholas R.; Mortensen, David A.; Smith, Richard G.; Snapp, Sieglinde

2016-01-01

Yield stability is fundamental to global food security in the face of climate change, and better strategies are needed for buffering crop yields against increased weather variability. Regional- scale analyses of yield stability can support robust inferences about buffering strategies for widely-grown staple crops, but have not been accomplished. We present a novel analytical approach, synthesizing 2000–2014 data on weather and soil factors to quantify their impact on county-level maize yield stability in four US states that vary widely in these factors (Illinois, Michigan, Minnesota and Pennsylvania). Yield stability is quantified as both ‘downside risk’ (minimum yield potential, MYP) and ‘volatility’ (temporal yield variability). We show that excessive heat and drought decreased mean yields and yield stability, while higher precipitation increased stability. Soil water holding capacity strongly affected yield volatility in all four states, either directly (Minnesota and Pennsylvania) or indirectly, via its effects on MYP (Illinois and Michigan). We infer that factors contributing to soil water holding capacity can help buffer maize yields against variable weather. Given that soil water holding capacity responds (within limits) to agronomic management, our analysis highlights broadly relevant management strategies for buffering crop yields against climate variability, and informs region-specific strategies. PMID:27560666

Adaptation of FIBER for Forest Inventory and Analysis growth projections in the State of Maine

Treesearch

Dale S. Solomon; Thomas B. Brann; Lawrence E. Caldwell

2000-01-01

The model FIBER (Forest Increment Based on Ecological Rationale) was selected by the Technical Review Team on the Sustainability of Timber Supplies in the State of Maine to construct yield information using USDA Forest Service Forest Inventory and Analysis (FIA) field data. FIBER habitat criteria based on soil characteristics, species composition of overstory, and...

Implicit Wiener series analysis of epileptic seizure recordings.

PubMed

Barbero, Alvaro; Franz, Matthias; van Drongelen, Wim; Dorronsoro, José R; Schölkopf, Bernhard; Grosse-Wentrup, Moritz

2009-01-01

Implicit Wiener series are a powerful tool to build Volterra representations of time series with any degree of non-linearity. A natural question is then whether higher order representations yield more useful models. In this work we shall study this question for ECoG data channel relationships in epileptic seizure recordings, considering whether quadratic representations yield more accurate classifiers than linear ones. To do so we first show how to derive statistical information on the Volterra coefficient distribution and how to construct seizure classification patterns over that information. As our results illustrate, a quadratic model seems to provide no advantages over a linear one. Nevertheless, we shall also show that the interpretability of the implicit Wiener series provides insights into the inter-channel relationships of the recordings.

Analysis on the application of background parameters on remote sensing classification

NASA Astrophysics Data System (ADS)

Qiao, Y.

Drawing accurate crop cultivation acreage, dynamic monitoring of crops growing and yield forecast are some important applications of remote sensing to agriculture. During the 8th 5-Year Plan period, the task of yield estimation using remote sensing technology for the main crops in major production regions in China once was a subtopic to the national research task titled "Study on Application of Remote sensing Technology". In 21 century in a movement launched by Chinese Ministry of Agriculture to combine high technology to farming production, remote sensing has given full play to farm crops' growth monitoring and yield forecast. And later in 2001 Chinese Ministry of Agriculture entrusted the Northern China Center of Agricultural Remote Sensing to forecast yield of some main crops like wheat, maize and rice in rather short time to supply information for the government decision maker. Present paper is a report for this task. It describes the application of background parameters in image recognition, classification and mapping with focuses on plan of the geo-science's theory, ecological feature and its cartographical objects or scale, the study of phrenology for image optimal time for classification of the ground objects, the analysis of optimal waveband composition and the application of background data base to spatial information recognition ;The research based on the knowledge of background parameters is indispensable for improving the accuracy of image classification and mapping quality and won a secondary reward of tech-science achievement from Chinese Ministry of Agriculture. Keywords: Spatial image; Classification; Background parameter

76 FR 55725 - Agency Information Collection Activities: Request for Comments for a New Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-08

... statistical surveys that yield quantitative results that can be generalized to the population of study. This... information will not be used for quantitative information collections that are designed to yield reliably... generic mechanisms that are designed to yield quantitative results. The FHWA received no comments in...

Sharing Overdose Data Across State Agencies to Inform Public Health Strategies: A Case Study.

PubMed

Cherico-Hsii, Sara; Bankoski, Andrea; Singal, Pooja; Horon, Isabelle; Beane, Eric; Casey, Meghan; Rebbert-Franklin, Kathleen; Sharfstein, Joshua

2016-01-01

Data sharing and analysis are important components of coordinated and cost-effective public health strategies. However, legal and policy barriers have made data from different agencies difficult to share and analyze for policy development. To address a rise in overdose deaths, Maryland used an innovative and focused approach to bring together data on overdose decedents across multiple agencies. The effort was focused on developing discrete intervention points based on information yielded on decedents' lives, such as vulnerability upon release from incarceration. Key aspects of this approach included gubernatorial leadership, a unified commitment to data sharing across agencies with memoranda of understanding, and designation of a data management team. Preliminary results have yielded valuable insights and have helped inform policy. This process of navigating legal and privacy concerns in data sharing across multiple agencies may be applied to a variety of public health problems challenging health departments across the country.

Evaluation in undergraduate medical education: Conceptualizing and validating a novel questionnaire for assessing the quality of bedside teaching.

PubMed

Dreiling, Katharina; Montano, Diego; Poinstingl, Herbert; Müller, Tjark; Schiekirka-Schwake, Sarah; Anders, Sven; von Steinbüchel, Nicole; Raupach, Tobias

2017-08-01

Evaluation is an integral part of curriculum development in medical education. Given the peculiarities of bedside teaching, specific evaluation tools for this instructional format are needed. Development of these tools should be informed by appropriate frameworks. The purpose of this study was to develop a specific evaluation tool for bedside teaching based on the Stanford Faculty Development Program's clinical teaching framework. Based on a literature review yielding 47 evaluation items, an 18-item questionnaire was compiled and subsequently completed by undergraduate medical students at two German universities. Reliability and validity were assessed in an exploratory full information item factor analysis (study one) and a confirmatory factor analysis as well as a measurement invariance analysis (study two). The exploratory analysis involving 824 students revealed a three-factor structure. Reliability estimates of the subscales were satisfactory (α = 0.71-0.84). The model yielded satisfactory fit indices in the confirmatory factor analysis involving 1043 students. The new questionnaire is short and yet based on a widely-used framework for clinical teaching. The analyses presented here indicate good reliability and validity of the instrument. Future research needs to investigate whether feedback generated from this tool helps to improve teaching quality and student learning outcome.

Fault tree analysis for data-loss in long-term monitoring networks.

PubMed

Dirksen, J; ten Veldhuis, J A E; Schilperoort, R P S

2009-01-01

Prevention of data-loss is an important aspect in the design as well as the operational phase of monitoring networks since data-loss can seriously limit intended information yield. In the literature limited attention has been paid to the origin of unreliable or doubtful data from monitoring networks. Better understanding of causes of data-loss points out effective solutions to increase data yield. This paper introduces FTA as a diagnostic tool to systematically deduce causes of data-loss in long-term monitoring networks in urban drainage systems. In order to illustrate the effectiveness of FTA, a fault tree is developed for a monitoring network and FTA is applied to analyze the data yield of a UV/VIS submersible spectrophotometer. Although some of the causes of data-loss cannot be recovered because the historical database of metadata has been updated infrequently, the example points out that FTA still is a powerful tool to analyze the causes of data-loss and provides useful information on effective data-loss prevention.

Predicted stand volume for Eucalyptus plantations by spatial analysis

NASA Astrophysics Data System (ADS)

Latifah, Siti; Teodoro, RV; Myrna, GC; Nathaniel, CB; Leonardo, M. F.

2018-03-01

The main objective of the present study was to assess nonlinear models generated by integrating the stand volume growth rate to estimate the growth and yield of Eucalyptus. The primary data was done for point of interest (POI) of permanent sample plots (PSPs) and inventory sample plots, in Aek Nauli sector, Simalungun regency,North Sumatera Province,Indonesia. from December 2008- March 2009. Today,the demand for forestry information has continued to grow over recent years. Because many forest managers and decision makers face complex decisions, reliable information has become the necessity. In the assessment of natural resources including plantation forests have been widely used geospatial technology.The yield of Eucalyptus plantations represented by merchantable volume as dependent variable while factors affecting yield namely stands variables and the geographic variables as independent variables. The majority of the areas in the study site has stand volume class 0 - 50 m3/ha with 16.59 ha or 65.85 % of the total study site.

Estimating yield gaps at the cropping system level.

PubMed

Guilpart, Nicolas; Grassini, Patricio; Sadras, Victor O; Timsina, Jagadish; Cassman, Kenneth G

2017-05-01

Yield gap analyses of individual crops have been used to estimate opportunities for increasing crop production at local to global scales, thus providing information crucial to food security. However, increases in crop production can also be achieved by improving cropping system yield through modification of spatial and temporal arrangement of individual crops. In this paper we define the cropping system yield potential as the output from the combination of crops that gives the highest energy yield per unit of land and time, and the cropping system yield gap as the difference between actual energy yield of an existing cropping system and the cropping system yield potential. Then, we provide a framework to identify alternative cropping systems which can be evaluated against the current ones. A proof-of-concept is provided with irrigated rice-maize systems at four locations in Bangladesh that represent a range of climatic conditions in that country. The proposed framework identified (i) realistic alternative cropping systems at each location, and (ii) two locations where expected improvements in crop production from changes in cropping intensity (number of crops per year) were 43% to 64% higher than from improving the management of individual crops within the current cropping systems. The proposed framework provides a tool to help assess food production capacity of new systems ( e.g. with increased cropping intensity) arising from climate change, and assess resource requirements (water and N) and associated environmental footprint per unit of land and production of these new systems. By expanding yield gap analysis from individual crops to the cropping system level and applying it to new systems, this framework could also be helpful to bridge the gap between yield gap analysis and cropping/farming system design.

Information content of visible and midinfrared radiances for retrieving tropical ice cloud properties

NASA Astrophysics Data System (ADS)

Chang, Kai-Wei; L'Ecuyer, Tristan S.; Kahn, Brian H.; Natraj, Vijay

2017-05-01

Hyperspectral instruments such as Atmospheric Infrared Sounder (AIRS) have spectrally dense observations effective for ice cloud retrievals. However, due to the large number of channels, only a small subset is typically used. It is crucial that this subset of channels be chosen to contain the maximum possible information about the retrieved variables. This study describes an information content analysis designed to select optimal channels for ice cloud retrievals. To account for variations in ice cloud properties, we perform channel selection over an ensemble of cloud regimes, extracted with a clustering algorithm, from a multiyear database at a tropical Atmospheric Radiation Measurement site. Multiple satellite viewing angles over land and ocean surfaces are considered to simulate the variations in observation scenarios. The results suggest that AIRS channels near wavelengths of 14, 10.4, 4.2, and 3.8 μm contain the most information. With an eye toward developing a joint AIRS-MODIS (Moderate Resolution Imaging Spectroradiometer) retrieval, the analysis is also applied to combined measurements from both instruments. While application of this method to MODIS yields results consistent with previous channel sensitivity studies, the analysis shows that this combination may yield substantial improvement in cloud retrievals. MODIS provides most information on optical thickness and particle size, aided by a better constraint on cloud vertical placement from AIRS. An alternate scenario where cloud top boundaries are supplied by the active sensors in the A-train is also explored. The more robust cloud placement afforded by active sensors shifts the optimal channels toward the window region and shortwave infrared, further constraining optical thickness and particle size.

Research in the application of spectral data to crop identification and assessment, volume 2

NASA Technical Reports Server (NTRS)

Daughtry, C. S. T. (Principal Investigator); Hixson, M. M.; Bauer, M. E.

1980-01-01

The development of spectrometry crop development stage models is discussed with emphasis on models for corn and soybeans. One photothermal and four thermal meteorological models are evaluated. Spectral data were investigated as a source of information for crop yield models. Intercepted solar radiation and soil productivity are identified as factors related to yield which can be estimated from spectral data. Several techniques for machine classification of remotely sensed data for crop inventory were evaluated. Early season estimation, training procedures, the relationship of scene characteristics to classification performance, and full frame classification methods were studied. The optimal level for combining area and yield estimates of corn and soybeans is assessed utilizing current technology: digital analysis of LANDSAT MSS data on sample segments to provide area estimates and regression models to provide yield estimates.

Meta-analysis of climate impacts and uncertainty on crop yields in Europe

NASA Astrophysics Data System (ADS)

Knox, Jerry; Daccache, Andre; Hess, Tim; Haro, David

2016-11-01

Future changes in temperature, rainfall and soil moisture could threaten agricultural land use and crop productivity in Europe, with major consequences for food security. We assessed the projected impacts of climate change on the yield of seven major crop types (viz wheat, barley, maize, potato, sugar beet, rice and rye) grown in Europe using a systematic review (SR) and meta-analysis of data reported in 41 original publications from an initial screening of 1748 studies. Our approach adopted an established SR procedure developed by the Centre for Evidence Based Conservation constrained by inclusion criteria and defined methods for literature searches, data extraction, meta-analysis and synthesis. Whilst similar studies exist to assess climate impacts on crop yield in Africa and South Asia, surprisingly, no comparable synthesis has been undertaken for Europe. Based on the reported results (n = 729) we show that the projected change in average yield in Europe for the seven crops by the 2050s is +8%. For wheat and sugar beet, average yield changes of +14% and +15% are projected, respectively. There were strong regional differences with crop impacts in northern Europe being higher (+14%) and more variable compared to central (+6%) and southern (+5) Europe. Maize is projected to suffer the largest negative mean change in southern Europe (-11%). Evidence of climate impacts on yield was extensive for wheat, maize, sugar beet and potato, but very limited for barley, rice and rye. The implications for supporting climate adaptation policy and informing climate impacts crop science research in Europe are discussed.

Separate-channel analysis of two-channel microarrays: recovering inter-spot information.

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.

Groundwater favorability map using GIS multicriteria data analysis on crystalline terrain, São Paulo State, Brazil

NASA Astrophysics Data System (ADS)

Madrucci, Vanessa; Taioli, Fabio; de Araújo, Carlos César

2008-08-01

SummaryThis paper presents the groundwater favorability mapping on a fractured terrain in the eastern portion of São Paulo State, Brazil. Remote sensing, airborne geophysical data, photogeologic interpretation, geologic and geomorphologic maps and geographic information system (GIS) techniques have been used. The results of cross-tabulation between these maps and well yield data allowed groundwater prospective parameters in a fractured-bedrock aquifer. These prospective parameters are the base for the favorability analysis whose principle is based on the knowledge-driven method. The multicriteria analysis (weighted linear combination) was carried out to give a groundwater favorability map, because the prospective parameters have different weights of importance and different classes of each parameter. The groundwater favorability map was tested by cross-tabulation with new well yield data and spring occurrence. The wells with the highest values of productivity, as well as all the springs occurrence are situated in the excellent and good favorability mapped areas. It shows good coherence between the prospective parameters and the well yield and the importance of GIS techniques for definition of target areas for detail study and wells location.

From Observation to Information: Data-Driven Understanding of on Farm Yield Variation

PubMed Central

Jiménez, Daniel; Dorado, Hugo; Cock, James; Prager, Steven D.; Delerce, Sylvain; Grillon, Alexandre; Andrade Bejarano, Mercedes; Benavides, Hector; Jarvis, Andy

2016-01-01

Agriculture research uses “recommendation domains” to develop and transfer crop management practices adapted to specific contexts. The scale of recommendation domains is large when compared to individual production sites and often encompasses less environmental variation than farmers manage. Farmers constantly observe crop response to management practices at a field scale. These observations are of little use for other farms if the site and the weather are not described. The value of information obtained from farmers’ experiences and controlled experiments is enhanced when the circumstances under which it was generated are characterized within the conceptual framework of a recommendation domain, this latter defined by Non-Controllable Factors (NCFs). Controllable Factors (CFs) refer to those which farmers manage. Using a combination of expert guidance and a multi-stage analytic process, we evaluated the interplay of CFs and NCFs on plantain productivity in farmers’ fields. Data were obtained from multiple sources, including farmers. Experts identified candidate variables likely to influence yields. The influence of the candidate variables on yields was tested through conditional forests analysis. Factor analysis then clustered harvests produced under similar NCFs, into Homologous Events (HEs). The relationship between NCFs, CFs and productivity in intercropped plantain were analyzed with mixed models. Inclusion of HEs increased the explanatory power of models. Low median yields in monocropping coupled with the occasional high yields within most HEs indicated that most of these farmers were not using practices that exploited the yield potential of those HEs. Varieties grown by farmers were associated with particular HEs. This indicates that farmers do adapt their management to the particular conditions of their HEs. Our observations confirm that the definition of HEs as recommendation domains at a small-scale is valid, and that the effectiveness of distinct management practices for specific micro-recommendation domains can be identified with the methodologies developed. PMID:26930552

New NIR Calibration Models Speed Biomass Composition and Reactivity Characterization

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

2015-09-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. This highlight describes NREL's work to use near-infrared (NIR) spectroscopy and partial least squares multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. This highlight is being developed for the September 2015 Alliance S&T Board meeting.

Incorporating scale into digital terrain analysis

NASA Astrophysics Data System (ADS)

Dragut, L. D.; Eisank, C.; Strasser, T.

2009-04-01

Digital Elevation Models (DEMs) and their derived terrain attributes are commonly used in soil-landscape modeling. Process-based terrain attributes meaningful to the soil properties of interest are sought to be produced through digital terrain analysis. Typically, the standard 3 X 3 window-based algorithms are used for this purpose, thus tying the scale of resulting layers to the spatial resolution of the available DEM. But this is likely to induce mismatches between scale domains of terrain information and soil properties of interest, which further propagate biases in soil-landscape modeling. We have started developing a procedure to incorporate scale into digital terrain analysis for terrain-based environmental modeling (Drăguţ et al., in press). The workflow was exemplified on crop yield data. Terrain information was generalized into successive scale levels with focal statistics on increasing neighborhood size. The degree of association between each terrain derivative and crop yield values was established iteratively for all scale levels through correlation analysis. The first peak of correlation indicated the scale level to be further retained. While in a standard 3 X 3 window-based analysis mean curvature was one of the poorest correlated terrain attribute, after generalization it turned into the best correlated variable. To illustrate the importance of scale, we compared the regression results of unfiltered and filtered mean curvature vs. crop yield. The comparison shows an improvement of R squared from a value of 0.01 when the curvature was not filtered, to 0.16 when the curvature was filtered within 55 X 55 m neighborhood size. This indicates the optimum size of curvature information (scale) that influences soil fertility. We further used these results in an object-based image analysis environment to create terrain objects containing aggregated values of both terrain derivatives and crop yield. Hence, we introduce terrain segmentation as an alternative method for generating scale levels in terrain-based environmental modeling. Based on segments, R squared improved up to a value of 0.47. Before integrating the procedure described above into a software application, thorough comparison between the results of different generalization techniques, on different datasets and terrain conditions is necessary. This is the subject of our ongoing research as part of the SCALA project (Scales and Hierarchies in Landform Classification). References: Drăguţ, L., Schauppenlehner, T., Muhar, A., Strobl, J. and Blaschke, T., in press. Optimization of scale and parametrization for terrain segmentation: an application to soil-landscape modeling, Computers & Geosciences.

Redundancy in the Iowa Tests of Basic Skills.

ERIC Educational Resources Information Center

Klein, Alice E.

1981-01-01

A factor analysis was performed for two levels of the Iowa Tests of Basic Skills (ITBS). Results showed that there was essentially one common factor with little evidence that the user would gain much nonredundant information from the 15 scores yielded by the ITBS. (Author/GK)

Soft-tissue anatomy of the extant hominoids: a review and phylogenetic analysis.

PubMed

Gibbs, S; Collard, M; Wood, B

2002-01-01

This paper reports the results of a literature search for information about the soft-tissue anatomy of the extant non-human hominoid genera, Pan, Gorilla, Pongo and Hylobates, together with the results of a phylogenetic analysis of these data plus comparable data for Homo. Information on the four extant non-human hominoid genera was located for 240 out of the 1783 soft-tissue structures listed in the Nomina Anatomica. Numerically these data are biased so that information about some systems (e.g. muscles) and some regions (e.g. the forelimb) are over-represented, whereas other systems and regions (e.g. the veins and the lymphatics of the vascular system, the head region) are either under-represented or not represented at all. Screening to ensure that the data were suitable for use in a phylogenetic analysis reduced the number of eligible soft-tissue structures to 171. These data, together with comparable data for modern humans, were converted into discontinuous character states suitable for phylogenetic analysis and then used to construct a taxon-by-character matrix. This matrix was used in two tests of the hypothesis that soft-tissue characters can be relied upon to reconstruct hominoid phylogenetic relationships. In the first, parsimony analysis was used to identify cladograms requiring the smallest number of character state changes. In the second, the phylogenetic bootstrap was used to determine the confidence intervals of the most parsimonious clades. The parsimony analysis yielded a single most parsimonious cladogram that matched the molecular cladogram. Similarly the bootstrap analysis yielded clades that were compatible with the molecular cladogram; a (Homo, Pan) clade was supported by 95% of the replicates, and a (Gorilla, Pan, Homo) clade by 96%. These are the first hominoid morphological data to provide statistically significant support for the clades favoured by the molecular evidence.

76 FR 12072 - Guidance for Agency Information Collection Activities: Proposed Collection; Comment Request...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-04

... not statistical surveys that yield quantitative results that can be generalized to the population of... information will not be used for quantitative information collections that are designed to yield reliably... generic mechanisms that are designed to yield quantitative results. No comments were received in response...

SCA with rotation to distinguish common and distinctive information in linked data.

PubMed

Schouteden, Martijn; Van Deun, Katrijn; Pattyn, Sven; Van Mechelen, Iven

2013-09-01

Often data are collected that consist of different blocks that all contain information about the same entities (e.g., items, persons, or situations). In order to unveil both information that is common to all data blocks and information that is distinctive for one or a few of them, an integrated analysis of the whole of all data blocks may be most useful. Interesting classes of methods for such an approach are simultaneous-component and multigroup factor analysis methods. These methods yield dimensions underlying the data at hand. Unfortunately, however, in the results from such analyses, common and distinctive types of information are mixed up. This article proposes a novel method to disentangle the two kinds of information, by making use of the rotational freedom of component and factor models. We illustrate this method with data from a cross-cultural study of emotions.

Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants.

PubMed

Iso-Touru, T; Sahana, G; Guldbrandtsen, B; Lund, M S; Vilkki, J

2016-03-22

The Nordic Red Cattle consisting of three different populations from Finland, Sweden and Denmark are under a joint breeding value estimation system. The long history of recording of production and health traits offers a great opportunity to study production traits and identify causal variants behind them. In this study, we used whole genome sequence level data from 4280 progeny tested Nordic Red Cattle bulls to scan the genome for loci affecting milk, fat and protein yields. Using a genome-wise significance threshold, regions on Bos taurus chromosomes 5, 14, 23, 25 and 26 were associated with fat yield. Regions on chromosomes 5, 14, 16, 19, 20 and 25 were associated with milk yield and chromosomes 5, 14 and 25 had regions associated with protein yield. Significantly associated variations were found in 227 genes for fat yield, 72 genes for milk yield and 30 genes for protein yield. Ingenuity Pathway Analysis was used to identify networks connecting these genes displaying significant hits. When compared to previously mapped genomic regions associated with fertility, significantly associated variations were found in 5 genes common for fat yield and fertility, thus linking these two traits via biological networks. This is the first time when whole genome sequence data is utilized to study genomic regions affecting milk production in the Nordic Red Cattle population. Sequence level data offers the possibility to study quantitative traits in detail but still cannot unambiguously reveal which of the associated variations is causative. Linkage disequilibrium creates difficulties to pinpoint the causative genes and variations. One solution to overcome these difficulties is the identification of the functional gene networks and pathways to reveal important interacting genes as candidates for the observed effects. This information on target genomic regions may be exploited to improve genomic prediction.

Satellite-based studies of maize yield spatial variations and their causes in China

NASA Astrophysics Data System (ADS)

Zhao, Y.

2013-12-01

Maize production in China has been expanding significantly in the past two decades, but yield has become relatively stagnant in the past few years, and needs to be improved to meet increasing demand. Multiple studies found that the gap between potential and actual yield of maize is as large as 40% to 60% of yield potential. Although a few major causes of yield gap have been qualitatively identified with surveys, there has not been spatial analysis aimed at quantifying relative importance of specific biophysical and socio-economic causes, information which would be useful for targeting interventions. This study analyzes the causes of yield variation at field and village level in Quzhou county of North China Plain (NCP). We combine remote sensing and crop modeling to estimate yields in 2009-2012, and identify fields that are consistently high or low yielding. To establish the relationship between yield and potential factors, we gather data on those factors through a household survey. We select targeted survey fields such that not only both extremes of yield distribution but also all soil texture categories in the county is covered. Our survey assesses management and biophysical factors as well as social factors such as farmers' access to agronomic knowledge, which is approximated by distance to the closest demonstration plot or 'Science and technology backyard'. Our survey covers 10 townships, 53 villages and 180 fields. Three to ten farmers are surveyed depending on the amount of variation present among sub pixels of each field. According to survey results, we extract the amount of variation within as well as between villages and or soil type. The higher within village or within field variation, the higher importance of management factors. Factors such as soil type and access to knowledge are more represented by between village variation. Through regression and analysis of variance, we gain more quantitative and thorough understanding of causes to yield variation at village scale, which further explains the gap between average and highest achieved yield.

An Information Transmission Measure for the Analysis of Effective Connectivity among Cortical Neurons

PubMed Central

Law, Andrew J.; Sharma, Gaurav; Schieber, Marc H.

2014-01-01

We present a methodology for detecting effective connections between simultaneously recorded neurons using an information transmission measure to identify the presence and direction of information flow from one neuron to another. Using simulated and experimentally-measured data, we evaluate the performance of our proposed method and compare it to the traditional transfer entropy approach. In simulations, our measure of information transmission outperforms transfer entropy in identifying the effective connectivity structure of a neuron ensemble. For experimentally recorded data, where ground truth is unavailable, the proposed method also yields a more plausible connectivity structure than transfer entropy. PMID:21096617

Responses of Teachers and Non-Teachers Regarding Placement of Exceptional Children. Final Report.

ERIC Educational Resources Information Center

Phelps, William R.

Evaluated were opinions of 10 teachers and 10 nonteachers on educational placement of children with such handicaps as orthopedic, visual, and speech problems. Analysis of questionnaires yielded the following information: the major differences centered on placement for the emotionally disturbed, hearing impaired, orthopedically handicapped, and…

Content Analysis of Teenaged Interviews for Designing Drug Programs.

ERIC Educational Resources Information Center

Bell, Edward V.

1980-01-01

Analyses of the data and youths' prescriptions concerning prevention of abuse yielded 12 program recommendations. These programs can create the awareness that led to concerted programs to stop the war and pollution. When designing educational-information programs, one must be aware of the total system of causal factors. (Author/BEF)

Thermogravimetric and differential thermal analysis of potassium bicarbonate contaminated cellulose

Treesearch

A. Broido

1966-01-01

When samples undergo a complicated set of simultaneous and sequential reactions, as cellulose does on heating, results of thermogravimetric and differential thermal analyses are difficult to interpret. Nevertheless, careful comparison of pure and contaminated samples, pyrolyzed under identical conditions, can yield useful information. In these experiments TGA and DTA...

Analysts guide: TreeVal for Windows, Version 2.0.

Treesearch

R.D. Fight; J.T. Chmelik; E.A. Coulter

2001-01-01

TreeVal for Windows provides financial information and analysis to support silvicultural decisions in coast Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco). It integrates the effect of growth and yield, management costs, harvesting costs, product and mill type, manufacturing costs, product prices, and product grade premiums. Output files from...

Advancements in LiDAR-based registration of FIA field plots

Treesearch

Demetrios Gatziolis

2012-01-01

Meaningful integration of National Forest Inventory field plot information with spectral imagery acquired from satellite or airborne platforms requires precise plot registration. Global positioning system-based plot registration procedures, such as the one employed by the Forest Inventory and Analysis (FIA) Program, yield plot coordinates that, although adequate for...

The open-source movement: an introduction for forestry professionals

Treesearch

Patrick Proctor; Paul C. Van Deusen; Linda S. Heath; Jeffrey H. Gove

2005-01-01

In recent years, the open-source movement has yielded a generous and powerful suite of software and utilities that rivals those developed by many commercial software companies. Open-source programs are available for many scientific needs: operating systems, databases, statistical analysis, Geographic Information System applications, and object-oriented programming....

The Rest of the Story: A Qualitative Study of Complementing Standardized Assessment Data with Informal Interviews with Older Patients and Families.

PubMed

Lafortune, Claire; Elliott, Jacobi; Egan, Mary Y; Stolee, Paul

2017-04-01

While standardized health assessments capture valuable information on patients' demographic and diagnostic characteristics, health conditions, and physical and mental functioning, they may not capture information of most relevance to individual patients and their families. Given that patients and their informal caregivers are the experts on that patient's unique context, it is important to ensure they are able to convey all relevant personal information to formal healthcare providers so that high-quality, patient-centered care may be delivered. This study aims to identify information that older patients and families consider important but that might not be included in standardized assessments. Transcripts were analyzed from 29 interviews relating to eight patients with hip fractures from three sites (large urban, smaller urban, rural) in two provinces in Canada. These interviews were conducted as part of a larger ethnographic study. Each transcript was analyzed by two researchers using content analysis. Results were reviewed in two focus group interviews with older adults and family caregivers. Identified themes were compared with items from two standardized assessments used in healthcare settings. Three broad themes emerged from the qualitative analysis that were not covered in the standardized assessments: informal caregiver and family considerations, insider healthcare knowledge, and patients' healthcare attitudes and experiences. The importance of these themes was confirmed through focus group interviews. Focus group participants also emphasized the importance of conducting assessments in a patient-centered way and the importance of open-ended questions. A less structured interview approach may yield information that would otherwise be missed in standardized assessments. Combining both sources could yield better-informed healthcare planning and quality-improvement efforts.

Genetic analysis of Holstein cattle populations in Brazil and the United States.

PubMed

Costa, C N; Blake, R W; Pollak, E J; Oltenacu, P A; Quaas, R L; Searle, S R

2000-12-01

Genetic relationships between Brazilian and US Holstein cattle populations were studied using first-lactation records of 305-d mature equivalent (ME) yields of milk and fat of daughters of 705 sires in Brazil and 701 sires in the United States, 358 of which had progeny in both countries. Components of(co)variance and genetic parameters were estimated from all data and from within herd-year standard deviation for milk (HYSD) data files using bivariate and multivariate sire models and DFREML procedures distinguishing the two countries. Sire (residual) variances from all data for milk yield were 51 to 59% (58 to 101%) as large in Brazil as those obtained from half-sisters in the average US herd. Corresponding proportions of the US variance in fat yield that were found in Brazil were 30 to 41% for the sire component of variance and 48 to 80% for the residual. Heritabilities for milk and fat yields from multivariate analysis of all the data were 0.25 and 0.22 in Brazil, and 0.34 and 0.35 in the United States. Genetic correlations between milk and fat were 0.79 in Brazil and 0.62 in the United States. Genetic correlations between countries were 0.85 for milk, 0.88 for fat, 0.55 for milk in Brazil and fat in the US, and 0.67 for fat in Brazil and milk in the United States. Correlated responses in Brazil from sire selection based on the US information increased with average HYSD in Brazil. Largest daughter yield response was predicted from information from half-sisters in low HYSD US herds (0.75 kg/kg for milk; 0.63 kg/kg for fat), which was 14% to 17% greater than estimates from all US herds because the scaling effects were less severe from heterogeneous variances. Unequal daughter response from unequal genetic (co)variances under restrictive Brazilian conditions is evidence for the interaction of genotype and environment. The smaller and variable yield expectations of daughters of US sires in Brazilian environments suggest the need for specific genetic improvement strategies in Brazilian Holstein herds. A US data file restricting daughter information to low HYSD US environments would be a wise choice for across-country evaluation. Procedures to incorporate such foreign evaluations should be explored to improve the accuracy of genetic evaluations for the Brazilian Holstein population.

Comparison of CEAS and Williams-type models for spring wheat yields in North Dakota and Minnesota

NASA Technical Reports Server (NTRS)

Barnett, T. L. (Principal Investigator)

1982-01-01

The CEAS and Williams-type yield models are both based on multiple regression analysis of historical time series data at CRD level. The CEAS model develops a separate relation for each CRD; the Williams-type model pools CRD data to regional level (groups of similar CRDs). Basic variables considered in the analyses are USDA yield, monthly mean temperature, monthly precipitation, and variables derived from these. The Williams-type model also used soil texture and topographic information. Technological trend is represented in both by piecewise linear functions of year. Indicators of yield reliability obtained from a ten-year bootstrap test of each model (1970-1979) demonstrate that the models are very similar in performance in all respects. Both models are about equally objective, adequate, timely, simple, and inexpensive. Both consider scientific knowledge on a broad scale but not in detail. Neither provides a good current measure of modeled yield reliability. The CEAS model is considered very slightly preferable for AgRISTARS applications.

Mapping Quantitative Trait Loci Associated with Toot Traits Using Sequencing-Based Genotyping Chromosome Segment Substitution Lines Derived from 9311 and Nipponbare in Rice (Oryza sativa L.).

PubMed

Zhou, Yong; Dong, Guichun; Tao, Yajun; Chen, Chen; Yang, Bin; Wu, Yue; Yang, Zefeng; Liang, Guohua; Wang, Baohe; Wang, Yulong

2016-01-01

Identification of quantitative trait loci (QTLs) associated with rice root morphology provides useful information for avoiding drought stress and maintaining yield production under the irrigation condition. In this study, a set of chromosome segment substitution lines derived from 9311 as the recipient and Nipponbare as donor, were used to analysis root morphology. By combining the resequencing-based bin-map with a multiple linear regression analysis, QTL identification was conducted on root number (RN), total root length (TRL), root dry weight (RDW), maximum root length (MRL), root thickness (RTH), total absorption area (TAA) and root vitality (RV), using the CSSL population grown under hydroponic conditions. A total of thirty-eight QTLs were identified: six for TRL, six for RDW, eight for the MRL, four for RTH, seven for RN, two for TAA, and five for RV. Phenotypic effect variance explained by these QTLs ranged from 2.23% to 37.08%, and four single QTLs had more than 10% phenotypic explanations on three root traits. We also detected the correlations between grain yield (GY) and root traits, and found that TRL, RTH and MRL had significantly positive correlations with GY. However, TRL, RDW and MRL had significantly positive correlations with biomass yield (BY). Several QTLs identified in our population were co-localized with some loci for grain yield or biomass. This information may be immediately exploited for improving rice water and fertilizer use efficiency for molecular breeding of root system architectures.

Chlorophyll Fluorescence Analysis of Cyanobacterial Photosynthesis and Acclimation

PubMed Central

Campbell, Douglas; Hurry, Vaughan; Clarke, Adrian K.; Gustafsson, Petter; Öquist, Gunnar

1998-01-01

Cyanobacteria are ecologically important photosynthetic prokaryotes that also serve as popular model organisms for studies of photosynthesis and gene regulation. Both molecular and ecological studies of cyanobacteria benefit from real-time information on photosynthesis and acclimation. Monitoring in vivo chlorophyll fluorescence can provide noninvasive measures of photosynthetic physiology in a wide range of cyanobacteria and cyanolichens and requires only small samples. Cyanobacterial fluorescence patterns are distinct from those of plants, because of key structural and functional properties of cyanobacteria. These include significant fluorescence emission from the light-harvesting phycobiliproteins; large and rapid changes in fluorescence yield (state transitions) which depend on metabolic and environmental conditions; and flexible, overlapping respiratory and photosynthetic electron transport chains. The fluorescence parameters FV/FM, FV′/FM′,qp,qN, NPQ, and φPS II were originally developed to extract information from the fluorescence signals of higher plants. In this review, we consider how the special properties of cyanobacteria can be accommodated and used to extract biologically useful information from cyanobacterial in vivo chlorophyll fluorescence signals. We describe how the pattern of fluorescence yield versus light intensity can be used to predict the acclimated light level for a cyanobacterial population, giving information valuable for both laboratory and field studies of acclimation processes. The size of the change in fluorescence yield during dark-to-light transitions can provide information on respiration and the iron status of the cyanobacteria. Finally, fluorescence parameters can be used to estimate the electron transport rate at the acclimated growth light intensity. PMID:9729605

Modelling heterogeneity variances in multiple treatment comparison meta-analysis--are informative priors the better solution?

PubMed

Thorlund, Kristian; Thabane, Lehana; Mills, Edward J

2013-01-11

Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the 'common variance' assumption). This approach 'borrows strength' for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice.

Analysis of Biomass Feedstock Availability and Variability for the Peace River Region of Alberta, Canada

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

Stephen, Jamie; Sokhansanj, Shahabaddine; Bi, X.T.

2009-11-01

Biorefineries or other biomass-dependent facilities require a predictable, dependable feedstock supplied over many years to justify capital investments. Determining inter-year variability in biomass availability is essential to quantifying the feedstock supply risk. Using a geographic information system (GIS) and historic crop yield data, average production was estimated for 10 sites in the Peace River region of Alberta, Canada. Four high-yielding potential sites were investigated for variability over a 20 year time-frame (1980 2000). The range of availability was large, from double the average in maximum years to nothing in minimum years. Biomass availability is a function of grain yield, themore » biomass to grain ratio, the cropping frequency, and residue retention rate to ensure future crop productivity. Storage strategies must be implemented and alternate feedstock sources identified to supply biomass processing facilities in low-yield years.« less

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy.

PubMed

Payne, Courtney E; Wolfrum, Edward J

2015-01-01

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. We present individual model statistics to demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. It is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.

Growth and yield of shortleaf pine

Treesearch

Paul A. Murphy

1986-01-01

A survey of available growth and yield information for shortleaf pine (Pinus echinata Mill.) is given. The kinds of studies and data sources that produce this information are also evaluated, and an example of how a growth and yield model can be used to answer management questions is illustrated. Guidelines are given for using growth and yield models, and needs for...

Environmental Assessment for Aviation Foreign Internal Defense Beddown (AvFID) at Duke Field, Eglin Air Force Base, Florida

DTIC Science & Technology

2012-07-01

yielded, or may be likely to yield, information important in prehistory or history” (36 CFR § 60:4). 3.8.2 Existing Conditions The ROI for...components may lack individual distinction; or d) that have yielded, or may be likely to yield, information important in prehistory or history (Advisory

Genetic evaluation of recombinant inbred lines of rice (Oryza sativa L.) for grain zinc concentrations, yield related traits and identification of associated SSR markers.

PubMed

Bekele, Berhanu D; Naveen, G K; Rakhi, S; Shashidhar, H E

2013-12-01

The objectives of the present study were to evaluate genetic variability parameters, correlations that exist for grain Zn concentration and yield related traits and identification of SSR markers linked to these traits in rice. One hundred seventy six Recombinant Inbred Lines (RILs) of Azucena X Moromutant were grown at University of Agricultural Sciences, Bangalore in augmented experimental design during wet seasons of 2010 and 2011. The study revealed significant genetic variability for all the traits. Grain yield per plant and grain zinc concentration showed higher phenotypic and genotypic co-efficient of variation. Significant positive correlation was observed for grain yield per plant with number of productive tillers per plant (r = 0.5) and number of tillers per plant (r = 0.4). Grain zinc concentration showed negative correlation with grain yield per plant (r = - 0.27). The path-coefficient analysis indicated the positive direct effect of number of productive tillers per plant on grain yield per plant (0.514). Grain zinc concentration showed negative direct effect on grain yield per plant (-0.186). Single-marker analysis using 26 SSR markers on RILs mapping population showed that RM212, RM263, RM6832, RM152, RM21, RM234 and RM3331 had association with grain zinc concentration and other yield related traits. But validation of these markers on fifty two rice genotypes showed that only three markers RM263, RM152 and RM21 had association with grain zinc concentration. Therefore, the genetic information generated and molecular markers identified from this study could be used for zinc biofortification programmes in rice.

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

Hirokawa, Takako; /U. Colorado, Boulder /SLAC

In this paper, we examine data acquisition in a high harmonic generation (HHG) lab and preliminary data analysis with the Cyclohexadiene Collaboration at the Linac Coherent Lightsource (LCLS) at SLAC National Accelerator Laboratory. HHG experiments have a large number of parameters that need to be monitored constantly. In particular, the pressure of the target is critical to HHG yield. However, this pressure can fluctuate wildly and without a tool to monitor it, it is difficult to analyze the correlation between HHG yield and the pressure. I used the Arduino microcontroller board and created a complementary MATLAB graphical user interface (GUI),more » thereby enhancing the ease with which users can acquire time-stamped parameter data. Using the Arduino, it is much easier to match the pressure to the corresponding HHG yield. Collecting data by using the Arduino and the GUI is flexible, user-friendly, and cost-effective. In the future, we hope to be able to control and monitor parts of the lab with the Arduino alone. While more parameter information is needed in the HHG lab, we needed to reduce the amount of data during the cyclohexadiene collaboration. This was achieved by sorting the data into bins and filtering out unnecessary details. This method was highly effective in that it minimized the amount of data without losing any valuable information. This effective preliminary data analysis technique will continue to be used to decrease the size of the collected data.« less

Raman spectroscopic study of reaction dynamics

NASA Astrophysics Data System (ADS)

MacPhail, R. A.

1990-12-01

The Raman spectra of reacting molecules in liquids can yield information about various aspects of the reaction dynamics. The author discusses the analysis of Raman spectra for three prototypical unimolecular reactions, the rotational isomerization of n-butane and 1,2-difluoroethane, and the barrierless exchange of axial and equatorial hydrogens in cyclopentane via pseudorotation. In the first two cases the spectra are sensitive to torsional oscillations of the gauche conformer, and yield estimates of the torsional solvent friction. In the case of cyclopentane, the spectra can be used to discriminate between different stochastic models of the pseudorotation dynamics, and to determine the relevant friction coefficients.

World Opinion and the Soviet Satellite: A Preliminary Evaluation

NASA Technical Reports Server (NTRS)

1957-01-01

Less than two weeks after the launch of Sputnik I, the United States Information Agency conducted an informal analysis of public opinion on this subject. The analysis yielded four clear conclusions: (1) Soviet claims of scientific and technological superiority were widely accepted in the United States; (2) U.S. allies were concerned about a shift in the balance of military power; (3) the overall credibility of Soviet propaganda was greatly strengthened; and (4) American prestige was dealt a severe blow. The report also concluded that the near-hysteria in the United States in turn increased the level of concern in countries friendly to the United States. An evaluation is presented.

Polarimetric Wavelet Fractal Remote Sensing Principles for Space Materials (Preprint)

DTIC Science & Technology

2012-06-04

previously introduced 9-10, 28. The combination of polarimetry and wavelet-fractal analysis yields enhanced knowledge of the spatial-temporal-frequency...applications in situations that require analysis over very short time durations or where information is localized, and have been combined with polarimetry ...and D.B. Chenault, “Near Infrared Imaging Polarimetry ”, Proc. SPIE 4481, pp. 30-31, 2001. [8] A.B. Mahler, P. Smith, R. Chipman, G. Smith, N

Meta-analysis to refine map position and reduce confidence intervals for delayed canopy wilting QTLs in soybean

USDA-ARS?s Scientific Manuscript database

Slow canopy wilting in soybean has been identified as a potentially beneficial trait for ameliorating drought effects on yield. Previous research identified QTLs for slow wilting from two different bi-parental populations and this information was combined with data from three other populations to id...

Using within-day hive weight changes to measure environmental effects on honey bee colonies

USDA-ARS?s Scientific Manuscript database

Patterns in within-day hive weight data from two independent datasets in Arizona and California were modeled using piecewise regression, and analyzed with respect to honey bee colony behavior and landscape effects. The regression analysis yielded information on the start and finish of a colony’s dai...

Study of Faculty and Information Technology, 2014

ERIC Educational Resources Information Center

Dahlstrom, Eden; Brooks, D. Christopher

2014-01-01

In this inaugural year of the faculty technology study, EDUCAUSE Center for Analysis and Research (ECAR) partnered with 151 college/university sites yielding responses from 17,451 faculty respondents across 13 countries. The findings are exploratory in nature, as they cover new ground to help us tell a more comprehensive story about technology…

Algebra for Everyone? Student Perceptions of Tracking in Mathematics

ERIC Educational Resources Information Center

Spielhagen, Frances R.

2010-01-01

This research explored the experiences of students in a school district that limited early access to the study of algebra and to inform education policymakers of the impact of such tracking policies on the lives and futures of the students. Quantitative analysis had already yielded a snapshot of inequities deriving from the policies surrounding…

Psychometric analysis of five measures of spatial ability.

PubMed

Hogan, Thomas P

2012-02-01

This study analyzed psychometric properties of five measures of spatial ability on 96 young adults, with supplementary analysis for three of the measures on another sample of 71 young adults. Two measures were taken from the widely cited Kit of Factor-Referenced Cognitive Tests and three other measures were taken from a relatively new source originally intended as laboratory demonstrations. Previous research provided limited information on the psychometric properties of the measures. All five measures yielded adequate reliability and loaded on a single factor. Three measures yielded markedly skewed distributions. Two measures showed clear sex differences with men scoring higher but this difference seemed contaminated by a speed factor; three measures did not show a sex difference. Recommendations for use of the measures in future studies are provided.

Microscopic analysis of currency and stock exchange markets.

PubMed

Kador, L

1999-08-01

Recently it was shown that distributions of short-term price fluctuations in foreign-currency exchange exhibit striking similarities to those of velocity differences in turbulent flows. Similar profiles represent the spectral-diffusion behavior of impurity molecules in disordered solids at low temperatures. It is demonstrated that a microscopic statistical theory of the spectroscopic line shapes can be applied to the other two phenomena. The theory interprets the financial data in terms of information which becomes available to the traders and their reactions as a function of time. The analysis shows that there is no characteristic time scale in financial markets, but that instead stretched-exponential or algebraic memory functions yield good agreement with the price data. For an algebraic function, the theory yields truncated Lévy distributions which are often observed in stock exchange markets.

Microscopic analysis of currency and stock exchange markets

NASA Astrophysics Data System (ADS)

Kador, L.

1999-08-01

Recently it was shown that distributions of short-term price fluctuations in foreign-currency exchange exhibit striking similarities to those of velocity differences in turbulent flows. Similar profiles represent the spectral-diffusion behavior of impurity molecules in disordered solids at low temperatures. It is demonstrated that a microscopic statistical theory of the spectroscopic line shapes can be applied to the other two phenomena. The theory interprets the financial data in terms of information which becomes available to the traders and their reactions as a function of time. The analysis shows that there is no characteristic time scale in financial markets, but that instead stretched-exponential or algebraic memory functions yield good agreement with the price data. For an algebraic function, the theory yields truncated Lévy distributions which are often observed in stock exchange markets.

GM(1,N) method for the prediction of anaerobic digestion system and sensitivity analysis of influential factors.

PubMed

Ren, Jingzheng

2018-01-01

Anaerobic digestion process has been recognized as a promising way for waste treatment and energy recovery in a sustainable way. Modelling of anaerobic digestion system is significantly important for effectively and accurately controlling, adjusting, and predicting the system for higher methane yield. The GM(1,N) approach which does not need the mechanism or a large number of samples was employed to model the anaerobic digestion system to predict methane yield. In order to illustrate the proposed model, an illustrative case about anaerobic digestion of municipal solid waste for methane yield was studied, and the results demonstrate that GM(1,N) model can effectively simulate anaerobic digestion system at the cases of poor information with less computational expense. Copyright © 2017 Elsevier Ltd. All rights reserved.

Construction of phylogenetic trees by kernel-based comparative analysis of metabolic networks.

PubMed

Oh, S June; Joung, Je-Gun; Chang, Jeong-Ho; Zhang, Byoung-Tak

2006-06-06

To infer the tree of life requires knowledge of the common characteristics of each species descended from a common ancestor as the measuring criteria and a method to calculate the distance between the resulting values of each measure. Conventional phylogenetic analysis based on genomic sequences provides information about the genetic relationships between different organisms. In contrast, comparative analysis of metabolic pathways in different organisms can yield insights into their functional relationships under different physiological conditions. However, evaluating the similarities or differences between metabolic networks is a computationally challenging problem, and systematic methods of doing this are desirable. Here we introduce a graph-kernel method for computing the similarity between metabolic networks in polynomial time, and use it to profile metabolic pathways and to construct phylogenetic trees. To compare the structures of metabolic networks in organisms, we adopted the exponential graph kernel, which is a kernel-based approach with a labeled graph that includes a label matrix and an adjacency matrix. To construct the phylogenetic trees, we used an unweighted pair-group method with arithmetic mean, i.e., a hierarchical clustering algorithm. We applied the kernel-based network profiling method in a comparative analysis of nine carbohydrate metabolic networks from 81 biological species encompassing Archaea, Eukaryota, and Eubacteria. The resulting phylogenetic hierarchies generally support the tripartite scheme of three domains rather than the two domains of prokaryotes and eukaryotes. By combining the kernel machines with metabolic information, the method infers the context of biosphere development that covers physiological events required for adaptation by genetic reconstruction. The results show that one may obtain a global view of the tree of life by comparing the metabolic pathway structures using meta-level information rather than sequence information. This method may yield further information about biological evolution, such as the history of horizontal transfer of each gene, by studying the detailed structure of the phylogenetic tree constructed by the kernel-based method.

Targeting the right input data to improve crop modeling at global level

NASA Astrophysics Data System (ADS)

Adam, M.; Robertson, R.; Gbegbelegbe, S.; Jones, J. W.; Boote, K. J.; Asseng, S.

2012-12-01

Designed for location-specific simulations, the use of crop models at a global level raises important questions. Crop models are originally premised on small unit areas where environmental conditions and management practices are considered homogeneous. Specific information describing soils, climate, management, and crop characteristics are used in the calibration process. However, when scaling up for global application, we rely on information derived from geographical information systems and weather generators. To run crop models at broad, we use a modeling platform that assumes a uniformly generated grid cell as a unit area. Specific weather, specific soil and specific management practices for each crop are represented for each of the cell grids. Studies on the impacts of the uncertainties of weather information and climate change on crop yield at a global level have been carried out (Osborne et al, 2007, Nelson et al., 2010, van Bussel et al, 2011). Detailed information on soils and management practices at global level are very scarce but recognized to be of critical importance (Reidsma et al., 2009). Few attempts to assess the impact of their uncertainties on cropping systems performances can be found. The objectives of this study are (i) to determine sensitivities of a crop model to soil and management practices, inputs most relevant to low input rainfed cropping systems, and (ii) to define hotspots of sensitivity according to the input data. We ran DSSAT v4.5 globally (CERES-CROPSIM) to simulate wheat yields at 45arc-minute resolution. Cultivar parameters were calibrated and validated for different mega-environments (results not shown). The model was run for nitrogen-limited production systems. This setting was chosen as the most representative to simulate actual yield (especially for low-input rainfed agricultural systems) and assumes crop growth to be free of any pest and diseases damages. We conducted a sensitivity analysis on contrasting management practices, initial soil conditions, and soil characteristics information. Management practices were represented by planting date and the amount of fertilizer, initial conditions estimates for initial nitrogen, soil water, and stable soil carbon, and soil information is based on a simplified version of the WISE database, characterized by soil organic matter, texture and soil depth. We considered these factors as the most important determinants of nutrient supply to crops during their growing season. Our first global results demonstrate that the model is most sensitive to the initial conditions in terms of soil carbon and nitrogen (CN): wheat yields decreased by 45% when soil CN is null and increase by 15% when twice the soil CN content of the reference run is used. The yields did not appear to be very sensitive to initial soil water conditions, varying from 0% yield increase when initial soil water is set to wilting point to 6% yield increase when it was set to field capacity. They are slightly sensitive to nitrogen application: 8% yield decrease when no N is applied to 9% yield increase when 150 kg.ha-1 is applied. However, with closer examination of results, the model is more sensitive to nitrogen application than to initial soil CN content in Vietnam, Thailand and Japan compared to the rest of the world. More analyses per region and results on the planting dates and soil properties will be presented.

Infant search and object permanence: a meta-analysis of the A-not-B error.

PubMed

Wellman, H M; Cross, D; Bartsch, K

1987-01-01

Research on Piaget's stage 4 object concept has failed to reveal a clear or consistent pattern of results. Piaget found that 8-12-month-old infants would make perserverative errors; his explanation for this phenomenon was that the infant's concept of the object was contextually dependent on his or her actions. Some studies designed to test Piaget's explanation have replicated Piaget's basic finding, yet many have found no preference for the A location or the B location or an actual preference for the B location. More recently, researchers have attempted to uncover the causes for these results concerning the A-not-B error. Again, however, different studies have yielded different results, and qualitative reviews have failed to yield a consistent explanation for the results of the individual studies. This state of affairs suggests that the phenomenon may simply be too complex to be captured by individual studies varying 1 factor at a time and by reviews based on similar qualitative considerations. Therefore, the current investigation undertook a meta-analysis, a synthesis capturing the quantitative information across the now sizable number of studies. We entered several important factors into the meta-analysis, including the effects of age, the number of A trials, the length of delay between hiding and search, the number of locations, the distances between locations, and the distinctive visual properties of the hiding arrays. Of these, the analysis consistently indicated that age, delay, and number of hiding locations strongly influence infants' search. The pattern of specific findings also yielded new information about infant search. A general characterization of the results is that, at every age, both above-chance and below-chance performance was observed. That is, at each age at least 1 combination of delay and number of locations yielded above-chance A-not-B errors or significant perseverative search. At the same time, at each age at least 1 alternative combination of delay and number of locations yielded below-chance errors and significant above-chance correct performance, that is, significantly accurate search. These 2 findings, appropriately elaborated, allow us to evaluate all extant theories of stage 4 infant search. When this is done, all these extant accounts prove to be incorrect. That is, they are incommensurate with one aspect or another of the pooled findings in the meta-analysis. Therefore, we end by proposing a new account that is consistent with the entire data set.

76 FR 63301 - Agency Information Collection Activities: Proposed Collection; Comment Request; Generic Clearance...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-12

... INFORMATION: Title: Comparative Effectiveness Research Inventory. Abstract: The information collection... will not be used for quantitative information collections that are designed to yield reliably... mechanisms that are designed to yield quantitative results. The Agency received no comments in response to...

76 FR 13018 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-09

... statistical surveys that yield quantitative results that can be generalized to the population of study. This... information will not be used for quantitative information collections that are designed to yield reliably... generic mechanisms that are designed to yield quantitative results. Total Burden Estimate for the...

Advanced Weapon System (AWS) Sensor Prediction Techniques Study. Volume II

DTIC Science & Technology

1981-09-01

models are suggested. TV. 1-1 ’ICourant Com’p’uter Sctence Report #9 December 1975 Scene Analysis: A Survey Carl Weiman Cou rant Institute of...some crucial differences. In the psycho- logical model of mechanical vision, the aim of scene analysis is to perceive and understand 2-0 images of 3-D...scenes. The meaning of this analogy can be clarified using a rudimentary informational model ; this yields a natural hierarchy from physical

Decision curve analysis: a novel method for evaluating prediction models.

PubMed

Vickers, Andrew J; Elkin, Elena B

2006-01-01

Diagnostic and prognostic models are typically evaluated with measures of accuracy that do not address clinical consequences. Decision-analytic techniques allow assessment of clinical outcomes but often require collection of additional information and may be cumbersome to apply to models that yield a continuous result. The authors sought a method for evaluating and comparing prediction models that incorporates clinical consequences,requires only the data set on which the models are tested,and can be applied to models that have either continuous or dichotomous results. The authors describe decision curve analysis, a simple, novel method of evaluating predictive models. They start by assuming that the threshold probability of a disease or event at which a patient would opt for treatment is informative of how the patient weighs the relative harms of a false-positive and a false-negative prediction. This theoretical relationship is then used to derive the net benefit of the model across different threshold probabilities. Plotting net benefit against threshold probability yields the "decision curve." The authors apply the method to models for the prediction of seminal vesicle invasion in prostate cancer patients. Decision curve analysis identified the range of threshold probabilities in which a model was of value, the magnitude of benefit, and which of several models was optimal. Decision curve analysis is a suitable method for evaluating alternative diagnostic and prognostic strategies that has advantages over other commonly used measures and techniques.

Evaluation of a Prison Occupational Therapy Informal Education Program: A Pilot Study.

PubMed

Crabtree, Jeffrey L; Ohm, David; Wall, Jarrod M; Ray, Joseph

2016-12-01

This pilot study explored the strengths and weaknesses of an informal education program and identified elements of the program valued by participants. Participants were men living in a minimum security prison who had been incarcerated for ten or more years. The outside researcher was joined by three former program participants as co-researchers. Together, they interviewed 27 residents who completed the informal education program. Interviews were transcribed and de-identified. Researchers used the summative content analysis approach to analyze the data. Initial content analysis yielded five concepts: doing (engaging in purposeful activities); information (program handouts and discussions that included data and descriptions of all of the topics discussed); re-entry fears (socialization; making amends with victims and/or reuniting with family and friends); technology (includes, but not limited to, using smartphones, internet and other technology in all areas of occupation); and self-worth as a person. Further interpretation per the summative content analysis method yielded three themes: doing (engaged in purposeful activities), validation of self-worth (confirmation of being a valued human being in spite of having committed a serious crime) and concerns about the future (being able to successfully engage in virtually all occupations). Whilst informal education programs may help people who are incarcerated gain information, gain a sense of self-worth and allay some reentry fears, understanding the long-term affect such programs may have such as preparing them for successful re-entry to society or reducing recidivism rates, will require long-term follow-up. Regardless of the occupational therapy intervention, the practice of occupational therapy in the criminal justice system needs to be client-centred. Because of the small number of participants and limited access to participants, one should not generalize the findings of this study to other situations or populations. Further research to examine the effectiveness of an occupational therapy education program is warranted. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

The Plastic Surgery Match: A Quantitative Analysis of Applicant Impressions From the Interview Visit.

PubMed

Frojo, Gianfranco; Tadisina, Kashyap Komarraju; Pressman, Zachary; Chibnall, John T; Lin, Alexander Y; Kraemer, Bruce A

2016-12-01

The integrated plastic surgery match is a competitive process not only for applicants but also for programs vying for highly qualified candidates. Interactions between applicants and program constituents are limited to a single interview visit. The authors aimed to identify components of the interview visit that influence applicant decision making when determining a final program rank list. Thirty-six applicants who were interviewed (100% response) completed the survey. Applicants rated the importance of 20 elements of the interview visit regarding future ranking of the program on a 1 to 5 Likert scale. Data were analyzed using descriptive statistics, hierarchical cluster analysis, analysis of variance, and Pearson correlations. A literature review was performed regarding the plastic surgery integrated residency interview process. Survey questions were categorized into four groups based on mean survey responses:1. Interactions with faculty and residents (mean response > 4),2. Information about the program (3.5-4),3. Ancillaries (food, amenities, stipends) (3-3.5),4. Hospital tour, hotel (<3).Hierarchical item cluster analysis and analysis of variance testing validated these groupings. Average summary scores were calculated for the items representing Interactions, Information, and Ancillaries. Correlation analysis between clusters yielded no significant correlations. A review of the literature yielded a paucity of data on analysis of the interview visit. The interview visit consists of a discrete hierarchy of perceived importance by applicants. The strongest independent factor in determining future program ranking is the quality of interactions between applicants and program constituents on the interview visit. This calls for further investigation and optimization of the interview visit experience.

Improvement of the Earth's gravity field from terrestrial and satellite data

NASA Technical Reports Server (NTRS)

Rapp, Richard H.

1992-01-01

The determination of the Earth's gravitational potential can be done through the analysis of satellite perturbations, the analysis of surface gravity data, or both. The combination of the two data types yields a solution that combines the strength of each method: the longer wavelength strength in the satellite analysis with the better high frequency information from surface gravity data. Since 1972, Ohio State has carried out activities that have provided surface gravity data to a number of organizations who have developed combination potential coefficient models that describe the Earth's gravitational potential.

Automating security monitoring and analysis for Space Station Freedom's electric power system

NASA Technical Reports Server (NTRS)

Dolce, James L.; Sobajic, Dejan J.; Pao, Yoh-Han

1990-01-01

Operating a large, space power system requires classifying the system's status and analyzing its security. Conventional algorithms are used by terrestrial electric utilities to provide such information to their dispatchers, but their application aboard Space Station Freedom will consume too much processing time. A new approach for monitoring and analysis using adaptive pattern techniques is presented. This approach yields an on-line security monitoring and analysis algorithm that is accurate and fast; and thus, it can free the Space Station Freedom's power control computers for other tasks.

Automating security monitoring and analysis for Space Station Freedom's electric power system

NASA Technical Reports Server (NTRS)

Dolce, James L.; Sobajic, Dejan J.; Pao, Yoh-Han

1990-01-01

Operating a large, space power system requires classifying the system's status and analyzing its security. Conventional algorithms are used by terrestrial electric utilities to provide such information to their dispatchers, but their application aboard Space Station Freedom will consume too much processing time. A novel approach for monitoring and analysis using adaptive pattern techniques is presented. This approach yields an on-line security monitoring and analysis algorithm that is accurate and fast; and thus, it can free the Space Station Freedom's power control computers for other tasks.

Experimental investigation of the Jahn-Teller effect in the ground and excited electronic states of the tropyl radical. Part II. Vibrational analysis of the A 2E"3-X 2E"2 electronic transition.

PubMed

Sioutis, Ilias; Stakhursky, Vadim L; Tarczay, György; Miller, Terry A

2008-02-28

Laser-induced fluorescence (LIF) and laser-excited dispersed fluorescence (LEDF) spectra of the cycloheptatrienyl (tropyl) radical C7H7 have been observed under supersonic jet-cooling conditions. Assignment of the LIF excitation spectrum yields detailed information about the A-state vibronic structure. The LEDF emission was collected by pumping different vibronic bands of the A 2E"3<--X 2E"2 electronic spectrum. Analysis of the LEDF spectra yields valuable information about the vibronic levels of the X 2E"2 state. The X- and A-state vibronic structures characterize the Jahn-Teller distortion of the respective potential energy surfaces. A thorough analysis reveals observable Jahn-Teller activity in three of the four e'3 modes for the X 2E"2 state and two of the three e'1 modes for the A 2E"3 state and provides values for their deperturbed vibrational frequencies as well as linear Jahn-Teller coupling constants. The molecular parameters characterizing the Jahn-Teller interaction in the X and A states of C7H7 are compared to theoretical results and to those previously obtained for C5H5 and C6H6+.

Identification of saline soils with multi-year remote sensing of crop yields

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

Lobell, D; Ortiz-Monasterio, I; Gurrola, F C

2006-10-17

Soil salinity is an important constraint to agricultural sustainability, but accurate information on its variation across agricultural regions or its impact on regional crop productivity remains sparse. We evaluated the relationships between remotely sensed wheat yields and salinity in an irrigation district in the Colorado River Delta Region. The goals of this study were to (1) document the relative importance of salinity as a constraint to regional wheat production and (2) develop techniques to accurately identify saline fields. Estimates of wheat yield from six years of Landsat data agreed well with ground-based records on individual fields (R{sup 2} = 0.65).more » Salinity measurements on 122 randomly selected fields revealed that average 0-60 cm salinity levels > 4 dS m{sup -1} reduced wheat yields, but the relative scarcity of such fields resulted in less than 1% regional yield loss attributable to salinity. Moreover, low yield was not a reliable indicator of high salinity, because many other factors contributed to yield variability in individual years. However, temporal analysis of yield images showed a significant fraction of fields exhibited consistently low yields over the six year period. A subsequent survey of 60 additional fields, half of which were consistently low yielding, revealed that this targeted subset had significantly higher salinity at 30-60 cm depth than the control group (p = 0.02). These results suggest that high subsurface salinity is associated with consistently low yields in this region, and that multi-year yield maps derived from remote sensing therefore provide an opportunity to map salinity across agricultural regions.« less

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy

DOE PAGES

Payne, Courtney E.; Wolfrum, Edward J.

2015-03-12

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. Here are the results: We present individual model statistics tomore » demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. In conclusion, it is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.« less

Rapid analysis of composition and reactivity in cellulosic biomass feedstocks with near-infrared spectroscopy

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

Payne, Courtney E.; Wolfrum, Edward J.

Obtaining accurate chemical composition and reactivity (measures of carbohydrate release and yield) information for biomass feedstocks in a timely manner is necessary for the commercialization of biofuels. Our objective was to use near-infrared (NIR) spectroscopy and partial least squares (PLS) multivariate analysis to develop calibration models to predict the feedstock composition and the release and yield of soluble carbohydrates generated by a bench-scale dilute acid pretreatment and enzymatic hydrolysis assay. Major feedstocks included in the calibration models are corn stover, sorghum, switchgrass, perennial cool season grasses, rice straw, and miscanthus. Here are the results: We present individual model statistics tomore » demonstrate model performance and validation samples to more accurately measure predictive quality of the models. The PLS-2 model for composition predicts glucan, xylan, lignin, and ash (wt%) with uncertainties similar to primary measurement methods. A PLS-2 model was developed to predict glucose and xylose release following pretreatment and enzymatic hydrolysis. An additional PLS-2 model was developed to predict glucan and xylan yield. PLS-1 models were developed to predict the sum of glucose/glucan and xylose/xylan for release and yield (grams per gram). The release and yield models have higher uncertainties than the primary methods used to develop the models. In conclusion, it is possible to build effective multispecies feedstock models for composition, as well as carbohydrate release and yield. The model for composition is useful for predicting glucan, xylan, lignin, and ash with good uncertainties. The release and yield models have higher uncertainties; however, these models are useful for rapidly screening sample populations to identify unusual samples.« less

Why Is It so? The [superscript 1]H-NMR CH[subscript 2] Splitting in Substituted Propanes

ERIC Educational Resources Information Center

Lim, Kieran F.; Dereani, Marino

2010-01-01

Nuclear magnetic resonance (NMR) spectroscopy is an important tool in the structural analysis of both organic and inorganic molecules. Proton NMR spectra can yield information about the chemical or bonding environment surrounding various protons, the number of protons in those environments, and the number of neighbouring protons around each…

Normal yield tables for red alder.

Treesearch

Norman P. Worthington; Floyd A. Johnson; George R. Staebler; William J. Lloyd

1960-01-01

Increasing interest in the management of red alder (Alnus rubra) has created a need for reliable yield information. Existing yield tables for red alder have been very useful as interim sources of information, but they are generally inadequate for current and prospective management needs. The advisory committee for the Station's Olympia...

77 FR 75498 - Request for Comments on a New Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-20

... statistical surveys that yield quantitative results that can be generalized to the population of study. DATES... surveys that yield quantitative results that can be generalized to the population of study. This feedback... qualitative information will not be used for quantitative information collections that are designed to yield...

The Continuous Confrontation of Caregiving as Described in Real-Time Online Group Chat.

PubMed

Male, Dana A; Fergus, Karen D; Stephen, Joanne E

2015-01-01

To date, our understanding of the caregiver experience has been informed primarily by guided inquiry in the form of interviews and surveys, yielding information that is limited by the scope of researchers questions. The intent of this study was to explore the experience of caring for a loved one with advanced-stage cancer by means of participant-determined communication, using interactive, text-based transcripts from synchronous online support groups. Grounded theory analysis of the group transcripts yielded the core category continuous confrontation, characterized by major challenges (unrelenting assault, a new us, and the costs of caregiving) and minor triumphs (refuelling and living more intentionally). This unique method of data collection allowed for an especially candid, intersubjective group account of what it is to be a caregiver for an ill loved one without compromising the details that caregivers themselves consider important.

Soft-tissue anatomy of the extant hominoids: a review and phylogenetic analysis

PubMed Central

Gibbs, S; Collard, M; Wood, B

2002-01-01

This paper reports the results of a literature search for information about the soft-tissue anatomy of the extant non-human hominoid genera, Pan, Gorilla, Pongo and Hylobates, together with the results of a phylogenetic analysis of these data plus comparable data for Homo. Information on the four extant non-human hominoid genera was located for 240 out of the 1783 soft-tissue structures listed in the Nomina Anatomica. Numerically these data are biased so that information about some systems (e.g. muscles) and some regions (e.g. the forelimb) are over-represented, whereas other systems and regions (e.g. the veins and the lymphatics of the vascular system, the head region) are either under-represented or not represented at all. Screening to ensure that the data were suitable for use in a phylogenetic analysis reduced the number of eligible soft-tissue structures to 171. These data, together with comparable data for modern humans, were converted into discontinuous character states suitable for phylogenetic analysis and then used to construct a taxon-by-character matrix. This matrix was used in two tests of the hypothesis that soft-tissue characters can be relied upon to reconstruct hominoid phylogenetic relationships. In the first, parsimony analysis was used to identify cladograms requiring the smallest number of character state changes. In the second, the phylogenetic bootstrap was used to determine the confidence intervals of the most parsimonious clades. The parsimony analysis yielded a single most parsimonious cladogram that matched the molecular cladogram. Similarly the bootstrap analysis yielded clades that were compatible with the molecular cladogram; a (Homo, Pan) clade was supported by 95% of the replicates, and a (Gorilla, Pan, Homo) clade by 96%. These are the first hominoid morphological data to provide statistically significant support for the clades favoured by the molecular evidence. PMID:11833653

Exploiting induced variation to dissect quantitative traits in barley.

PubMed

Druka, Arnis; Franckowiak, Jerome; Lundqvist, Udda; Bonar, Nicola; Alexander, Jill; Guzy-Wrobelska, Justyna; Ramsay, Luke; Druka, Ilze; Grant, Iain; Macaulay, Malcolm; Vendramin, Vera; Shahinnia, Fahimeh; Radovic, Slobodanka; Houston, Kelly; Harrap, David; Cardle, Linda; Marshall, David; Morgante, Michele; Stein, Nils; Waugh, Robbie

2010-04-01

The identification of genes underlying complex quantitative traits such as grain yield by means of conventional genetic analysis (positional cloning) requires the development of several large mapping populations. However, it is possible that phenotypically related, but more extreme, allelic variants generated by mutational studies could provide a means for more efficient cloning of QTLs (quantitative trait loci). In barley (Hordeum vulgare), with the development of high-throughput genome analysis tools, efficient genome-wide identification of genetic loci harbouring mutant alleles has recently become possible. Genotypic data from NILs (near-isogenic lines) that carry induced or natural variants of genes that control aspects of plant development can be compared with the location of QTLs to potentially identify candidate genes for development--related traits such as grain yield. As yield itself can be divided into a number of allometric component traits such as tillers per plant, kernels per spike and kernel size, mutant alleles that both affect these traits and are located within the confidence intervals for major yield QTLs may represent extreme variants of the underlying genes. In addition, the development of detailed comparative genomic models based on the alignment of a high-density barley gene map with the rice and sorghum physical maps, has enabled an informed prioritization of 'known function' genes as candidates for both QTLs and induced mutant genes.

Survival or productivity? Global synthesis of root and tuber production during drought

NASA Astrophysics Data System (ADS)

Daryanto, S.; Wang, L.; Jacinthe, P. A.

2016-12-01

According to FAO, there are six major root and tuber crops: potato, cassava, sweet potato, yam, taro, and yautia. Some root and tuber crops (e.g., sweet potato and cassava) are considered to be `drought-resistant', although quantitative evidence that support the premise was still lacking. Greater uncertainties exist on how drought effects co-vary with: 1) soil texture, 2) agro-ecological region, and 3) drought timing. To address these uncertainties, we collected literature data between 1980 and 2015 that reported monoculture root and tuber yield responses to drought under field conditions, and analyzed this large data set using meta-analysis techniques. Our results showed that the amount of water reduction was positively related with yield reduction, but the extent of the impact varied with root or tuber species and the phenological phase during which drought occurred. In contrast to common assumptions regarding drought resistance of certain root and tuber crops, we found that yield reduction was similar between potato and species thought to be `drought-resistant' such as cassava and sweet potato. Here we suggest that drought-resistance in cassava and sweet potato could be more related to survival rather than yield. All roots or tubers crops, however, experienced greater yield reduction when drought occurred during the tuberization period compared to during their vegetative phase. The effect of soil texture as well as region (and related climatic factors) on yield reduction and crop sensitivity were less obvious. Our study provides useful information that could inform agricultural planning, and influence the direction of research for improving the productivity and the resilience of these under-utilized crops in the drought-prone regions of the world.

Water erosion and climate change in a small alpine catchment

NASA Astrophysics Data System (ADS)

Berteni, Francesca; Grossi, Giovanna

2017-04-01

WATER EROSION AND CLIMATE CHANGE IN A SMALL ALPINE CATCHMENT Francesca Berteni, Giovanna Grossi A change in the mean and variability of some variables of the climate system is expected to affect the sediment yield of mountainous areas in several ways: for example through soil temperature and precipitation peak intensity change, permafrost thawing, snow- and ice-melt time shifting. Water erosion, sediment transport and yield and the effects of climate change on these physical phenomena are the focus of this work. The study area is a small mountainous basin, the Guerna creek watershed, located in the Central Southern Alps. The sensitivity of sediment yield estimates to a change of condition of the climate system may be investigated through the application of different models, each characterized by its own features and limits. In this preliminary analysis two different empirical mathematical models are considered: RUSLE (Revised Universal Soil Loss Equation; Renard et al., 1991) and EPM (Erosion Potential Method; Gavrilovic, 1988). These models are implemented in a Geographical Information System (GIS) supporting the management of the territorial database used to estimate relevant geomorphological parameters and to create different thematic maps. From one side the geographical and geomorphological information is required (land use, slope and hydrogeological instability, resistance to erosion, lithological characterization and granulometric composition). On the other side the knowledge of the weather-climate parameters (precipitation and temperature data) is fundamental as well to evaluate the intensity and variability of the erosive processes and estimate the sediment yield at the basin outlet. Therefore different climate change scenarios were considered in order to tentatively assess the impact on the water erosion and sediment yield at the small basin scale. Keywords: water erosion, sediment yield, climate change, empirical mathematical models, EPM, RUSLE, GIS, Guerna

The intellectual core of enterprise information systems: a co-citation analysis

NASA Astrophysics Data System (ADS)

Shiau, Wen-Lung

2016-10-01

Enterprise information systems (EISs) have evolved in the past 20 years, attracting the attention of international practitioners and scholars. Although literature reviews and analyses have been conducted to examine the multiple dimensions of EISs, no co-citation analysis has been conducted to examine the knowledge structures involved in EIS studies; thus, the current study fills this research gap. This study investigated the intellectual structures of EISs. All data source documents (1083 articles and 24,090 citations) were obtained from the Institute for Scientific Information Web of Knowledge database. A co-citation analysis was used to analyse EIS data. By using factor analysis, we identified eight critical factors: (a) factors affecting the implementation and success of information systems (ISs); (b) the successful implementation of enterprise resource planning (ERP); (c) IS evaluation and success, (d) system science studies; (e) factors influencing ERP success; (f) case research and theoretical models; (g) user acceptance of information technology; and (h) IS frameworks. Multidimensional scaling and cluster analysis were used to visually map the resultant EIS knowledge. It is difficult to implement an EIS in an enterprise and each organisation exhibits specific considerations. The current findings indicate that managers must focus on ameliorating inferior project performance levels, enabling a transition from 'vicious' to 'virtuous' projects. Successful EIS implementation yields substantial organisational advantages.

Strategies for soil-based precision agriculture in cotton

NASA Astrophysics Data System (ADS)

Neely, Haly L.; Morgan, Cristine L. S.; Stanislav, Scott; Rouze, Gregory; Shi, Yeyin; Thomasson, J. Alex; Valasek, John; Olsenholler, Jeff

2016-05-01

The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.

Modelling heterogeneity variances in multiple treatment comparison meta-analysis – Are informative priors the better solution?

PubMed Central

2013-01-01

Background Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the ‘common variance’ assumption). This approach ‘borrows strength’ for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. Methods In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. Results In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. Conclusions MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice. PMID:23311298

Estimating the Economic Value of Information for Screening in Disseminating and Targeting Effective School-based Preventive Interventions: An Illustrative Example.

PubMed

Johnston, Stephen S; Salkever, David S; Ialongo, Nicholas S; Slade, Eric P; Stuart, Elizabeth A

2017-11-01

When candidates for school-based preventive interventions are heterogeneous in their risk of poor outcomes, an intervention's expected economic net benefits may be maximized by targeting candidates for whom the intervention is most likely to yield benefits, such as those at high risk of poor outcomes. Although increasing amounts of information about candidates may facilitate more accurate targeting, collecting information can be costly. We present an illustrative example to show how cost-benefit analysis results from effective intervention demonstrations can help us to assess whether improved targeting accuracy justifies the cost of collecting additional information needed to make this improvement.

Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways.

PubMed

Hardy, Simon; Robillard, Pierre N

2008-01-15

Cellular signaling networks are dynamic systems that propagate and process information, and, ultimately, cause phenotypical responses. Understanding the circuitry of the information flow in cells is one of the keys to understanding complex cellular processes. The development of computational quantitative models is a promising avenue for attaining this goal. Not only does the analysis of the simulation data based on the concentration variations of biological compounds yields information about systemic state changes, but it is also very helpful for obtaining information about the dynamics of signal propagation. This article introduces a new method for analyzing the dynamics of signal propagation in signaling pathways using Petri net theory. The method is demonstrated with the Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) regulation network. The results constitute temporal information about signal propagation in the network, a simplified graphical representation of the network and of the signal propagation dynamics and a characterization of some signaling routes as regulation motifs.

Intercomparison of Soil Moisture, Evaporative Stress, and Vegetation Indices for Estimating Corn and Soybean Yields Over the U.S.

NASA Technical Reports Server (NTRS)

Mladenova, Iliana E.; Bolten, John D.; Crow, Wade T.; Anderson, Martha C.; Hain, C. R.; Johnson, David M.; Mueller, Rick

2017-01-01

This paper presents an intercomparative study of 12 operationally produced large-scale datasets describing soil moisture, evapotranspiration (ET), and or vegetation characteristics within agricultural regions of the contiguous United States (CONUS). These datasets have been developed using a variety of techniques, including, hydrologic modeling, satellite-based retrievals, data assimilation, and survey in-field data collection. The objectives are to assess the relative utility of each dataset for monitoring crop yield variability, to quantitatively assess their capacity for predicting end-of-season corn and soybean yields, and to examine the evolution of the yield-index correlations during the growing season. This analysis is unique both with regards to the number and variety of examined yield predictor datasets and the detailed assessment of the water availability timing on the end-of-season crop production during the growing season. Correlation results indicate that over CONUS, at state-level soil moisture and ET indices can provide better information for forecasting corn and soybean yields than vegetation-based indices such as normalized difference vegetation index. The strength of correlation with corn and soybean yields strongly depends on the interannual variability in yield measured at a given location. In this case study, some of the remotely derived datasets examined provide skill comparable to that of in situ field survey-based data further demonstrating the utility of these remote sensing-based approaches for estimating crop yield.

Crop monitoring & yield forecasting system based on Synthetic Aperture Radar (SAR) and process-based crop growth model: Development and validation in South and South East Asian Countries

NASA Astrophysics Data System (ADS)

Setiyono, T. D.

2014-12-01

Accurate and timely information on rice crop growth and yield helps governments and other stakeholders adapting their economic policies and enables relief organizations to better anticipate and coordinate relief efforts in the wake of a natural catastrophe. Such delivery of rice growth and yield information is made possible by regular earth observation using space-born Synthetic Aperture Radar (SAR) technology combined with crop modeling approach to estimate yield. Radar-based remote sensing is capable of observing rice vegetation growth irrespective of cloud coverage, an important feature given that in incidences of flooding the sky is often cloud-covered. The system allows rapid damage assessment over the area of interest. Rice yield monitoring is based on a crop growth simulation and SAR-derived key information, particularly start of season and leaf growth rate. Results from pilot study sites in South and South East Asian countries suggest that incorporation of SAR data into crop model improves yield estimation for actual yields. Remote-sensing data assimilation into crop model effectively capture responses of rice crops to environmental conditions over large spatial coverage, which otherwise is practically impossible to achieve. Such improvement of actual yield estimates offers practical application such as in a crop insurance program. Process-based crop simulation model is used in the system to ensure climate information is adequately captured and to enable mid-season yield forecast.

Decision-making by experienced rugby referees: use of perceptual information and episodic memory.

PubMed

MacMahon, Clare; Ste-Marie, Diane M

2002-10-01

The expertise paradigm was used in two studies to examine decision-making by rugby referees. Videoclips were used to assess infraction detection and knowledge base, or sources of information used. In Study 1, referees of high and low experience were compared, and in Study 2 referees and players were compared. Analysis by signal detection used a framework to classify types of information. Study 1 yielded no differences in detection of infractions as a function of experience, however, referees of high experience used significantly more sources of information than the group with low experience across all categories of information. In Study 2, there were no significant differences between referees and players, with the exception that referees displayed greater use of episodic memory information in decision-making.

Mask industry assessment trend analysis: 2010

NASA Astrophysics Data System (ADS)

Hughes, Greg; Yun, Henry

2010-05-01

Microelectronics industry leaders consistently cite the cost and cycle time of mask technology and mask supply as top critical issues. A survey was designed with input from semiconductor company mask technologists and merchant mask suppliers and support from SEMATECH to gather information about the mask industry as an objective assessment of its overall condition. This year's assessment was the eighth in the current series of annual reports. Its data were presented in detail at BACUS, and the detailed trend analysis is presented at EMLC. With continued industry support, the report can be used as a baseline to gain perspective on the technical and business status of the mask and microelectronics industries. The report will continue to serve as a valuable reference to identify the strengths and opportunities of the mask industry. Its results will be used to guide future investments on critical path issues. This year's survey is basically the same as the surveys in 2005 through 2009. Questions are grouped into six categories: General Business Profile Information, Data Processing, Yields and Yield Loss Mechanisms, Delivery Times, Returns, and Services. Within each category is a multitude of questions that creates a detailed profile of both the business and technical status of the critical mask industry.

The 2002 to 2010 mask survey trend analysis

NASA Astrophysics Data System (ADS)

Hughes, Greg; Chan, David

2011-03-01

Microelectronics industry leaders consistently cite the cost and cycle time of mask technology and mask supply as top critical issues. A survey was designed with input from semiconductor company mask technologists and merchant mask suppliers and support from SEMATECH to gather information about the mask industry as an objective assessment of its overall condition. This year's assessment was the ninth in the current series of annual reports. Its data were presented in detail at BACUS, and the detailed trend analysis is presented at EMLC. With continued industry support, the report can be used as a baseline to gain perspective on the technical and business status of the mask and microelectronics industries. The report will continue to serve as a valuable reference to identify the strengths and opportunities of the mask industry. Results will be used to guide future investments in critical path issues. This year's survey is basically the same as the 2005 through 2010 surveys. Questions are grouped into six categories: General Business Profile Information, Data Processing, Yields and Yield Loss Mechanisms, Delivery Times, Returns, and Services. Within each category are multiple questions that ultimately create a detailed profile of both the business and technical status of the critical mask industry.

Study of the Information Dissemination Service--Health Sciences Library, State University of New York at Buffalo.

PubMed Central

Brown, H J; Miller, J K; Pinchoff, D M

1975-01-01

The Information Dissemination Service at the Health Sciences Library, State University of New York at Buffalo, was established June 1970 through a three-year grant from the Lakes Area Regional Medical Program, Inc. Analysis of two samples of user request forms yielded results which significantly substantiate findings in prior biomedical literature utilization studies. The findings demonstrate comparable utilization patterns by user group, age of material, journal titles, language, time to process request, source of reference, and size of institution. PMID:1148441

Simulation of corn yields and parameters uncertainties analysis in Hebei and Sichuang, China

NASA Astrophysics Data System (ADS)

Fu, A.; Xue, Y.; Hartman, M. D.; Chandran, A.; Qiu, B.; Liu, Y.

2016-12-01

Corn is one of most important agricultural production in China. Research on the impacts of climate change and human activities on corn yields is important in understanding and mitigating the negative effects of environmental factors on corn yields and maintaining the stable corn production. Using climatic data, including daily temperature, precipitation, and solar radiation from 1948 to 2010, soil properties, observed corn yields, and farmland management information, corn yields in Sichuang and Hebei Provinces of China in the past 63 years were simulated using the Daycent model, and the results was evaluated using Root mean square errors, bias, simulation efficiency, and standard deviation. The primary climatic factors influencing corn yields were examined, the uncertainties of climatic factors was analyzed, and the uncertainties of human activity parameters were also studied by changing fertilization levels and cultivated ways. The results showed that: (1) Daycent model is capable to simulate corn yields in Sichuang and Hebei provinces of China. Observed and simulated corn yields have the similar increasing trend with time. (2) The minimum daily temperature is the primary factor influencing corn yields in Sichuang. In Hebei Province, daily temperature, precipitation and wind speed significantly affect corn yields.(3) When the global warming trend of original data was removed, simulated corn yields were lower than before, decreased by about 687 kg/hm2 from 1992 to 2010; When the fertilization levels, cultivated ways were increased and decreased by 50% and 75%, respectively in the Schedule file in Daycent model, the simulated corn yields increased by 1206 kg/hm2 and 776 kg/hm2, respectively, with the enhancement of fertilization level and the improvement of cultivated way. This study provides a scientific base for selecting a suitable fertilization level and cultivated way in corn fields in China.

Isotopic Ratio, Isotonic Ratio, Isobaric Ratio and Shannon Information Uncertainty

NASA Astrophysics Data System (ADS)

Ma, Chun-Wang; Wei, Hui-Ling

2014-11-01

The isoscaling and the isobaric yield ratio difference (IBD) probes, both of which are constructed by yield ratio of fragment, provide cancelation of parameters. The information entropy theory is introduced to explain the physical meaning of the isoscaling and IBD probes. The similarity between the isoscaling and IBD results is found, i.e., the information uncertainty determined by the IBD method equals to β - α determined by the isoscaling (α (β) is the parameter fitted from the isotopic (isotonic) yield ratio).

Enhancement of plant metabolite fingerprinting by machine learning.

PubMed

Scott, Ian M; Vermeer, Cornelia P; Liakata, Maria; Corol, Delia I; Ward, Jane L; Lin, Wanchang; Johnson, Helen E; Whitehead, Lynne; Kular, Baldeep; Baker, John M; Walsh, Sean; Dave, Anuja; Larson, Tony R; Graham, Ian A; Wang, Trevor L; King, Ross D; Draper, John; Beale, Michael H

2010-08-01

Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by (1)H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, (1)H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted.

76 FR 43353 - Agency Information Collection Activities: Proposed Collection; Comment Request; Generic Clearance...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-20

... and opinions, but are not statistical surveys that yield quantitative results that can be generalized... generic clearance for qualitative information will not be used for quantitative information collections... for submission for other generic mechanisms that are designed to yield quantitative results. The...

Topographic ERP analyses: a step-by-step tutorial review.

PubMed

Murray, Micah M; Brunet, Denis; Michel, Christoph M

2008-06-01

In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within high-density ERP datasets.

A fast and efficient method for device level layout analysis

NASA Astrophysics Data System (ADS)

Dong, YaoQi; Zou, Elaine; Pang, Jenny; Huang, Lucas; Yang, Legender; Zhang, Chunlei; Du, Chunshan; Hu, Xinyi; Wan, Qijian

2017-03-01

There is an increasing demand for device level layout analysis, especially as technology advances. The analysis is to study standard cells by extracting and classifying critical dimension parameters. There are couples of parameters to extract, like channel width, length, gate to active distance, and active to adjacent active distance, etc. for 14nm technology, there are some other parameters that are cared about. On the one hand, these parameters are very important for studying standard cell structures and spice model development with the goal of improving standard cell manufacturing yield and optimizing circuit performance; on the other hand, a full chip device statistics analysis can provide useful information to diagnose the yield issue. Device analysis is essential for standard cell customization and enhancements and manufacturability failure diagnosis. Traditional parasitic parameters extraction tool like Calibre xRC is powerful but it is not sufficient for this device level layout analysis application as engineers would like to review, classify and filter out the data more easily. This paper presents a fast and efficient method based on Calibre equation-based DRC (eqDRC). Equation-based DRC extends the traditional DRC technology to provide a flexible programmable modeling engine which allows the end user to define grouped multi-dimensional feature measurements using flexible mathematical expressions. This paper demonstrates how such an engine and its programming language can be used to implement critical device parameter extraction. The device parameters are extracted and stored in a DFM database which can be processed by Calibre YieldServer. YieldServer is data processing software that lets engineers query, manipulate, modify, and create data in a DFM database. These parameters, known as properties in eqDRC language, can be annotated back to the layout for easily review. Calibre DesignRev can create a HTML formatted report of the results displayed in Calibre RVE which makes it easy to share results among groups. This method has been proven and used in SMIC PDE team and SPICE team.

Performance of Blind Source Separation Algorithms for FMRI Analysis using a Group ICA Method

PubMed Central

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D.

2007-01-01

Independent component analysis (ICA) is a popular blind source separation (BSS) technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist, however the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely information maximization, maximization of non-gaussianity, joint diagonalization of cross-cumulant matrices, and second-order correlation based methods when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study the variability among different ICA algorithms and propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA, and JADE all yield reliable results; each having their strengths in specific areas. EVD, an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for the iterative ICA algorithms, it is important to investigate the variability of the estimates from different runs. We test the consistency of the iterative algorithms, Infomax and FastICA, by running the algorithm a number of times with different initializations and note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis. PMID:17540281

Performance of blind source separation algorithms for fMRI analysis using a group ICA method.

PubMed

Correa, Nicolle; Adali, Tülay; Calhoun, Vince D

2007-06-01

Independent component analysis (ICA) is a popular blind source separation technique that has proven to be promising for the analysis of functional magnetic resonance imaging (fMRI) data. A number of ICA approaches have been used for fMRI data analysis, and even more ICA algorithms exist; however, the impact of using different algorithms on the results is largely unexplored. In this paper, we study the performance of four major classes of algorithms for spatial ICA, namely, information maximization, maximization of non-Gaussianity, joint diagonalization of cross-cumulant matrices and second-order correlation-based methods, when they are applied to fMRI data from subjects performing a visuo-motor task. We use a group ICA method to study variability among different ICA algorithms, and we propose several analysis techniques to evaluate their performance. We compare how different ICA algorithms estimate activations in expected neuronal areas. The results demonstrate that the ICA algorithms using higher-order statistical information prove to be quite consistent for fMRI data analysis. Infomax, FastICA and joint approximate diagonalization of eigenmatrices (JADE) all yield reliable results, with each having its strengths in specific areas. Eigenvalue decomposition (EVD), an algorithm using second-order statistics, does not perform reliably for fMRI data. Additionally, for iterative ICA algorithms, it is important to investigate the variability of estimates from different runs. We test the consistency of the iterative algorithms Infomax and FastICA by running the algorithm a number of times with different initializations, and we note that they yield consistent results over these multiple runs. Our results greatly improve our confidence in the consistency of ICA for fMRI data analysis.

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

2016-01-01

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

Independent Component Analysis of Textures

NASA Technical Reports Server (NTRS)

Manduchi, Roberto; Portilla, Javier

2000-01-01

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.

Information Retrieval and Graph Analysis Approaches for Book Recommendation.

PubMed

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

Information Retrieval and Graph Analysis Approaches for Book Recommendation

PubMed Central

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments. PMID:26504899

Inferences about Membrane Properties from Electrical Noise Measurements

PubMed Central

Stevens, Charles F.

1972-01-01

Four sources of electrical noise in biological membranes, each with a different physical basis, are discussed; the analysis of each type of noise potentially yields a different sort of information about membrane properties. (a) From the thermal noise spectrum, the passive membrane impedance may be obtained, so that thermal noise measurements are essentially equivalent to the type of since wave analysis carried out by Cole and Curtis. (b) If adequately high frequency measurements could be made, the shot noise spectrum should give information about the average motion of a single ion within the membrane. (c) The number of charge carriers and single ion mobilities within the membrane can possibly be inferred from measurements of noise with a 1/f spectrum. Available data indicate, for example, that increases in axon membrane conductance are not achieved by modulations in the mobility of ions within the membrane. (d) Fluctuations arising from the mechanisms normally responsible for membrane conductance changes can produce a type of electrical noise. Analysis of such conductance fluctuations provides a way to assess the validity of various microscopic models for the behavior of individual channels. Two different probabilistic interpretations of the Hodgkin-Huxley equations are investigated here and shown to yield different predictions about the spectrum of conductance fluctuations; thus, appropriate noise measurements may serve to eliminate certain classes of microscopic models for membrane conductance changes. Further, it is shown how the analysis of conductance fluctuations can, in some circumstances, provide an estimate of the conductance of a single channel. PMID:5044577

Analysis And Assistant Planning System Ofregional Agricultural Economic Inform

NASA Astrophysics Data System (ADS)

Han, Jie; Zhang, Junfeng

For the common problems existed in regional development and planning, we try to design a decision support system for assisting regional agricultural development and alignment as a decision-making tool for local government and decision maker. The analysis methods of forecast, comparative advantage, liner programming and statistical analysis are adopted. According to comparative advantage theory, the regional advantage can be determined by calculating and comparing yield advantage index (YAI), Scale advantage index (SAI), Complicated advantage index (CAI). Combining with GIS, agricultural data are presented as a form of graph such as area, bar and pie to uncover the principle and trend for decision-making which can't be found in data table. This system provides assistant decisions for agricultural structure adjustment, agro-forestry development and planning, and can be integrated to information technologies such as RS, AI and so on.

Yield of bedrock wells in the Nashoba terrane, central and eastern Massachusetts

USGS Publications Warehouse

DeSimone, Leslie A.; Barbaro, Jeffrey R.

2012-01-01

The yield of bedrock wells in the fractured-bedrock aquifers of the Nashoba terrane and surrounding area, central and eastern Massachusetts, was investigated with analyses of existing data. Reported well yield was compiled for 7,287 wells from Massachusetts Department of Environmental Protection and U.S. Geological Survey databases. Yield of these wells ranged from 0.04 to 625 gallons per minute. In a comparison with data from 103 supply wells, yield and specific capacity from aquifer tests were well correlated, indicating that reported well yield was a reasonable measure of aquifer characteristics in the study area. Statistically significant relations were determined between well yield and a number of cultural and hydrogeologic factors. Cultural variables included intended water use, well depth, year of construction, and method of yield measurement. Bedrock geology, topography, surficial geology, and proximity to surface waters were statistically significant hydrogeologic factors. Yield of wells was higher in areas of granites, mafic intrusive rocks, and amphibolites than in areas of schists and gneisses or pelitic rocks; higher in valleys and low-slope areas than on hills, ridges, or high slopes; higher in areas overlain by stratified glacial deposits than in areas overlain by till; and higher in close proximity to streams, ponds, and wetlands than at greater distances from these surface-water features. Proximity to mapped faults and to lineaments from aerial photographs also were related to well yield by some measures in three quadrangles in the study area. Although the statistical significance of these relations was high, their predictive power was low, and these relations explained little of the variability in the well-yield data. Similar results were determined from a multivariate regression analysis. Multivariate regression models for the Nashoba terrane and for a three-quadrangle subarea included, as significant variables, many of the cultural and hydrogeologic factors that were individually related to well yield, in ways that are consistent with conceptual understanding of their effects, but the models explained only 21 percent (regional model for the entire terrane) and 30 percent (quadrangle model) of the overall variance in yield. Moreover, most of the explained variance was due to well characteristics rather than hydrogeologic factors. Hydrogeologic factors such as topography and geology are likely important. However, the overall high variability in the well-yield data, which results from the high variability in aquifer hydraulic properties as well as from limitations of the dataset, would make it difficult to use hydrogeologic factors to predict well yield in the study area. Geostatistical analysis (variograms), on the other hand, indicated that, although highly variable, the well-yield data are spatially correlated. The spatial continuity appears greater in the northeast-southwest direction and less in the southeast-northwest direction, directions that are parallel and perpendicular, respectively, to the regional geologic structural trends. Geostatistical analysis (kriging), used to estimate yield values throughout the study area, identified regional-scale areas of higher and lower yield that may be related to regional structural features—in particular, to a northeast-southwest trending regional fault zone within the Nashoba terrane. It also would be difficult to use kriging to predict yield at specific locations, however, because of the spatial variability in yield, particularly at small scales. The regional-scale analyses in this study, both with hydrogeologic variables and geostatistics, provide a context for understanding the variability in well yield, rather a basis for precise predictions, and site-specific information would be needed to understand local conditions.

Inference of cosmological parameters from gravitational waves: Applications to second generation interferometers

NASA Astrophysics Data System (ADS)

Del Pozzo, Walter

2012-08-01

The advanced worldwide network of gravitational waves (GW) observatories is scheduled to begin operations within the current decade. Thanks to their improved sensitivity, they promise to yield a number of detections and thus to open new observational windows for astronomy and astrophysics. Among the scientific goals that should be achieved, there is the independent measurement of the value of the cosmological parameters, hence an independent test of the current cosmological paradigm. Because of the importance of such a task, a number of studies have evaluated the capabilities of GW telescopes in this respect. However, since GW do not yield information about the source redshift, different groups have made different assumptions regarding the means through which the GW redshift can be obtained. These different assumptions imply also different methodologies to solve this inference problem. This work presents a formalism based on Bayesian inference developed to facilitate the inclusion of all assumptions and prior information about a GW source within a single data analysis framework. This approach guarantees the minimization of information loss and the possibility of including naturally event-specific knowledge (such as the sky position for a gamma ray burst-GW coincident observation) in the analysis. The workings of the method are applied to a specific example, loosely designed along the lines of the method proposed by Schutz in 1986, in which one uses information from wide-field galaxy surveys as prior information for the location of a GW source. I show that combining the results from few tens of observations from a network of advanced interferometers will constrain the Hubble constant H0 to an accuracy of ˜4%-5% at 95% confidence.

Does administering a comprehensive examination affect pass rates on the Registered Health Information Administrator certification examination?

PubMed

McNeill, Marjorie H

2009-01-01

The purpose of this research study was to determine whether the administration of a comprehensive examination before graduation increases the percentage of students passing the Registered Health Information Administrator certification examination. A t-test for independent means yielded a statistically significant difference between the Registered Health Information Administrator certification examination pass rates of health information administration programs that administer a comprehensive examination and programs that do not administer a comprehensive examination. Programs with a high certification examination pass rate do not require a comprehensive examination when compared with those programs with a lower pass rate. It is concluded that health information administration faculty at the local level should perform program self-analysis to improve student progress toward achievement of learning outcomes and entry-level competencies.

A framework for evaluating forest restoration alternatives and their outcomes, over time, to inform monitoring: Bioregional inventory originated simulation under management

Treesearch

Jeremy S. Fried; Theresa B. Jain; Sara Loreno; Robert F. Keefe; Conor K. Bell

2017-01-01

The BioSum modeling framework summarizes current and prospective future forest conditions under alternative management regimes along with their costs, revenues and product yields. BioSum translates Forest Inventory and Analysis (FIA) data for input to the Forest Vegetation Simulator (FVS), summarizes FVS outputs for input to the treatment operations cost model (OpCost...

An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Liu, Yanlou; Tian, Wei; Xin, Tao

2016-01-01

The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

Comparison of four glycosyl residue composition methods for effectiveness in detecting sugars from cell walls of dicot and grass tissues.

PubMed

Biswal, Ajaya K; Tan, Li; Atmodjo, Melani A; DeMartini, Jaclyn; Gelineo-Albersheim, Ivana; Hunt, Kimberly; Black, Ian M; Mohanty, Sushree S; Ryno, David; Wyman, Charles E; Mohnen, Debra

2017-01-01

The effective use of plant biomass for biofuel and bioproduct production requires a comprehensive glycosyl residue composition analysis to understand the different cell wall polysaccharides present in the different biomass sources. Here we compared four methods side-by-side for their ability to measure the neutral and acidic sugar composition of cell walls from herbaceous, grass, and woody model plants and bioenergy feedstocks. Arabidopsis, Populus , rice, and switchgrass leaf cell walls, as well as cell walls from Populus wood, rice stems, and switchgrass tillers, were analyzed by (1) gas chromatography-mass spectrometry (GC-MS) of alditol acetates combined with a total uronic acid assay; (2) carbodiimide reduction of uronic acids followed by GC-MS of alditol acetates; (3) GC-MS of trimethylsilyl (TMS) derivatives; and (4) high-pressure, anion-exchange chromatography (HPAEC). All four methods gave comparable abundance ranking of the seven neutral sugars, and three of the methods were able to quantify unique acidic sugars. The TMS, HPAEC, and carbodiimide methods provided comparable quantitative results for the specific neutral and acidic sugar content of the biomass, with the TMS method providing slightly greater yield of specific acidic sugars and high total sugar yields. The alditol acetate method, while providing comparable information on the major neutral sugars, did not provide the requisite quantitative information on the specific acidic sugars in plant biomass. Thus, the alditol acetate method is the least informative of the four methods. This work provides a side-by-side comparison of the efficacy of four different established glycosyl residue composition analysis methods in the analysis of the glycosyl residue composition of cell walls from both dicot (Arabidopsis and Populus ) and grass (rice and switchgrass) species. Both primary wall-enriched leaf tissues and secondary wall-enriched wood/stem tissues were analyzed for mol% and mass yield of the non-cellulosic sugars. The TMS, HPAEC, and carbodiimide methods were shown to provide comparable quantitative data on the nine neutral and acidic sugars present in all plant cell walls.

Decision analysis for designing marine protected areas for multiple species with uncertain fishery status.

PubMed

White, J Wilson; Botsford, Louis W; Moffitt, Elizabeth A; Fischer, Douglas T

2010-09-01

Marine protected areas (MPAs) are growing in popularity as a conservation tool, and there are increasing calls for additional MPAs. Meta-analyses indicate that most MPAs successfully meet the minimal goal of increasing biomass inside the MPA, while some do not, leaving open the important question of what makes MPAs successful. An often-overlooked aspect of this problem is that the success of fishery management outside MPA boundaries (i.e., whether a population is overfished) affects how well MPAs meet both conservation goals (e.g., increased biomass) and economic goals (e.g., minimal negative effects on fishery yield). Using a simple example of a system with homogeneous habitat and periodically spaced MPAs, we show that, as area in MPAs increases, (1) conservation value (biomass) may initially be zero, implying no benefit, then at some point increases monotonically; and (2) fishery yield may be zero, then increases monotonically to a maximum beyond which further increase in MPA area causes yield to decline. Importantly, the points at which these changes in slope occur vary among species and depend on management outside MPAs. Decision makers considering the effects of a potential system of MPAs on multiple species are confronted by a number of such cost-benefit curves, and it is usually impossible to maximize benefits and minimize costs for all species. Moreover, the precise shape of each curve is unknown due to uncertainty regarding the fishery status of each species. Here we describe a decision-analytic approach that incorporates existing information on fishery stock status to present decision makers with the range of likely outcomes of MPA implementation. To summarize results from many species whose overfishing status is uncertain, our decision-analysis approach involves weighted averages over both overfishing uncertainty and species. In an example from an MPA decision process in California, USA, an optimistic projection of future fishery management success led to recommendation of fewer and smaller MPAs than that derived from a more pessimistic projection of future management success. This example illustrates how information on fishery status can be used to project potential outcomes of MPA implementation within a decision analysis framework and highlights the need for better population information.

Unmanned Aerial Vehicle (UAV) data analysis for fertilization dose assessment

NASA Astrophysics Data System (ADS)

Kavvadias, Antonis; Psomiadis, Emmanouil; Chanioti, Maroulio; Tsitouras, Alexandros; Toulios, Leonidas; Dercas, Nicholas

2017-10-01

The growth rate monitoring of crops throughout their biological cycle is very important as it contributes to the achievement of a uniformly optimum production, a proper harvest planning, and reliable yield estimation. Fertilizer application often dramatically increases crop yields, but it is necessary to find out which is the ideal amount that has to be applied in the field. Remote sensing collects spatially dense information that may contribute to, or provide feedback about, fertilization management decisions. There is a potential goal to accurately predict the amount of fertilizer needed so as to attain an ideal crop yield without excessive use of fertilizers cause financial loss and negative environmental impacts. The comparison of the reflectance values at different wavelengths, utilizing suitable vegetation indices, is commonly used to determine plant vigor and growth. Unmanned Aerial Vehicles (UAVs) have several advantages; because they can be deployed quickly and repeatedly, they are flexible regarding flying height and timing of missions, and they can obtain very high-resolution imagery. In an experimental crop field in Eleftherio Larissa, Greece, different dose of pre-plant and in-season fertilization was applied in 27 plots. A total of 102 aerial photos in two flights were taken using an Unmanned Aerial Vehicle based on the scheduled fertilization. Α correlation of experimental fertilization with the change of vegetation indices values and with the increase of the vegetation cover rate during those days was made. The results of the analysis provide useful information regarding the vigor and crop growth rate performance of various doses of fertilization.

An Analysis of the Second Project High Water Data

NASA Technical Reports Server (NTRS)

Woodbridge, David D.; Lasater, James A.; Fultz, Bennett M.; Clark, Richard E.; Wylie, Nancy

1963-01-01

Early in 1962 NASA established "Project High Water" to investigate the sudden release of large quantities of water into the upper atmosphere. The primary objectives of these experiments were to obtain information on the behavior of liquids released in the ionosphere and the localized effects on the ionosphere produced by the injection of large quantities of water. The data obtained in the two (2) Project High Water experiments have yielded an extensive amount of information concerning the complex phenomena associated with the sudden release of liquids in the Ionosphere. The detailed analysis of data obtained during the second Project High Water experiment (i.e., the third Saturn I vehicle test or SA-3) presented in this report demonstrates that the objectives of the Project High Water were achieved. In addition, the Project High Water has provided essential information relevant to a number of problems vital to manned explorations of space.

Tuberculosis and latent tuberculous infection screening of migrants in Europe: comparative analysis of policies, surveillance systems and results.

PubMed

Kunst, H; Burman, M; Arnesen, T M; Fiebig, L; Hergens, M-P; Kalkouni, O; Klinkenberg, E; Orcau, À; Soini, H; Sotgiu, G; Zenner, D; de Vries, G

2017-08-01

Migration patterns into and within Europe have changed over the last decade. In 2015, European Union (EU) countries received over 1.2 million asylum requests, more than double the number registered in the previous year. This review compares the published literature on policies for tuberculosis (TB) and latent tuberculous infection (LTBI) screening in EU and European Free Trade Association (EFTA) countries with the existing TB/LTBI screening programmes for migrants in 11 EU/EFTA countries based on a survey of policy and surveillance systems. In addition, we provide a systematic review of the literature on the yield of screening migrants for active TB and LTBI in Europe. Published studies provide limited information about screening coverage and the yield of screening evaluations in EU/EFTA countries. Furthermore, countries use different screening strategies and settings, and different definitions for coverage and yield of screening for active TB and LTBI. We recommend harmonising case definitions, reporting standards and policies for TB/LTBI screening. To achieve TB elimination targets, a European platform for multi-country data collection and analysis, sharing of countries' policies and practices, and harmonisation of migrant screening strategies is needed.

Architectural Survey of Pershing Elementary School, Fort Leonard Wood, Missouri

DTIC Science & Technology

2013-08-01

information important in prehistory or history. 16 NPS 1991. 17 Excerpted from...school has yielded, or was likely to yield, any information important in prehistory or history. Final Determination for Building 6501 It is the

Chemical reactions involved in the initiation of hot corrosion of IN-738

NASA Technical Reports Server (NTRS)

Fryburg, G. C.; Kohl, F. J.; Stearns, C. A.

1984-01-01

Sodium-sulfate-induced hot corrosion of preoxidized IN-738 was studied at 975 C with special emphasis placed on the processes occurring during the long induction period. Thermogravimetric tests were run for predetermined periods of time, and then one set of specimens was washed with water. Chemical analysis of the wash solutions yielded information about water soluble metal salts and residual sulfate. A second set of samples was cross sectioned dry and polished in a nonaqueous medium. Element distributions within the oxide scale were obtained from electron microprobe X-ray micrographs. Evolution of SO was monitored throughout the thermogravimetric tests. Kinetic rate studies were performed for several pertinent processes; appropriate rate constants were obtained from the following chemical reactions; Cr203 + 2 Na2S04(1) + 3/2 02 yields 2 Na2Cr04(1) + 2 S03(g)n TiO2 + Na2S04(1) yields Na20(T102)n + 503(g)n T102 + Na2Cro4(1) yields Na2(T102)n + Cr03(g).

Mining Social Media and Web Searches For Disease Detection

PubMed Central

Yang, Y. Tony; Horneffer, Michael; DiLisio, Nicole

2013-01-01

Web-based social media is increasingly being used across different settings in the health care industry. The increased frequency in the use of the Internet via computer or mobile devices provides an opportunity for social media to be the medium through which people can be provided with valuable health information quickly and directly. While traditional methods of detection relied predominately on hierarchical or bureaucratic lines of communication, these often failed to yield timely and accurate epidemiological intelligence. New web-based platforms promise increased opportunities for a more timely and accurate spreading of information and analysis. This article aims to provide an overview and discussion of the availability of timely and accurate information. It is especially useful for the rapid identification of an outbreak of an infectious disease that is necessary to promptly and effectively develop public health responses. These web-based platforms include search queries, data mining of web and social media, process and analysis of blogs containing epidemic key words, text mining, and geographical information system data analyses. These new sources of analysis and information are intended to complement traditional sources of epidemic intelligence. Despite the attractiveness of these new approaches, further study is needed to determine the accuracy of blogger statements, as increases in public participation may not necessarily mean the information provided is more accurate. PMID:25170475

Mining social media and web searches for disease detection.

PubMed

Yang, Y Tony; Horneffer, Michael; DiLisio, Nicole

2013-04-28

Web-based social media is increasingly being used across different settings in the health care industry. The increased frequency in the use of the Internet via computer or mobile devices provides an opportunity for social media to be the medium through which people can be provided with valuable health information quickly and directly. While traditional methods of detection relied predominately on hierarchical or bureaucratic lines of communication, these often failed to yield timely and accurate epidemiological intelligence. New web-based platforms promise increased opportunities for a more timely and accurate spreading of information and analysis. This article aims to provide an overview and discussion of the availability of timely and accurate information. It is especially useful for the rapid identification of an outbreak of an infectious disease that is necessary to promptly and effectively develop public health responses. These web-based platforms include search queries, data mining of web and social media, process and analysis of blogs containing epidemic key words, text mining, and geographical information system data analyses. These new sources of analysis and information are intended to complement traditional sources of epidemic intelligence. Despite the attractiveness of these new approaches, further study is needed to determine the accuracy of blogger statements, as increases in public participation may not necessarily mean the information provided is more accurate.

A meta-analysis of the effects of feeding yeast culture produced by anaerobic fermentation of Saccharomyces cerevisiae on milk production of lactating dairy cows.

PubMed

Poppy, G D; Rabiee, A R; Lean, I J; Sanchez, W K; Dorton, K L; Morley, P S

2012-10-01

The purpose of this study was to use meta-analytic methods to estimate the effect of a commercially available yeast culture product on milk production and other production measures in lactating dairy cows using a meta-analysis of randomized controlled trials. Sixty-one research publications (published journal articles, published abstracts, and technical reports) were identified through a review of literature provided by the manufacturer and a search of published literature using 6 search engines. Thirty-six separate studies with 69 comparisons met the criteria for inclusion in the meta-analysis. The fixed-effect meta-analysis showed substantial heterogeneity for milk yield, energy-corrected milk, 3.5% fat-corrected milk, milk fat yield, and milk protein yield. Sub-group analysis of the data showed much less heterogeneity in peer-reviewed studies versus non-peer-reviewed abstracts and technical reports, and tended to show higher, but not significantly different, treatment effects. A random-effects meta-analysis showed estimated raw mean differences between treated and untreated cattle reported in peer-reviewed publications of 1.18 kg/d [95% confidence interval (CI): 0.55 to 1.81], 1.61 kg/d (95% CI: 0.92 to 2.29), and 1.65 kg/d (95% CI: 0.97 to 2.34) for milk yield, 3.5% fat-corrected milk, and energy-corrected milk, respectively. Milk fat yield and milk protein yield for peer-reviewed studies showed an increase in the raw mean difference of 0.06 kg/d (95% CI: 0.01 to 0.10) and 0.03 kg/d (95% CI: 0.00 to 0.05), respectively. Estimated raw mean dry matter intake of the peer-reviewed studies during early lactation (<70 d in milk) and not-early lactation were 0.62 kg/d (95% CI: 0.21 to 1.02) and a decrease of 0.78 kg/d (95% CI: -1.36 to -0.21), respectively. These findings provide strong evidence that this commercially available yeast culture product provides significant improvement in several important milk production outcomes as evaluated in production settings typical for commercial dairies in North America. Utilizing meta-analytic methods to study the complete breadth of information relating to a specific treatment by studying multiple overcomes of all eligible studies can reduce the uncertainty often seen in small individual studies designed without sufficient power to detect differences in treatments. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Molecular Diagnostic Yield of Chromosomal Microarray Analysis and Whole-Exome Sequencing in Children With Autism Spectrum Disorder.

PubMed

Tammimies, Kristiina; Marshall, Christian R; Walker, Susan; Kaur, Gaganjot; Thiruvahindrapuram, Bhooma; Lionel, Anath C; Yuen, Ryan K C; Uddin, Mohammed; Roberts, Wendy; Weksberg, Rosanna; Woodbury-Smith, Marc; Zwaigenbaum, Lonnie; Anagnostou, Evdokia; Wang, Zhuozhi; Wei, John; Howe, Jennifer L; Gazzellone, Matthew J; Lau, Lynette; Sung, Wilson W L; Whitten, Kathy; Vardy, Cathy; Crosbie, Victoria; Tsang, Brian; D'Abate, Lia; Tong, Winnie W L; Luscombe, Sandra; Doyle, Tyna; Carter, Melissa T; Szatmari, Peter; Stuckless, Susan; Merico, Daniele; Stavropoulos, Dimitri J; Scherer, Stephen W; Fernandez, Bridget A

2015-09-01

The use of genome-wide tests to provide molecular diagnosis for individuals with autism spectrum disorder (ASD) requires more study. To perform chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) in a heterogeneous group of children with ASD to determine the molecular diagnostic yield of these tests in a sample typical of a developmental pediatric clinic. The sample consisted of 258 consecutively ascertained unrelated children with ASD who underwent detailed assessments to define morphology scores based on the presence of major congenital abnormalities and minor physical anomalies. The children were recruited between 2008 and 2013 in Newfoundland and Labrador, Canada. The probands were stratified into 3 groups of increasing morphological severity: essential, equivocal, and complex (scores of 0-3, 4-5, and ≥6). All probands underwent CMA, with WES performed for 95 proband-parent trios. The overall molecular diagnostic yield for CMA and WES in a population-based ASD sample stratified in 3 phenotypic groups. Of 258 probands, 24 (9.3%, 95%CI, 6.1%-13.5%) received a molecular diagnosis from CMA and 8 of 95 (8.4%, 95%CI, 3.7%-15.9%) from WES. The yields were statistically different between the morphological groups. Among the children who underwent both CMA and WES testing, the estimated proportion with an identifiable genetic etiology was 15.8% (95%CI, 9.1%-24.7%; 15/95 children). This included 2 children who received molecular diagnoses from both tests. The combined yield was significantly higher in the complex group when compared with the essential group (pairwise comparison, P = .002). [table: see text]. Among a heterogeneous sample of children with ASD, the molecular diagnostic yields of CMA and WES were comparable, and the combined molecular diagnostic yield was higher in children with more complex morphological phenotypes in comparison with the children in the essential category. If replicated in additional populations, these findings may inform appropriate selection of molecular diagnostic testing for children affected by ASD.

Hydroponics Database and Handbook for the Advanced Life Support Test Bed

NASA Technical Reports Server (NTRS)

Nash, Allen J.

1999-01-01

During the summer 1998, I did student assistance to Dr. Daniel J. Barta, chief plant growth expert at Johnson Space Center - NASA. We established the preliminary stages of a hydroponic crop growth database for the Advanced Life Support Systems Integration Test Bed, otherwise referred to as BIO-Plex (Biological Planetary Life Support Systems Test Complex). The database summarizes information from published technical papers by plant growth experts, and it includes bibliographical, environmental and harvest information based on plant growth under varying environmental conditions. I collected 84 lettuce entries, 14 soybean, 49 sweet potato, 16 wheat, 237 white potato, and 26 mix crop entries. The list will grow with the publication of new research. This database will be integrated with a search and systems analysis computer program that will cross-reference multiple parameters to determine optimum edible yield under varying parameters. Also, we have made preliminary effort to put together a crop handbook for BIO-Plex plant growth management. It will be a collection of information obtained from experts who provided recommendations on a particular crop's growing conditions. It includes bibliographic, environmental, nutrient solution, potential yield, harvest nutritional, and propagation procedure information. This handbook will stand as the baseline growth conditions for the first set of experiments in the BIO-Plex facility.

Methods for Remote Determination of CO2 Emissions

DTIC Science & Technology

2011-01-01

support monitoring of compliance with international agreements. • It is difficult to predict when direct measurements of CO2 will yield useful emission...level of reasonable prior information, which is combined with the direct measurements to yield an emissions estimate. This prior information might...infrastructure of a country could yield a “proxy” estimate of CO2 emissions by assuming emission factors for various supply and demand sectors a

Quantum process tomography of excitonic dimers from two-dimensional electronic spectroscopy. I. General theory and application to homodimers.

PubMed

Yuen-Zhou, Joel; Aspuru-Guzik, Alán

2011-04-07

Is it possible to infer the time evolving quantum state of a multichromophoric system from a sequence of two-dimensional electronic spectra (2D-ES) as a function of waiting time? Here we provide a positive answer for a tractable model system: a coupled dimer. After exhaustively enumerating the Liouville pathways associated to each peak in the 2D-ES, we argue that by judiciously combining the information from a series of experiments varying the polarization and frequency components of the pulses, detailed information at the amplitude level about the input and output quantum states at the waiting time can be obtained. This possibility yields a quantum process tomography (QPT) of the single-exciton manifold, which completely characterizes the open quantum system dynamics through the reconstruction of the process matrix. In this manuscript, we present the general theory as well as specific and numerical results for a homodimer, for which we prove that signals stemming from coherence to population transfer and vice versa vanish upon isotropic averaging, therefore, only allowing for a partial QPT in such case. However, this fact simplifies the spectra, and it follows that only two polarization controlled experiments (and no pulse-shaping requirements) suffice to yield the elements of the process matrix, which survive under isotropic averaging. Redundancies in the 2D-ES amplitudes allow for the angle between the two site transition dipole moments to be self-consistently obtained, hence simultaneously yielding structural and dynamical information of the dimer. Model calculations are presented, as well as an error analysis in terms of the angle between the dipoles and peak amplitude extraction. In the second article accompanying this study, we numerically exemplify the theory for heterodimers and carry out a detailed error analysis for such case. This investigation reveals an exciting quantum information processing (QIP) approach to spectroscopic experiments of excitonic systems, and hence, bridges an important gap between theoretical studies on excitation energy transfer from the QIP standpoint and experimental methods to study such systems in the chemical physics community.

Status of growth and yield information for northern forest types

Treesearch

Dale S. Solomon

1977-01-01

Existing regional growth-and-yield information for most of the northern forest types is summarized by species. Present research is concentrated on growth-simulation models, constructed by either aggregating available information or through individual tree growth studies. A uniformity of more refined measurements is needed so that future growth models can be tried for...

Analysis of yield and oil from a series of canola breeding trials. Part II. Exploring variety by environment interaction using factor analysis.

PubMed

Cullis, B R; Smith, A B; Beeck, C P; Cowling, W A

2010-11-01

Exploring and exploiting variety by environment (V × E) interaction is one of the major challenges facing plant breeders. In paper I of this series, we presented an approach to modelling V × E interaction in the analysis of complex multi-environment trials using factor analytic models. In this paper, we develop a range of statistical tools which explore V × E interaction in this context. These tools include graphical displays such as heat-maps of genetic correlation matrices as well as so-called E-scaled uniplots that are a more informative alternative to the classical biplot for large plant breeding multi-environment trials. We also present a new approach to prediction for multi-environment trials that include pedigree information. This approach allows meaningful selection indices to be formed either for potential new varieties or potential parents.

Predicting Great Lakes fish yields: tools and constraints

USGS Publications Warehouse

Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

1987-01-01

Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

Development of a European Ensemble System for Seasonal Prediction: Application to crop yield

NASA Astrophysics Data System (ADS)

Terres, J. M.; Cantelaube, P.

2003-04-01

Western European agriculture is highly intensive and the weather is the main source of uncertainty for crop yield assessment and for crop management. In the current system, at the time when a crop yield forecast is issued, the weather conditions leading up to harvest time are unknown and are therefore a major source of uncertainty. The use of seasonal weather forecast would bring additional information for the remaining crop season and has valuable benefit for improving the management of agricultural markets and environmentally sustainable farm practices. An innovative method for supplying seasonal forecast information to crop simulation models has been developed in the frame of the EU funded research project DEMETER. It consists in running a crop model on each individual member of the seasonal hindcasts to derive a probability distribution of crop yield. Preliminary results of cumulative probability function of wheat yield provides information on both the yield anomaly and the reliability of the forecast. Based on the spread of the probability distribution, the end-user can directly quantify the benefits and risks of taking weather-sensitive decisions.

Enhancement of Plant Metabolite Fingerprinting by Machine Learning1[W

PubMed Central

Scott, Ian M.; Vermeer, Cornelia P.; Liakata, Maria; Corol, Delia I.; Ward, Jane L.; Lin, Wanchang; Johnson, Helen E.; Whitehead, Lynne; Kular, Baldeep; Baker, John M.; Walsh, Sean; Dave, Anuja; Larson, Tony R.; Graham, Ian A.; Wang, Trevor L.; King, Ross D.; Draper, John; Beale, Michael H.

2010-01-01

Metabolite fingerprinting of Arabidopsis (Arabidopsis thaliana) mutants with known or predicted metabolic lesions was performed by 1H-nuclear magnetic resonance, Fourier transform infrared, and flow injection electrospray-mass spectrometry. Fingerprinting enabled processing of five times more plants than conventional chromatographic profiling and was competitive for discriminating mutants, other than those affected in only low-abundance metabolites. Despite their rapidity and complexity, fingerprints yielded metabolomic insights (e.g. that effects of single lesions were usually not confined to individual pathways). Among fingerprint techniques, 1H-nuclear magnetic resonance discriminated the most mutant phenotypes from the wild type and Fourier transform infrared discriminated the fewest. To maximize information from fingerprints, data analysis was crucial. One-third of distinctive phenotypes might have been overlooked had data models been confined to principal component analysis score plots. Among several methods tested, machine learning (ML) algorithms, namely support vector machine or random forest (RF) classifiers, were unsurpassed for phenotype discrimination. Support vector machines were often the best performing classifiers, but RFs yielded some particularly informative measures. First, RFs estimated margins between mutant phenotypes, whose relations could then be visualized by Sammon mapping or hierarchical clustering. Second, RFs provided importance scores for the features within fingerprints that discriminated mutants. These scores correlated with analysis of variance F values (as did Kruskal-Wallis tests, true- and false-positive measures, mutual information, and the Relief feature selection algorithm). ML classifiers, as models trained on one data set to predict another, were ideal for focused metabolomic queries, such as the distinctiveness and consistency of mutant phenotypes. Accessible software for use of ML in plant physiology is highlighted. PMID:20566707

Affective outcomes of virtual reality exposure therapy for anxiety and specific phobias: a meta-analysis.

PubMed

Parsons, Thomas D; Rizzo, Albert A

2008-09-01

Virtual reality exposure therapy (VRET) is an increasingly common treatment for anxiety and specific phobias. Lacking is a quantitative meta-analysis that enhances understanding of the variability and clinical significance of anxiety reduction outcomes after VRET. Searches of electronic databases yielded 52 studies, and of these, 21 studies (300 subjects) met inclusion criteria. Although meta-analysis revealed large declines in anxiety symptoms following VRET, moderator analyses were limited due to inconsistent reporting in the VRET literature. This highlights the need for future research studies that report uniform and detailed information regarding presence, immersion, anxiety and/or phobia duration, and demographics.

Commissioner's Annual Report to the Education Committees of the Senate and General Assembly on Violence, Vandalism and Substance Abuse in New Jersey Public Schools, July 1, 2007 to June 30, 2008

ERIC Educational Resources Information Center

New Jersey Department of Education, 2009

2009-01-01

The Commissioner's annual report provides the Legislature with information reported by school districts concerning incidents of serious student misconduct grouped into the following four major reporting categories: violence, vandalism, weapons, and substance abuse. An analysis of trends yields indications of progress and of ongoing concern, and…

Commissioner's Annual Report to the Education Committees of the Senate and General Assembly on Violence, Vandalism and Substance Abuse in New Jersey Public Schools, July 1, 2008 to June 30, 2009

ERIC Educational Resources Information Center

New Jersey Department of Education, 2010

2010-01-01

The Commissioner's annual report provides the Legislature with information reported by school districts concerning incidents of serious student misconduct grouped into the following four major reporting categories: violence, vandalism, weapons, and substance abuse. An analysis of trends yields indications of progress and of ongoing concern, and…

Blanks: a computer program for analyzing furniture rough-part needs in standard-size blanks

Treesearch

Philip A. Araman

1983-01-01

A computer program is described that allows a company to determine the number of edge-glued, standard-size blanks required to satisfy its rough-part needs for a given production period. Yield and cost information also is determined by the program. A list of the program inputs, outputs, and uses of outputs is described, and an example analysis with sample output is...

Mapping Human-Dominated Landscapes: the Distribution and Yield of Major Crops of the World

NASA Astrophysics Data System (ADS)

Monfreda, C.; Ramankutty, N.; Foley, J. A.

2005-12-01

Croplands cover 18 million km2, an area the size of South America, and provide ecosystem goods and services essential to human well-being. Most global land-cover classifications group the diversity of croplands into a single or very few categories, thereby excluding critical information to answer key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information on land-use practices is even more limited. The relative lack of information about agricultural landscapes results partly from difficulties in using satellite data to identify individual crop types and land-use practices at a global scale. We address limitations common to remote-sensing classifications by distributing national, state, and county level statistics across a recently updated global dataset of cropland cover at 5 minute resolution. The resulting datasets depict the fractional harvested area and yield of twenty distinct crop types: maize, wheat, rice, sorghum, millet, barley, oats, soybeans, sunflower, rapeseed/canola, pulses, groundnuts/peanuts, oil palm, cassava, potatoes, sugar cane, sugar beets, tobacco, coffee, and cotton. These datasets represent the state of agriculture circa the year 2000 and will be made available for applications in ecological analysis, modeling, visualization, and education.

Identification and delineation of areas flood hazard using high accuracy of DEM data

NASA Astrophysics Data System (ADS)

Riadi, B.; Barus, B.; Widiatmaka; Yanuar, M. J. P.; Pramudya, B.

2018-05-01

Flood incidents that often occur in Karawang regency need to be mitigated. These expectations exist on technologies that can predict, anticipate and reduce disaster risks. Flood modeling techniques using Digital Elevation Model (DEM) data can be applied in mitigation activities. High accuracy DEM data used in modeling, will result in better flooding flood models. The result of high accuracy DEM data processing will yield information about surface morphology which can be used to identify indication of flood hazard area. The purpose of this study was to identify and describe flood hazard areas by identifying wetland areas using DEM data and Landsat-8 images. TerraSAR-X high-resolution data is used to detect wetlands from landscapes, while land cover is identified by Landsat image data. The Topography Wetness Index (TWI) method is used to detect and identify wetland areas with basic DEM data, while for land cover analysis using Tasseled Cap Transformation (TCT) method. The result of TWI modeling yields information about potential land of flood. Overlay TWI map with land cover map that produces information that in Karawang regency the most vulnerable areas occur flooding in rice fields. The spatial accuracy of the flood hazard area in this study was 87%.

Mask industry assessment trend analysis

NASA Astrophysics Data System (ADS)

Hughes, Greg; Yun, Henry

2009-01-01

Microelectronics industry leaders routinely name the cost and cycle time of mask technology and mask supply as top critical issues. A survey was created with support from SEMATECH to gather information about the mask industry as an objective assessment of its overall condition. This year's survey data were presented in detail at BACUS and the detailed trend analysis presented at EMLC. The survey is designed with the input of semiconductor company mask technologists and merchant mask suppliers. This year's assessment is the seventh in the current series of annual reports. With continued industry support, the report can be used as a baseline to gain perspective on the technical and business status of the mask and microelectronics industries. The report will continue to serve as a valuable reference to identify the strengths and opportunities of the mask industry. The results will be used to guide future investments on critical path issues. This year's survey is basically the same as the surveys in 2005 through 2007. Questions are grouped into seven categories: General Business Profile Information, Data Processing, Yields and Yield Loss, Mechanisms, Delivery Times, Returns, and Services. (Examples are given below). Within each category is a multitude of questions that creates a detailed profile of both the business and technical status of the critical mask industry.

Development of a Dmt Monitor for Statistical Tracking of Gravitational-Wave Burst Triggers Generated from the Omega Pipeline

NASA Astrophysics Data System (ADS)

Li, Jun-Wei; Cao, Jun-Wei

2010-04-01

One challenge in large-scale scientific data analysis is to monitor data in real-time in a distributed environment. For the LIGO (Laser Interferometer Gravitational-wave Observatory) project, a dedicated suit of data monitoring tools (DMT) has been developed, yielding good extensibility to new data type and high flexibility to a distributed environment. Several services are provided, including visualization of data information in various forms and file output of monitoring results. In this work, a DMT monitor, OmegaMon, is developed for tracking statistics of gravitational-wave (OW) burst triggers that are generated from a specific OW burst data analysis pipeline, the Omega Pipeline. Such results can provide diagnostic information as reference of trigger post-processing and interferometer maintenance.

Fission yield covariances for JEFF: A Bayesian Monte Carlo method

NASA Astrophysics Data System (ADS)

Leray, Olivier; Rochman, Dimitri; Fleming, Michael; Sublet, Jean-Christophe; Koning, Arjan; Vasiliev, Alexander; Ferroukhi, Hakim

2017-09-01

The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties) and the theoretical knowledge from the GEF code. Examples of this method are presented for the main actinides together with their impacts on simple burn-up and decay heat calculations.

Proton irradiation of simple gas mixtures: Influence of irradiation parameters

NASA Technical Reports Server (NTRS)

Sack, Norbert J.; Schuster, R.; Hofmann, A.

1990-01-01

In order to get information about the influence of irradiation parameters on radiolysis processes of astrophysical interest, methane gas targets were irradiated with 6.5 MeV protons at a pressure of 1 bar and room temperature. Yields of higher hydrocarbons like ethane or propane were found by analysis of irradiated gas samples using gas chromatography. The handling of the proton beam was of great experimental importance for determining the irradiation parameters. In a series of experiments current density of the proton beam and total absorbed energy were shown to have a large influence on the yields of produced hydrocarbons. Mechanistic interpretations of the results are given and conclusions are drawn with regard to the chemistry and the simulation of various astrophysical systems.

Non-dimensional groups in the description of finite-amplitude sound propagation through aerosols

NASA Technical Reports Server (NTRS)

Scott, D. S.

1976-01-01

Several parameters, which have fairly transparent physical interpretations, appear in the analytic description of finite-amplitude sound propagation through aerosols. Typically, each of these parameters characterizes, in some sense, either the sound or the aerosol. It also turns out that fairly obvious combinations of these parameters yield non-dimensional groups which, in turn, characterize the nature of the acoustic-aerosol interaction. This theme is developed in order to illustrate how a quick examination of such parameters and groups can yield information about the nature of the processes involved, without the necessity of extensive mathematical analysis. This concept is developed primarily from the viewpoint of sound propagation through aerosols, although complimentary acoustic-aerosol interaction phenomena are briefly noted.

Variation of inulin content, inulin yield and water use efficiency for inulin yield in Jerusalem artichoke genotypes under different water regimes

USDA-ARS?s Scientific Manuscript database

The information on genotypic variation for inulin content, inulin yield and water use efficiency of inulin yield (WUEi) in response to drought is limited. This study was to investigate the genetic variability in inulin content, inulin yield and WUEi of Jerusalem artichoke (Helianthus tuberosus L.) ...

Modeling Mental Health Information Preferences During the Early Adult Years: A Discrete Choice Conjoint Experiment

PubMed Central

Cunningham, Charles E.; Walker, John R.; Eastwood, John D.; Westra, Henny; Rimas, Heather; Chen, Yvonne; Marcus, Madalyn; Swinson, Richard P.; Bracken, Keyna

2013-01-01

Although most young adults with mood and anxiety disorders do not seek treatment, those who are better informed about mental health problems are more likely to use services. The authors used conjoint analysis to model strategies for providing information about anxiety and depression to young adults. Participants (N = 1,035) completed 17 choice tasks presenting combinations of 15 four-level attributes of a mental health information strategy. Latent class analysis yielded 3 segments. The virtual segment (28.7%) preferred working independently on the Internet to obtain information recommended by young adults who had experienced anxiety or depression. Self-assessment options and links to service providers were more important to this segment. Conventional participants (30.1%) preferred books or pamphlets recommended by a doctor, endorsed by mental health professionals, and used with a doctor's support. They would devote more time to information acquisition but were less likely to use Internet social networking options. Brief sources of information were more important to the low interest segment (41.2%). All segments preferred information about alternative ways to reduce anxiety or depression rather than psychological approaches or medication. Maximizing the use of information requires active and passive approaches delivered through old-media (e.g. books) and new-media (e.g., Internet) channels. PMID:24266450

Modeling mental health information preferences during the early adult years: a discrete choice conjoint experiment.

PubMed

Cunningham, Charles E; Walker, John R; Eastwood, John D; Westra, Henny; Rimas, Heather; Chen, Yvonne; Marcus, Madalyn; Swinson, Richard P; Bracken, Keyna; The Mobilizing Minds Research Group

2014-04-01

Although most young adults with mood and anxiety disorders do not seek treatment, those who are better informed about mental health problems are more likely to use services. The authors used conjoint analysis to model strategies for providing information about anxiety and depression to young adults. Participants (N = 1,035) completed 17 choice tasks presenting combinations of 15 four-level attributes of a mental health information strategy. Latent class analysis yielded 3 segments. The virtual segment (28.7%) preferred working independently on the Internet to obtain information recommended by young adults who had experienced anxiety or depression. Self-assessment options and links to service providers were more important to this segment. Conventional participants (30.1%) preferred books or pamphlets recommended by a doctor, endorsed by mental health professionals, and used with a doctor's support. They would devote more time to information acquisition but were less likely to use Internet social networking options. Brief sources of information were more important to the low interest segment (41.2%). All segments preferred information about alternative ways to reduce anxiety or depression rather than psychological approaches or medication. Maximizing the use of information requires active and passive approaches delivered through old-media (e.g., books) and new-media (e.g., Internet) channels.

Growth Characteristics of Organisms

NASA Astrophysics Data System (ADS)

Gatenby, Robert A.; Frieden, B. Roy

In this chapter a systems viewpoint is taken of the growth characteristics of normal and malignant tissue. We find that such growth is well analyzed by the concepts of Shannon and Fisher information. In Section 3.1 conventional mechanisms of information transmission via DNA, RNA, and proteins are identified, as well as unconventional structures such as lipids and ion gradients. Information storage, flow, and utilization are analyzed, both within cells and over a system of cells. In Section 3.2, malignant tissue growth is found to be accurately described by the use of Fisher information in particular. Cancer growth is seen to occur as a disease of information, in fact an information catastrophe due to the regression of cells to a minimally ordered state consistent with life. The analysis yields many predictions about the growth of healthy tissue and cancerous tissue, some of which are nonintuitive and have a strong bearing on cancer diagnosis and treatment.

Sensitive and Structure-Informative N-Glycosylation Analysis by MALDI-MS; Ionization, Fragmentation, and Derivatization

PubMed Central

Nishikaze, Takashi

2017-01-01

Mass spectrometry (MS) has become an indispensable tool for analyzing post translational modifications of proteins, including N-glycosylated molecules. Because most glycosylation sites carry a multitude of glycans, referred to as “glycoforms,” the purpose of an N-glycosylation analysis is glycoform profiling and glycosylation site mapping. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has unique characteristics that are suited for the sensitive analysis of N-glycosylated products. However, the analysis is often hampered by the inherent physico-chemical properties of N-glycans. Glycans are highly hydrophilic in nature, and therefore tend to show low ion yields in both positive- and negative-ion modes. The labile nature and complicated branched structures involving various linkage isomers make structural characterization difficult. This review focuses on MALDI-MS-based approaches for enhancing analytical performance in N-glycosylation research. In particular, the following three topics are emphasized: (1) Labeling for enhancing the ion yields of glycans and glycopeptides, (2) Negative-ion fragmentation for less ambiguous elucidation of the branched structure of N-glycans, (3) Derivatization for the stabilization and linkage isomer discrimination of sialic acid residues. PMID:28794918

The use of Fourier-transform infrared spectroscopy to predict cheese yield and nutrient recovery or whey loss traits from unprocessed bovine milk samples.

PubMed

Ferragina, A; Cipolat-Gotet, C; Cecchinato, A; Bittante, G

2013-01-01

Cheese yield is an important technological trait in the dairy industry in many countries. The aim of this study was to evaluate the effectiveness of Fourier-transform infrared (FTIR) spectral analysis of fresh unprocessed milk samples for predicting cheese yield and nutrient recovery traits. A total of 1,264 model cheeses were obtained from 1,500-mL milk samples collected from individual Brown Swiss cows. Individual measurements of 7 new cheese yield-related traits were obtained from the laboratory cheese-making procedure, including the fresh cheese yield, total solid cheese yield, and the water retained in curd, all as a percentage of the processed milk, and nutrient recovery (fat, protein, total solids, and energy) in the curd as a percentage of the same nutrient contained in the milk. All individual milk samples were analyzed using a MilkoScan FT6000 over the spectral range from 5,000 to 900 wavenumber × cm(-1). Two spectral acquisitions were carried out for each sample and the results were averaged before data analysis. Different chemometric models were fitted and compared with the aim of improving the accuracy of the calibration equations for predicting these traits. The most accurate predictions were obtained for total solid cheese yield and fresh cheese yield, which exhibited coefficients of determination between the predicted and measured values in cross-validation (1-VR) of 0.95 and 0.83, respectively. A less favorable result was obtained for water retained in curd (1-VR=0.65). Promising results were obtained for recovered protein (1-VR=0.81), total solids (1-VR=0.86), and energy (1-VR=0.76), whereas recovered fat exhibited a low accuracy (1-VR=0.41). As FTIR spectroscopy is a rapid, cheap, high-throughput technique that is already used to collect standard milk recording data, these FTIR calibrations for cheese yield and nutrient recovery highlight additional potential applications of the technique in the dairy industry, especially for monitoring cheese-making processes and milk payment systems. In addition, the prediction models can be used to provide breeding organizations with information on new phenotypes for cheese yield and milk nutrient recovery, potentially allowing these traits to be enhanced through selection. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NASA Technical Reports Server (NTRS)

Makowski, David; Asseng, Senthold; Ewert, Frank; Bassu, Simona; Durand, Jean-Louis; Martre, Pierre; Adam, Myriam; Aggarwal, Pramod K.; Angulo, Carlos; Baron, Chritian;

Gene by Social-Context Interactions for Number of Sexual Partners Among White Male Youths: Genetics-informed Sociology

PubMed Central

Guo, Guang; Tong, Yuying; Cai, Tianji

2010-01-01

In this study, we set out to investigate whether introducing molecular genetic measures into an analysis of sexual partner variety will yield novel sociological insights. The data source is the white male DNA sample in the National Longitudinal Study of Adolescent Health. Our empirical analysis has produced a robust protective effect of the 9R/9R genotype relative to the Any10R genotype in the dopamine transporter gene (DAT1). The gene-environment interaction analysis demonstrates that the protective effect of 9R/9R tends to be lost in schools in which higher proportions of students start having sex early or among those with relatively low levels of cognitive ability. Our genetics-informed sociological analysis suggests that the “one size” of a single social theory may not fit all. Explaining a human trait or behavior may require a theory that accommodates the complex interplay between social contextual and individual influences and genetic predispositions. PMID:19569400

Geographic information system as country-level development and monitoring tool, Senegal example

USGS Publications Warehouse

Moore, Donald G.; Howard, Stephen M.; ,

1990-01-01

Geographic information systems (GIS) allow an investigator the capability to merge and analyze numerous types of country-level resource data. Hypothetical resource analysis applications in Senegal were conducted to illustrate the utility of a GIS for development planning and resource monitoring. Map and attribute data for soils, vegetation, population, infrastructure, and administrative units were merged to form a database within a GIS. Several models were implemented using a GIS to: analyze development potential for sustainable dryland agriculture; prioritize where agricultural development should occur based upon a regional food budget; and monitor dynamic events with remote sensing. The steps for implementing a GIS analysis are described and illustrated, and the use of a GIS for conducting an economic analysis is outlined. Using a GIS for analysis and display of results opens new methods of communication between resource scientists and decision makers. Analyses yielding country-wide map output and detailed statistical data for each level of administration provide the advantage of a single system that can serve a variety of users.

Towards integrated pest management in red clover seed production.

PubMed

Lundin, Ola; Rundlöf, Maj; Smith, Henrik G; Bommarco, Riccardo

2012-10-01

The development of integrated pest management is hampered by lack of information on how insect pest abundances relate to yield losses, and how pests are affected by control measures. In this study, we develop integrated pest management tactics for Apion spp. weevils (Coleoptera: Brentidae) in seed production of red clover, Trifolium pratense L. We tested a method to forecast pest damage, quantified the relationship between pest abundance and yield, and evaluated chemical and biological pest control in 29 Swedish red clover fields in 2008 and 2011. Pest inflorescence abundance, which had a highly negative effect on yield, could be predicted with pan trap catches of adult pests. In 2008, chemical control with typically one application of pyrethroids was ineffective both in decreasing pest abundances and in increasing yields. In 2011, when chemical control included applications of the neonicotinoid thiacloprid, pest abundances decreased and yields increased considerably in treated field zones. A post hoc analysis indicated that using pyrethroids in addition to thiacloprid was largely redundant. Infestation rates by parasitoids was higher and reached average levels of around 40% in insecticide treated field zones in 2011, which is a level of interest for biological pest control. Based on the data presented, an economic threshold for chemical control is developed, and guidelines are provided on minimum effective chemical pest control.

From loquacious to reticent: understanding patient health information communication to guide consumer health IT design.

PubMed

Valdez, Rupa S; Guterbock, Thomas M; Fitzgibbon, Kara; Williams, Ishan C; Wellbeloved-Stone, Claire A; Bears, Jaime E; Menefee, Hannah K

2017-07-01

It is increasingly recognized that some patients self-manage in the context of social networks rather than alone. Consumer health information technology (IT) designed to support socially embedded self-management must be responsive to patients' everyday communication practices. There is an opportunity to improve consumer health IT design by explicating how patients currently leverage social media to support health information communication. The objective of this study was to determine types of health information communication patterns that typify Facebook users with chronic health conditions to guide consumer health IT design. Seven hundred participants with type 2 diabetes were recruited through a commercial survey access panel. Cluster analysis was used to identify distinct approaches to health information communication both on and off Facebook. Analysis of variance (ANOVA) methods were used to identify demographic and behavioral differences among profiles. Secondary analysis of qualitative interviews ( n  = 25) and analysis of open-ended survey questions were conducted to understand participant rationales for each profile. Our analysis yielded 7 distinct health information communication profiles. Five of 7 profiles had consistent patterns both on and off Facebook, while the remaining 2 demonstrated distinct practices, with no health information communication on Facebook but some off Facebook. One profile was distinct from all others in both health information communication practices and demographic composition. Rationales for following specific health information communication practices were categorized under 6 themes: altruism, instrumental support, social support, privacy and stigma, convenience, and Facebook knowledge. Facebook has been widely adopted for health information communication; This study demonstrates that Facebook has been widely adopted for health information communication. It also shows that the ways in which patients communicate health information on and off Facebook are diverse. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Anthropic Correction of Information Estimates and Its Application to Neural Coding

PubMed Central

Gastpar, Michael C.; Gill, Patrick R.; Huth, Alexander G.; Theunissen, Frédéric E.

2015-01-01

Information theory has been used as an organizing principle in neuroscience for several decades. Estimates of the mutual information (MI) between signals acquired in neurophysiological experiments are believed to yield insights into the structure of the underlying information processing architectures. With the pervasive availability of recordings from many neurons, several information and redundancy measures have been proposed in the recent literature. A typical scenario is that only a small number of stimuli can be tested, while ample response data may be available for each of the tested stimuli. The resulting asymmetric information estimation problem is considered. It is shown that the direct plug-in information estimate has a negative bias. An anthropic correction is introduced that has a positive bias. These two complementary estimators and their combinations are natural candidates for information estimation in neuroscience. Tail and variance bounds are given for both estimates. The proposed information estimates are applied to the analysis of neural discrimination and redundancy in the avian auditory system. PMID:26900172

Anthropic Correction of Information Estimates and Its Application to Neural Coding.

PubMed

Gastpar, Michael C; Gill, Patrick R; Huth, Alexander G; Theunissen, Frédéric E

2010-02-01

Information theory has been used as an organizing principle in neuroscience for several decades. Estimates of the mutual information (MI) between signals acquired in neurophysiological experiments are believed to yield insights into the structure of the underlying information processing architectures. With the pervasive availability of recordings from many neurons, several information and redundancy measures have been proposed in the recent literature. A typical scenario is that only a small number of stimuli can be tested, while ample response data may be available for each of the tested stimuli. The resulting asymmetric information estimation problem is considered. It is shown that the direct plug-in information estimate has a negative bias. An anthropic correction is introduced that has a positive bias. These two complementary estimators and their combinations are natural candidates for information estimation in neuroscience. Tail and variance bounds are given for both estimates. The proposed information estimates are applied to the analysis of neural discrimination and redundancy in the avian auditory system.

From Paris to Iowa and Back: Global Temperature Targets, Agricultural Impacts, and Producer Response

NASA Astrophysics Data System (ADS)

Anderson, C.; Hayhoe, K.; Terando, A. J.

2016-12-01

Traditionally, assessments such as those produced by IPCC and USGCRP have been structured to provide a one-way flow of information from scientists to national and international policy makers. Because the Paris Agreement will ultimately require corresponding domestic policies, the traditional one-way information flow could be inadequate, since it lacks both direct participation and informed feedback from many of the important entities that influence domestic policy. We have engaged Iowa row crop producers in identifying impacts and feasibility of adaptation under global warming of 1.0 and 2.0OC. Our engagement seeks to create within climate impacts assessment a decision-maker feedback loop. We have engaged an expert panel by using yield data modeling as a first step to communicate vividly the potential yield impacts of global average temperature targets. This engagement included validation with historical global average temperature before presenting yield impact under global mean surface temperature increase of 1.0 and 2.0OC. The expert panel requested further analysis of targets at 0.25 and 0.50OC increase and of possible impacts should they pursue adaptation by increasing maize plant population density and soil moisture storage. Several clear messages have emerged that can be voiced by Iowa agribusiness leaders to national and international decision-makers. While Iowa soybean agriculture may remain robust for the foreseeable future, the Paris Agreement is insufficient to protect Iowa maize production from substantial changes in productivity and volatility. These effects could be largely (though not entirely) mitigated by moving from the current +2OC to the "high ambition" +1.5OC target. The projected spring rainfall increase of 10% under +1OC would increase the cost of spring planting. The data model predicts a 5-day reduction in average number of fieldwork days, which requires the addition of one half-time person or larger planting equipment. The current annual rate of increase in maize plant density will maintain historical yield increase through +1OC but by +2OC is substantially reduced and results in unprecedented yield volatility. By increasing soil moisture during July, Iowa maize production can reduce markedly the impacts of +2OC.

Mask industry assessment trend analysis

NASA Astrophysics Data System (ADS)

Shelden, Gilbert; Marmillion, Patricia; Hughes, Greg

2008-04-01

Microelectronics industry leaders routinely name the cost and cycle time of mask technology and mask supply as top critical issues. A survey was created with support from SEMATECH and administered by SEMI North America to gather information about the mask industry as an objective assessment of its overall condition. This year's survey data were presented in detail at BACUS and the detailed trend analysis presented at EMLC. The survey is designed with the input of semiconductor company mask technologists, merchant mask suppliers, and industry equipment makers. This year's assessment is the sixth in the current series of annual reports. With continued industry support, the report can be used as a baseline to gain perspective on the technical and business status of the mask and microelectronics industries. The report will continue to serve as a valuable reference to identify the strengths and opportunities of the mask industry. The results will be used to guide future investments on critical path issues. This year's survey is basically the same as the 2005 and 2006 surveys. Questions are grouped into eight categories: General Business Profile Information, Data Processing, Yields and Yield Loss, Mechanisms, Delivery Times, Returns and Services, Operating Cost Factors, and Equipment Utilization. Within each category is a multitude of questions that creates a detailed profile of both the business and technical status of the critical mask industry. Note: the questions covering operating cost factors and equipment utilization were added to the survey only in 2005; therefore, meaningful trend analysis is not available.

Radiation use efficiency, biomass production, and grain yield in two maize hybrids differing in drought tolerance

USDA-ARS?s Scientific Manuscript database

Drought tolerant (DT) maize (Zea mays L.) hybrids have potential to increase yield under drought conditions. However, little information is known about the physiological determinations of yield in DT hybrids. Our objective was to assess radiation use efficiency (RUE), biomass production, and yield ...

Assessment of Climate Change Impacts on Agricultural Water Demands and Crop Yields in California's Central Valley

NASA Astrophysics Data System (ADS)

Tansey, M. K.; Flores-Lopez, F.; Young, C. A.; Huntington, J. L.

2012-12-01

Long term planning for the management of California's water resources requires assessment of the effects of future climate changes on both water supply and demand. Considerable progress has been made on the evaluation of the effects of future climate changes on water supplies but less information is available with regard to water demands. Uncertainty in future climate projections increases the difficulty of assessing climate impacts and evaluating long range adaptation strategies. Compounding the uncertainty in the future climate projections is the fact that most readily available downscaled climate projections lack sufficient meteorological information to compute evapotranspiration (ET) by the widely accepted ASCE Penman-Monteith (PM) method. This study addresses potential changes in future Central Valley water demands and crop yields by examining the effects of climate change on soil evaporation, plant transpiration, growth and yield for major types of crops grown in the Central Valley of California. Five representative climate scenarios based on 112 bias corrected spatially downscaled CMIP 3 GCM climate simulations were developed using the hybrid delta ensemble method to span a wide range future climate uncertainty. Analysis of historical California Irrigation Management Information System meteorological data was combined with several meteorological estimation methods to compute future solar radiation, wind speed and dew point temperatures corresponding to the GCM projected temperatures and precipitation. Future atmospheric CO2 concentrations corresponding to the 5 representative climate projections were developed based on weighting IPCC SRES emissions scenarios. The Land, Atmosphere, and Water Simulator (LAWS) model was used to compute ET and yield changes in the early, middle and late 21st century for 24 representative agricultural crops grown in the Sacramento, San Joaquin and Tulare Lake basins. Study results indicate that changes in ET and yield vary between crops due to plant specific sensitivities to temperature, solar radiation and the vapor pressure deficits. Shifts in the growth period to earlier in the year, shortened growth period for annual crops as well as extended fall growth can also exert important influences. Projected increases in CO2 concentrations in the late 21st century exert very significant influences on ET and yield for many crops. To characterize potential impacts and the range of uncertainty, changes in total agricultural water demands and yields were computed assuming that current crop types and acreages in 21 Central Valley regional planning areas remained constant throughout the 21st century for each of the 5 representative future climate scenarios.

Exploring and Harnessing Haplotype Diversity to Improve Yield Stability in Crops.

PubMed

Qian, Lunwen; Hickey, Lee T; Stahl, Andreas; Werner, Christian R; Hayes, Ben; Snowdon, Rod J; Voss-Fels, Kai P

2017-01-01

In order to meet future food, feed, fiber, and bioenergy demands, global yields of all major crops need to be increased significantly. At the same time, the increasing frequency of extreme weather events such as heat and drought necessitates improvements in the environmental resilience of modern crop cultivars. Achieving sustainably increase yields implies rapid improvement of quantitative traits with a very complex genetic architecture and strong environmental interaction. Latest advances in genome analysis technologies today provide molecular information at an ultrahigh resolution, revolutionizing crop genomic research, and paving the way for advanced quantitative genetic approaches. These include highly detailed assessment of population structure and genotypic diversity, facilitating the identification of selective sweeps and signatures of directional selection, dissection of genetic variants that underlie important agronomic traits, and genomic selection (GS) strategies that not only consider major-effect genes. Single-nucleotide polymorphism (SNP) markers today represent the genotyping system of choice for crop genetic studies because they occur abundantly in plant genomes and are easy to detect. SNPs are typically biallelic, however, hence their information content compared to multiallelic markers is low, limiting the resolution at which SNP-trait relationships can be delineated. An efficient way to overcome this limitation is to construct haplotypes based on linkage disequilibrium, one of the most important features influencing genetic analyses of crop genomes. Here, we give an overview of the latest advances in genomics-based haplotype analyses in crops, highlighting their importance in the context of polyploidy and genome evolution, linkage drag, and co-selection. We provide examples of how haplotype analyses can complement well-established quantitative genetics frameworks, such as quantitative trait analysis and GS, ultimately providing an effective tool to equip modern crops with environment-tailored characteristics.

Genetic Analysis of Milk Yield in First-Lactation Holstein Friesian in Ethiopia: A Lactation Average vs Random Regression Test-Day Model Analysis

PubMed Central

Meseret, S.; Tamir, B.; Gebreyohannes, G.; Lidauer, M.; Negussie, E.

2015-01-01

The development of effective genetic evaluations and selection of sires requires accurate estimates of genetic parameters for all economically important traits in the breeding goal. The main objective of this study was to assess the relative performance of the traditional lactation average model (LAM) against the random regression test-day model (RRM) in the estimation of genetic parameters and prediction of breeding values for Holstein Friesian herds in Ethiopia. The data used consisted of 6,500 test-day (TD) records from 800 first-lactation Holstein Friesian cows that calved between 1997 and 2013. Co-variance components were estimated using the average information restricted maximum likelihood method under single trait animal model. The estimate of heritability for first-lactation milk yield was 0.30 from LAM whilst estimates from the RRM model ranged from 0.17 to 0.29 for the different stages of lactation. Genetic correlations between different TDs in first-lactation Holstein Friesian ranged from 0.37 to 0.99. The observed genetic correlation was less than unity between milk yields at different TDs, which indicated that the assumption of LAM may not be optimal for accurate evaluation of the genetic merit of animals. A close look at estimated breeding values from both models showed that RRM had higher standard deviation compared to LAM indicating that the TD model makes efficient utilization of TD information. Correlations of breeding values between models ranged from 0.90 to 0.96 for different group of sires and cows and marked re-rankings were observed in top sires and cows in moving from the traditional LAM to RRM evaluations. PMID:26194217

Test-well drilling in the upper Satus Creek basin, Yakima Indian Reservation, Washington

USGS Publications Warehouse

Pearson, H.E.

1977-01-01

Two test wells were drilled in the upper Satus Creek basin of the Yakima Indian Reservation, Washington, using the air-rotary method. At site 1 the well penetrated a young basalt and 175 feet of the Yakima Basalt, and at site 2 the well penetrated the young basalt. The well at site 1 was drilled to a depth of 350 feet. Tests for drawdown and yield indicated a specific capacity of about 11 gallons per minute per foot of drawdown. The potential yield of this well may be about 1,000 gallons per minute. The well at site 2 was drilled to a depth of 500 feet. Only a small quantity of water was encountered and no test for yield was made. Data from these wells, including chemical analysis of the water from the well at site 1, will provide information useful in the development and management of the ground-water resources in this part of the Yakima Indian Reservation. (Woodard-USGS)

On-line prediction of yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score using the MARC beef carcass image analysis system.

PubMed

Shackelford, S D; Wheeler, T L; Koohmaraie, M

2003-01-01

The present experiment was conducted to evaluate the ability of the U.S. Meat Animal Research Center's beef carcass image analysis system to predict calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score under commercial beef processing conditions. In two commercial beef-processing facilities, image analysis was conducted on 800 carcasses on the beef-grading chain immediately after the conventional USDA beef quality and yield grades were applied. Carcasses were blocked by plant and observed calculated yield grade. The carcasses were then separated, with 400 carcasses assigned to a calibration data set that was used to develop regression equations, and the remaining 400 carcasses assigned to a prediction data set used to validate the regression equations. Prediction equations, which included image analysis variables and hot carcass weight, accounted for 90, 88, 90, 88, and 76% of the variation in calculated yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score, respectively, in the prediction data set. In comparison, the official USDA yield grade as applied by online graders accounted for 73% of the variation in calculated yield grade. The technology described herein could be used by the beef industry to more accurately determine beef yield grades; however, this system does not provide an accurate enough prediction of marbling score to be used without USDA grader interaction for USDA quality grading.

Obesity in social media: a mixed methods analysis.

PubMed

Chou, Wen-Ying Sylvia; Prestin, Abby; Kunath, Stephen

2014-09-01

The escalating obesity rate in the USA has made obesity prevention a top public health priority. Recent interventions have tapped into the social media (SM) landscape. To leverage SM in obesity prevention, we must understand user-generated discourse surrounding the topic. This study was conducted to describe SM interactions about weight through a mixed methods analysis. Data were collected across 60 days through SM monitoring services, yielding 2.2 million posts. Data were cleaned and coded through Natural Language Processing (NLP) techniques, yielding popular themes and the most retweeted content. Qualitative analyses of selected posts add insight into the nature of the public dialogue and motivations for participation. Twitter represented the most common channel. Twitter and Facebook were dominated by derogatory and misogynist sentiment, pointing to weight stigmatization, whereas blogs and forums contained more nuanced comments. Other themes included humor, education, and positive sentiment countering weight-based stereotypes. This study documented weight-related attitudes and perceptions. This knowledge will inform public health/obesity prevention practice.

77 FR 74191 - Information Collection; Proposed Collection; Comment Request; General Services Administration...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-13

... insights on perceptions and opinions, but are not statistical surveys that yield quantitative results that.... This type of generic clearance for qualitative information will not be used for quantitative... for submission for other generic mechanisms that are designed to yield quantitative results. The...

An information system design for watershed-wide modeling of water loss to the atmosphere using remote sensing techniques

NASA Technical Reports Server (NTRS)

Khorram, S.

1977-01-01

Results are presented of a study intended to develop a general location-specific remote-sensing procedure for watershed-wide estimation of water loss to the atmosphere by evaporation and transpiration. The general approach involves a stepwise sequence of required information definition (input data), appropriate sample design, mathematical modeling, and evaluation of results. More specifically, the remote sensing-aided system developed to evaluate evapotranspiration employs a basic two-stage two-phase sample of three information resolution levels. Based on the discussed design, documentation, and feasibility analysis to yield timely, relatively accurate, and cost-effective evapotranspiration estimates on a watershed or subwatershed basis, work is now proceeding to implement this remote sensing-aided system.

Shea (Vitellaria paradoxa Gaertn C. F.) fruit yield assessment and management by farm households in the Atacora district of Benin

PubMed Central

Villamor, Grace B.; Nyarko, Benjamin Kofi; Wala, Kperkouma; Akpagana, Koffi

2018-01-01

Vitellaria paradoxa (Gaertn C. F.), or shea tree, remains one of the most valuable trees for farmers in the Atacora district of northern Benin, where rural communities depend on shea products for both food and income. To optimize productivity and management of shea agroforestry systems, or "parklands," accurate and up-to-date data are needed. For this purpose, we monitored120 fruiting shea trees for two years under three land-use scenarios and different soil groups in Atacora, coupled with a farm household survey to elicit information on decision making and management practices. To examine the local pattern of shea tree productivity and relationships between morphological factors and yields, we used a randomized branch sampling method and applied a regression analysis to build a shea yield model based on dendrometric, soil and land-use variables. We also compared potential shea yields based on farm household socio-economic characteristics and management practices derived from the survey data. Soil and land-use variables were the most important determinants of shea fruit yield. In terms of land use, shea trees growing on farmland plots exhibited the highest yields (i.e., fruit quantity and mass) while trees growing on Lixisols performed better than those of the other soil group. Contrary to our expectations, dendrometric parameters had weak relationships with fruit yield regardless of land-use and soil group. There is an inter-annual variability in fruit yield in both soil groups and land-use type. In addition to observed inter-annual yield variability, there was a high degree of variability in production among individual shea trees. Furthermore, household socioeconomic characteristics such as road accessibility, landholding size, and gross annual income influence shea fruit yield. The use of fallow areas is an important land management practice in the study area that influences both conservation and shea yield. PMID:29346406

Shea (Vitellaria paradoxa Gaertn C. F.) fruit yield assessment and management by farm households in the Atacora district of Benin.

PubMed

Aleza, Koutchoukalo; Villamor, Grace B; Nyarko, Benjamin Kofi; Wala, Kperkouma; Akpagana, Koffi

2018-01-01

Vitellaria paradoxa (Gaertn C. F.), or shea tree, remains one of the most valuable trees for farmers in the Atacora district of northern Benin, where rural communities depend on shea products for both food and income. To optimize productivity and management of shea agroforestry systems, or "parklands," accurate and up-to-date data are needed. For this purpose, we monitored120 fruiting shea trees for two years under three land-use scenarios and different soil groups in Atacora, coupled with a farm household survey to elicit information on decision making and management practices. To examine the local pattern of shea tree productivity and relationships between morphological factors and yields, we used a randomized branch sampling method and applied a regression analysis to build a shea yield model based on dendrometric, soil and land-use variables. We also compared potential shea yields based on farm household socio-economic characteristics and management practices derived from the survey data. Soil and land-use variables were the most important determinants of shea fruit yield. In terms of land use, shea trees growing on farmland plots exhibited the highest yields (i.e., fruit quantity and mass) while trees growing on Lixisols performed better than those of the other soil group. Contrary to our expectations, dendrometric parameters had weak relationships with fruit yield regardless of land-use and soil group. There is an inter-annual variability in fruit yield in both soil groups and land-use type. In addition to observed inter-annual yield variability, there was a high degree of variability in production among individual shea trees. Furthermore, household socioeconomic characteristics such as road accessibility, landholding size, and gross annual income influence shea fruit yield. The use of fallow areas is an important land management practice in the study area that influences both conservation and shea yield.

Integrating NASA Satellite Data Into USDA World Agricultural Outlook Board Decision Making Environment To Improve Agricultural Estimates

NASA Technical Reports Server (NTRS)

Teng, William; Shannon, Harlan; deJeu, Richard; Kempler, Steve

2012-01-01

The USDA World Agricultural Outlook Board (WAOB) is responsible for monitoring weather and climate impacts on domestic and foreign crop development. One of WAOB's primary goals is to determine the net cumulative effect of weather and climate anomalies on final crop yields. To this end, a broad array of information is consulted. The resulting agricultural weather assessments are published in the Weekly Weather and Crop Bulletin, to keep farmers, policy makers, and commercial agricultural interests informed of weather and climate impacts on agriculture. The goal of the current project is to improve WAOB estimates by integrating NASA satellite precipitation and soil moisture observations into WAOB's decision making environment. Precipitation (Level 3 gridded) is from the TRMM Multi-satellite Precipitation Analysis (TMPA). Soil moisture (Level 2 swath and Level 3 gridded) is generated by the Land Parameter Retrieval Model (LPRM) and operationally produced by the NASA Goddard Earth Sciences Data and Information Services Center (GBS DISC). A root zone soil moisture (RZSM) product is also generated, via assimilation of the Level 3 LPRM data by a land surface model (part of a related project). Data services to be available for these products include GeoTIFF, GDS (GrADS Data Server), WMS (Web Map Service), WCS (Web Coverage Service), and NASA Giovanni. Project benchmarking is based on retrospective analyses of WAOB analog year comparisons. The latter are between a given year and historical years with similar weather patterns and estimated crop yields. An analog index (AI) was developed to introduce a more rigorous, statistical approach for identifying analog years. Results thus far show that crop yield estimates derived from TMPA precipitation data are closer to measured yields than are estimates derived from surface-based precipitation measurements. Work is continuing to include LPRM surface soil moisture data and model-assimilated RZSM.

Optimizing Training Population Size and Genotyping Strategy for Genomic Prediction Using Association Study Results and Pedigree Information. A Case of Study in Advanced Wheat Breeding Lines.

PubMed

Cericola, Fabio; Jahoor, Ahmed; Orabi, Jihad; Andersen, Jeppe R; Janss, Luc L; Jensen, Just

2017-01-01

Wheat breeding programs generate a large amount of variation which cannot be completely explored because of limited phenotyping throughput. Genomic prediction (GP) has been proposed as a new tool which provides breeding values estimations without the need of phenotyping all the material produced but only a subset of it named training population (TP). However, genotyping of all the accessions under analysis is needed and, therefore, optimizing TP dimension and genotyping strategy is pivotal to implement GP in commercial breeding schemes. Here, we explored the optimum TP size and we integrated pedigree records and genome wide association studies (GWAS) results to optimize the genotyping strategy. A total of 988 advanced wheat breeding lines were genotyped with the Illumina 15K SNPs wheat chip and phenotyped across several years and locations for yield, lodging, and starch content. Cross-validation using the largest possible TP size and all the SNPs available after editing (~11k), yielded predictive abilities (rGP) ranging between 0.5-0.6. In order to explore the Training population size, rGP were computed using progressively smaller TP. These exercises showed that TP of around 700 lines were enough to yield the highest observed rGP. Moreover, rGP were calculated by randomly reducing the SNPs number. This showed that around 1K markers were enough to reach the highest observed rGP. GWAS was used to identify markers associated with the traits analyzed. A GWAS-based selection of SNPs resulted in increased rGP when compared with random selection and few hundreds SNPs were sufficient to obtain the highest observed rGP. For each of these scenarios, advantages of adding the pedigree information were shown. Our results indicate that moderate TP sizes were enough to yield high rGP and that pedigree information and GWAS results can be used to greatly optimize the genotyping strategy.

Computer optimization of cutting yield from multiple ripped boards

Treesearch

A.R. Stern; K.A. McDonald

1978-01-01

RIPYLD is a computer program that optimizes the cutting yield from multiple-ripped boards. Decisions are based on automatically collected defect information, cutting bill requirements, and sawing variables. The yield of clear cuttings from a board is calculated for every possible permutation of specified rip widths and both the maximum and minimum percent yield...

Nitrogen, phosphorus, and potassium effects on biomass yield and flavonoid content of American Skullcap (Scutellaria Lateriflora)

USDA-ARS?s Scientific Manuscript database

Information on optimum dosage of nitrogen (N), phosphorus (P) and potassium (K) fertilizer for high dry matter yield and flavonoid yield of American Skullcap is lacking. Greenhouse experiments were conducted to determine the effects of N, P and K fertilizer on biomass yield and flavonoid content of...

An energy balance approach for mapping crop waterstress and yield impacts over the Czech Republic

USDA-ARS?s Scientific Manuscript database

There is a growing demand for timely, spatially distributed information regarding crop condition and water use to inform agricultural decision making and yield forecasting efforts. Remote sensing of land-surface temperature has proven valuable for mapping evapotranspiration (ET) and crop stress from...

76 FR 12140 - Agency Information Collection Activities: Proposed Collection; Comment Request; Generic Clearance...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-04

... provides useful insights on perceptions and opinions, but are not statistical surveys that yield quantitative results that can be generalized to the population of study. This feedback will provide insights... used for quantitative information collections that are designed to yield reliably actionable results...

Final Environmental Assessment of Military Service Station Privatization at Five AETC Installations

DTIC Science & Technology

2013-10-01

distinction (Criterion C); or • Have yielded, or may likely yield, information important in prehistory or history (Criterion D). Resources less than 50...important information in history or prehistory ; thus, it does not meet the requirement of Criterion D. Building 2109 is recommended not eligible for

Metal-assisted SIMS and cluster ion bombardment for ion yield enhancement

NASA Astrophysics Data System (ADS)

Heile, A.; Lipinsky, D.; Wehbe, N.; Delcorte, A.; Bertrand, P.; Felten, A.; Houssiau, L.; Pireaux, J.-J.; De Mondt, R.; Van Vaeck, L.; Arlinghaus, H. F.

2008-12-01

In addition to structural information, a detailed knowledge of the local chemical environment proves to be of ever greater importance, for example for the development of new types of materials as well as for specific modifications of surfaces and interfaces in multiple fields of materials science or various biomedical and chemical applications. But the ongoing miniaturization and therefore reduction of the amount of material available for analysis constitute a challenge to the detection limits of analytical methods. In the case of time-of-flight secondary ion mass spectrometry (TOF-SIMS), several methods of secondary ion yield enhancement have been proposed. This paper focuses on the investigation of the effects of two of these methods, metal-assisted SIMS and polyatomic primary ion bombardment. For this purpose, thicker layers of polystyrene (PS), both pristine and metallized with different amounts of gold, were analyzed using monoatomic (Ar +, Ga +, Xe +, Bi +) and polyatomic (SF 5+, Bi 3+, C 60+) primary ions. It was found that polyatomic ions generally induce a significant increase of the secondary ion yield. On the other hand, with gold deposition, a yield enhancement can only be detected for monoatomic ion bombardment.

Nutrient database improvement project: the influence of U.S.D.A. Quality and Yield Grade on the separable components and proximate composition of raw and cooked retail cuts from the beef rib and plate.

PubMed

Martin, J N; Brooks, J C; Thompson, L D; Savell, J W; Harris, K B; May, L L; Haneklaus, A N; Schutz, J L; Belk, K E; Engle, T; Woerner, D R; Legako, J F; Luna, A M; Douglass, L W; Douglass, S E; Howe, J; Duvall, M; Patterson, K Y; Leheska, J L

2013-11-01

Beef nutrition is important to the worldwide beef industry. The objective of this study was to analyze proximate composition of eight beef rib and plate cuts to update the USDA National Nutrient Database for Standard Reference (SR). Furthermore, this study aimed to determine the influence of USDA Quality Grade on the separable components and proximate composition of the examined retail cuts. Carcasses (n=72) representing a composite of Yield Grade, Quality Grade, gender and genetic type were identified from six regions across the U.S. Beef plates and ribs (IMPS #109 and 121C and D) were collected from the selected carcasses and shipped to three university meat laboratories for storage, retail fabrication, cooking, and dissection and analysis of proximate composition. These data provide updated information regarding the nutrient content of beef and emphasize the influence of common classification systems (Yield Grade and Quality Grade) on the separable components, cooking yield, and proximate composition of retail beef cuts. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chemical mechanisms and reaction rates for the initiation of hot corrosion of IN-738

NASA Technical Reports Server (NTRS)

Fryburg, G. C.; Kohl, F. J.; Stearns, C. A.

1984-01-01

Sodium-sulfate-induced hot corrosion of preoxidized IN-738 was studied at 975 C with special emphasis placed on the processes occurring during the long induction period. Thermogravimetric tests were run for predetermined periods of time, and then one set of specimens was washed with water. Chemical analysis of the wash solutions yielded information about water soluble metal salts and residual sulfate. A second set of samples was cross sectioned dry and polished in a nonaqueous medium. Element distributions within the oxide scale were obtained from electron microprobe X-ray micrographs. Evolution of SO was monitored throughout the thermogravimetric tests. Kinetic rate studies were performed for several pertinent processes; appropriate rate constants were obtained from the following chemical reactions: Cr2O3 + 2 Na2SO4(1) + 3/2 O2 yields 2 Na2CrO4(1) + 2 SO3(g)n TiO2 + Na2SO4(1) yields Na2O(TiO2)n + SO3(g)n TiO2 + Na2CrO4(1) yields Na2O(TiO2)n + CrO3(g).

[Ecological adaptability evaluation of peanut cultivars based on biomass and nutrient accumulation].

PubMed

Wang, Xue; Cui, Shao-xiong; Sun, Zhi-mei; Mu, Guo-jun; Cui, Shun-li; Wang, Peng-chao; Liu, Li-feng

2015-07-01

To identify the good peanut cultivars with the properties of high yield, high nutrient use efficiency and wide adaptability, 19 selected peanut cultivars were planted in the low champaign area and piedmont plain area of Hebei Province. By using principal component analysis, the adaptability of these 19 cultivars was evaluated for different ecological regions through comparing their 16 main traits including biomass and nutrient parameters. According to the critical value of principal component (>1.0), the 16 biomass and nutrient characteristics were integrated into 4 principal components which accounted for 85% of the original information. The results indicated that there were obvious differences in yield and nutrient use efficiency for the peanut cultivars in different ecological regions. The 19 peanut cultivars were classified into 2 groups according to their ecological adaptability, and the cultivars from the group with wide adaptability could further be divided into 3 categories according to their yield and nutrient use efficiency. Among these cultivars, Yuhua 9719, Jihua 0212-4, Weihua 10, Yuhua 15, Puhua 28 and Jihua 10 were selected as the better peanut cultivars with the properties of high yield, high nutrient use efficiency and wide adaptability.

Colonoscopy yields fewer polyps as the day progresses despite using social influence theory to reverse the trend.

PubMed

Kaneshiro, Marc; Ho, Andrew; Chan, Michael; Cohen, Hartley; Spiegel, Brennan M R

2010-12-01

We previously reported that fewer polyps are detected by colonoscopy as the day progresses, a phenomenon that could be modified with "social influence theory" by using auditing and feedback. To measure the impact of a social influence informational poster on the relationship between time of day and colonoscopy yield. Controlled before-and-after study comparing the polyp yield and time of day relationship in a historical cohort versus a 3-month intervention period. University-based Veterans Affairs medical center. Patients undergoing outpatient screening, surveillance, or diagnostic colonoscopies. Placement of informational posters in endoscopy rooms within view of operators and nurses. The poster depicted a bar graph of the previously documented hour-by-hour decreases in polyp yield coupled with prominent text: "What Time Is It Now?" Polyp yield, including secondary end point limited to adenoma detection. We performed regression to measure the effect of start time on polyp yield. There were 477 and 301 patients in the control and intervention periods, respectively. There was a negative relationship between start time and polyp yield, including adenoma detection, for both periods (P = .001). Start time remained negatively predictive of polyp and adenoma yield after adjusting for poster exposure and confounders (P = .01). Nonrandomized study design. An informational poster did not alter the relationship between colonoscopy start time and polyp yield. This strengthens the previous finding that start time may affect polyp yield and suggests that passive use of social influence theory is inadequate to modify this effect. Shortening endoscopy shifts and active auditing with feedback may be necessary. Copyright © 2010 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Breeding Potential of Introgression Lines Developed from Interspecific Crossing between Upland Cotton (Gossypium hirsutum) and Gossypium barbadense: Heterosis, Combining Ability and Genetic Effects

PubMed Central

Li, Xingli; Pei, Wenfeng

2016-01-01

Upland cotton (Gossypium hirstum L.), which produces more than 95% of the world natural cotton fibers, has a narrow genetic base which hinders progress in cotton breeding. Introducing germplasm from exotic sources especially from another cultivated tetraploid G. barbadense L. can broaden the genetic base of Upland cotton. However, the breeding potential of introgression lines (ILs) in Upland cotton with G. barbadense germplasm integration has not been well addressed. This study involved six ILs developed from an interspecific crossing and backcrossing between Upland cotton and G. barbadense and represented one of the first studies to investigate breeding potentials of a set of ILs using a full diallel analysis. High mid-parent heterosis was detected in several hybrids between ILs and a commercial cultivar, which also out-yielded the high-yielding cultivar parent in F1, F2 and F3 generations. A further analysis indicated that general ability (GCA) variance was predominant for all the traits, while specific combining ability (SCA) variance was either non-existent or much lower than GCA. The estimated GCA effects and predicted additive effects for parents in each trait were positively correlated (at P<0.01). Furthermore, GCA and additive effects for each trait were also positively correlated among generations (at P<0.05), suggesting that F2 and F3 generations can be used as a proxy to F1 in analyzing combining abilities and estimating genetic parameters. In addition, differences between reciprocal crosses in F1 and F2 were not significant for yield, yield components and fiber quality traits. But maternal effects appeared to be present for seed oil and protein contents in F3. This study identified introgression lines as good general combiners for yield and fiber quality improvement and hybrids with high heterotic vigor in yield, and therefore provided useful information for further utilization of introgression lines in cotton breeding. PMID:26730964

Breeding Potential of Introgression Lines Developed from Interspecific Crossing between Upland Cotton (Gossypium hirsutum) and Gossypium barbadense: Heterosis, Combining Ability and Genetic Effects.

PubMed

Zhang, Jinfa; Wu, Man; Yu, Jiwen; Li, Xingli; Pei, Wenfeng

2016-01-01

Upland cotton (Gossypium hirstum L.), which produces more than 95% of the world natural cotton fibers, has a narrow genetic base which hinders progress in cotton breeding. Introducing germplasm from exotic sources especially from another cultivated tetraploid G. barbadense L. can broaden the genetic base of Upland cotton. However, the breeding potential of introgression lines (ILs) in Upland cotton with G. barbadense germplasm integration has not been well addressed. This study involved six ILs developed from an interspecific crossing and backcrossing between Upland cotton and G. barbadense and represented one of the first studies to investigate breeding potentials of a set of ILs using a full diallel analysis. High mid-parent heterosis was detected in several hybrids between ILs and a commercial cultivar, which also out-yielded the high-yielding cultivar parent in F1, F2 and F3 generations. A further analysis indicated that general ability (GCA) variance was predominant for all the traits, while specific combining ability (SCA) variance was either non-existent or much lower than GCA. The estimated GCA effects and predicted additive effects for parents in each trait were positively correlated (at P<0.01). Furthermore, GCA and additive effects for each trait were also positively correlated among generations (at P<0.05), suggesting that F2 and F3 generations can be used as a proxy to F1 in analyzing combining abilities and estimating genetic parameters. In addition, differences between reciprocal crosses in F1 and F2 were not significant for yield, yield components and fiber quality traits. But maternal effects appeared to be present for seed oil and protein contents in F3. This study identified introgression lines as good general combiners for yield and fiber quality improvement and hybrids with high heterotic vigor in yield, and therefore provided useful information for further utilization of introgression lines in cotton breeding.

Information filtering based on corrected redundancy-eliminating mass diffusion.

PubMed

Zhu, Xuzhen; Yang, Yujie; Chen, Guilin; Medo, Matus; Tian, Hui; Cai, Shi-Min

2017-01-01

Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects' attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is based on a spreading process on the network. Extensive experiments on three benchmark data sets-Movilens, Netflix and Amazon-show that when used in recommendation, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices.

[Development of medical supplies management system].

PubMed

Zhong, Jianping; Shen, Beijun; Zhu, Huili

2012-11-01

This paper adopts advanced information technology to manage medical supplies, in order to improve the medical supplies management level and reduce material cost. It develops a Medical Supplies Management System with B/S and C/S mixed structure, optimizing material management process, building large equipment performance evaluation model, providing interface solution with HIS, and realizing real-time information briefing of high value material's consumption. The medical materials are managed during its full life-cycle. The material consumption of the clinical departments is monitored real-timely. Through the closed-loop management with pre-event budget, mid-event control and after-event analysis, it realizes the final purpose of management yielding benefit.

Prosocial coping and substance use during pregnancy.

PubMed

Blechman, E A; Lowell, E S; Garrett, J

1999-01-01

In structured interviews of pregnant inner-city residents, 38 substance users reported more current liking of drugs and polysubstance use, disengagement coping, depressive symptoms, negative affect, and antisocial behavior than did 45 nonusers. During videotaped interviews, trained observers coded less warmth and less prosocial information exchange (e.g., self-disclosure, question asking) among users. Factor analysis of measures of coping and its concomitants yielded a three-factor (prosocial, antisocial, asocial) solution, with asocial and antisocial coping predominating among substance users. These results suggest that coping has emotional, social, and cognitive elements. This study is the first to demonstrate an association between a substance-using lifestyle and limited prosocial information exchange.

An ideal observer analysis of visual working memory.

PubMed

Sims, Chris R; Jacobs, Robert A; Knill, David C

2012-10-01

Limits in visual working memory (VWM) strongly constrain human performance across many tasks. However, the nature of these limits is not well understood. In this article we develop an ideal observer analysis of human VWM by deriving the expected behavior of an optimally performing but limited-capacity memory system. This analysis is framed around rate-distortion theory, a branch of information theory that provides optimal bounds on the accuracy of information transmission subject to a fixed information capacity. The result of the ideal observer analysis is a theoretical framework that provides a task-independent and quantitative definition of visual memory capacity and yields novel predictions regarding human performance. These predictions are subsequently evaluated and confirmed in 2 empirical studies. Further, the framework is general enough to allow the specification and testing of alternative models of visual memory (e.g., how capacity is distributed across multiple items). We demonstrate that a simple model developed on the basis of the ideal observer analysis-one that allows variability in the number of stored memory representations but does not assume the presence of a fixed item limit-provides an excellent account of the empirical data and further offers a principled reinterpretation of existing models of VWM. PsycINFO Database Record (c) 2012 APA, all rights reserved.

A compendium of forest growth and yield simulators for the Pacific coast states

Treesearch

Martin W. Ritchie

1999-01-01

This manuscript provides information needed for the user to access current information about forest growth and yield simulators. Ultimately, the best source of information for any simulator is the user’s guide and the sage advice of those who built the simulator. In some instances, these people are easy to find and are willing to provide all the support for the program...

Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

NASA Astrophysics Data System (ADS)

Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed to evaluate the influence of each parameter mentioned above on the winter wheat yield formation. Finally, six parameters that sensitivity index more than 0.1 as sensitivity factors were chose, which are TSUM1, SLATB1, SLATB2, SPAN, EFFTB3 and TMPF4. To other parameters, we confirmed them via practical measurement and calculation, available literature or WOFOST default. Eventually, we completed the regulation of WOFOST parameters. (3) Look-up table algorithm was used to realize single-point yield estimation through the assimilation of the WOFOST model and the retrieval LAI. This simulation achieved a high accuracy which perfectly meet the purpose of assimilation (R2=0.941 and RMSE=194.58kg/hm2). In this paper, the optimum value of sensitivity parameters were confirmed and the estimation of single-point yield were finished. Key words: yield estimation of winter wheat, LAI, WOFOST crop growth model, assimilation

Stem cell collection in unmanipulated HLA-haploidentical/mismatched related transplantation with combined granulocyte-colony stimulating factor-mobilised blood and bone marrow for patients with haematologic malignancies: the impact of donor characteristics and procedural settings.

PubMed

Zhang, C; Chen, X-H; Zhang, X; Gao, L; Gao, L; Kong, P-Y; Peng, X-G; Sun, A-H; Gong, Y; Zeng, D-F; Wang, Q-Y

2010-06-01

Unmanipulated haploidentical/mismatched related transplantation with combined granulocyte-colony stimulating factor-mobilised peripheral blood stem cells (G-PBSCs) and granulocyte-colony stimulating factor-mobilised bone marrow (G-BM) has been developed as an alternative transplantation strategy for patients with haematologic malignancies. However, little information is available about the factors predicting the outcome of peripheral blood stem cell (PBSC) collection and bone marrow (BM) harvest in this transplantation. The effects of donor characteristics and procedure factors on CD34(+) cell yield were investigated. A total of 104 related healthy donors received granulocyte-colony stimulating factor (G-CSF) followed by PBSC collection and BM harvest. Male donors had significantly higher yields compared with female donors. In multiple regression analysis for peripheral blood collection, age and flow rate were negatively correlated with cell yield, whereas body mass index, pre-aphaeresis white blood cell (WBC) and circulating immature cell (CIC) counts were positively correlated with cell yields. For BM harvest, age was negatively correlated with cell yields, whereas pre-BM collection CIC counts were positively correlated with cell yield. All donors achieved the final product of >or=6 x10(6) kg(-1) recipient body weight. This transplantation strategy has been shown to be a feasible approach with acceptable outcomes in stem cell collection for patients who received HLA-haploidentical/mismatched transplantation with combined G-PBSCs and G-BM. In donors with multiple high-risk characteristics for poor aphaeresis CD34(+) cell yield, BM was an alternative source.

Impacts of 1.5 versus 2.0 °C on cereal yields in the West African Sudan Savanna

NASA Astrophysics Data System (ADS)

Faye, Babacar; Webber, Heidi; Naab, Jesse B.; MacCarthy, Dilys S.; Adam, Myriam; Ewert, Frank; Lamers, John P. A.; Schleussner, Carl-Friedrich; Ruane, Alex; Gessner, Ursula; Hoogenboom, Gerrit; Boote, Ken; Shelia, Vakhtang; Saeed, Fahad; Wisser, Dominik; Hadir, Sofia; Laux, Patrick; Gaiser, Thomas

2018-03-01

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security.

Identification and validation of QTL for grain yield and plant water status under contrasting water treatments in fall-sown spring wheats.

PubMed

Zhang, Junli; Gizaw, Shiferaw Abate; Bossolini, Eligio; Hegarty, Joshua; Howell, Tyson; Carter, Arron H; Akhunov, Eduard; Dubcovsky, Jorge

2018-05-16

Chromosome regions affecting grain yield, grain yield components and plant water status were identified and validated in fall-sown spring wheats grown under full and limited irrigation. Increases in wheat production are required to feed a growing human population. To understand the genetic basis of grain yield in fall-sown spring wheats, we performed a genome-wide association study (GWAS) including 262 photoperiod-insensitive spring wheat accessions grown under full and limited irrigation treatments. Analysis of molecular variance showed that 4.1% of the total variation in the panel was partitioned among accessions originally developed under fall-sowing or spring-sowing conditions, 11.7% among breeding programs within sowing times and 84.2% among accessions within breeding programs. We first identified QTL for grain yield, yield components and plant water status that were significant in at least three environments in the GWAS, and then selected those that were also significant in at least two environments in a panel of eight biparental mapping populations. We identified and validated 14 QTL for grain yield, 15 for number of spikelets per spike, one for kernel number per spike, 11 for kernel weight and 9 for water status, which were not associated with differences in plant height or heading date. We detected significant correlations among traits and colocated QTL that were consistent with those correlations. Among those, grain yield and plant water status were negatively correlated in all environments, and six QTL for these traits were colocated or tightly linked (< 1 cM). QTL identified and validated in this study provide useful information for the improvement of fall-sown spring wheats under full and limited irrigation.

Methods to isolate extracellular vesicles for diagnosis

NASA Astrophysics Data System (ADS)

Kang, Hyejin; Kim, Jiyoon; Park, Jaesung

2017-12-01

Extracellular vesicles (EVs) are small membrane-bound bodies that are released into extracellular space by diverse cells, and are found in body fluids like blood, urine and saliva. EVs contain RNA, DNA and proteins, which can be biomarkers for diagnosis. EVs can be obtained by minimally-invasive biopsy, so they are useful in disease diagnosis. High yield and purity contribute to precise diagnosis of disease, but damaged EVs and impurities can cause confu sed results. However, EV isolation methods have different yields and purities. Furthermore, the isolation method that is most suitable to maximize EV recovery efficiency depends on the experimental conditions. This review focuses on merits and demerits of several types of EV isolation methods, and provides examples of how to diagnose disease by exploiting information obtained by analysis of EVs.

Reducing the Requirements and Cost of Astronomical Telescopes

NASA Technical Reports Server (NTRS)

Smith, W. Scott; Whitakter, Ann F. (Technical Monitor)

2002-01-01

Limits on astronomical telescope apertures are being rapidly approached. These limits result from logistics, increasing complexity, and finally budgetary constraints. In an historical perspective, great strides have been made in the area of aperture, adaptive optics, wavefront sensors, detectors, stellar interferometers and image reconstruction. What will be the next advances? Emerging data analysis techniques based on communication theory holds the promise of yielding more information from observational data based on significant computer post-processing. This paper explores some of the current telescope limitations and ponders the possibilities increasing the yield of scientific data based on the migration computer post-processing techniques to higher dimensions. Some of these processes hold the promise of reducing the requirements on the basic telescope hardware making the next generation of instruments more affordable.

Hyperspectral imaging to investigate the distribution of organic matter and iron down the soil profile

NASA Astrophysics Data System (ADS)

Hobley, Eleanor; Kriegs, Stefanie; Steffens, Markus

2017-04-01

Obtaining reliable and accurate data regarding the spatial distribution of different soil components is difficult due to issues related with sampling scale and resolution on the one hand and laboratory analysis on the other. When investigating the chemical composition of soil, studies frequently limit themselves to two dimensional characterisations, e.g. spatial variability near the surface or depth distribution down the profile, but rarely combine both approaches due to limitations to sampling and analytical capacities. Furthermore, when assessing depth distributions, samples are taken according to horizon or depth increments, resulting in a mixed sample across the sampling depth. Whilst this facilitates mean content estimation per depth increment and therefore reduces analytical costs, the sample information content with regards to heterogeneity within the profile is lost. Hyperspectral imaging can overcome these sampling limitations, yielding high resolution spectral data of down the soil profile, greatly enhancing the information content of the samples. This can then be used to augment horizontal spatial characterisation of a site, yielding three dimensional information into the distribution of spectral characteristics across a site and down the profile. Soil spectral characteristics are associated with specific chemical components of soil, such as soil organic matter or iron contents. By correlating the content of these soil components with their spectral behaviour, high resolution multi-dimensional analysis of soil chemical composition can be obtained. Here we present a hyperspectral approach to the characterisation of soil organic matter and iron down different soil profiles, outlining advantages and issues associated with the methodology.

Vineyard zonal management for grape quality assessment by combining airborne remote sensed imagery and soil sensors

NASA Astrophysics Data System (ADS)

Bonilla, I.; Martínez De Toda, F.; Martínez-Casasnovas, J. A.

2014-10-01

Vineyard variability within the fields is well known by grape growers, producing different plant responses and fruit characteristics. Many technologies have been developed in last recent decades in order to assess this spatial variability, including remote sensing and soil sensors. In this paper we study the possibility of creating a stable classification system that better provides useful information for the grower, especially in terms of grape batch quality sorting. The work was carried out during 4 years in a rain-fed Tempranillo vineyard located in Rioja (Spain). NDVI was extracted from airborne imagery, and soil conductivity (EC) data was acquired by an EM38 sensor. Fifty-four vines were sampled at véraison for vegetative parameters and before harvest for yield and grape analysis. An Isocluster unsupervised classification in two classes was performed in 5 different ways, combining NDVI maps individually, collectively and combined with EC. The target vines were assigned in different zones depending on the clustering combination. Analysis of variance was performed in order to verify the ability of the combinations to provide the most accurate information. All combinations showed a similar behaviour concerning vegetative parameters. Yield parameters classify better by the EC-based clustering, whilst maturity grape parameters seemed to give more accuracy by combining all NDVIs and EC. Quality grape parameters (anthocyanins and phenolics), presented similar results for all combinations except for the NDVI map of the individual year, where the results were poorer. This results reveal that stable parameters (EC or/and NDVI all-together) clustering outcomes in better information for a vineyard zonal management strategy.

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

Takahashi, Koh; Umeda, Hideyuki; Yoshida, Takashi, E-mail: ktakahashi@astron.s.u-tokyo.ac.jp

We perform a stellar evolution simulation of first stars and calculate stellar yields from the first supernovae. The initial masses are taken from 12 to 140 M {sub ☉} to cover the whole range of core-collapse supernova progenitors, and stellar rotation is included, which results in efficient internal mixing. A weak explosion is assumed in supernova yield calculations, thus only outer distributed matter, which is not affected by the explosive nucleosynthesis, is ejected in the models. We show that the initial mass and the rotation affect the explosion yield. All the weak explosion models have abundances of [C/O] larger thanmore » unity. Stellar yields from massive progenitors of >40-60 M {sub ☉} show enhancement of Mg and Si. Rotating models yield abundant Na and Al, and Ca is synthesized in nonrotating heavy massive models of >80 M {sub ☉}. We fit the stellar yields to the three most iron-deficient stars and constrain the initial parameters of the mother progenitor stars. The abundance pattern in SMSS 0313–6708 is well explained by 50-80 M {sub ☉} nonrotating models, rotating 30-40 M {sub ☉} models well fit the abundance of HE 0107-5240, and both nonrotating and rotating 15-40 M {sub ☉} models explain HE 1327-2326. The presented analysis will be applicable to other carbon-enhanced hyper-metal-poor stars observed in the future. The abundance analyses will give valuable information about the characteristics of the first stars.« less

Accurate FRET Measurements within Single Diffusing Biomolecules Using Alternating-Laser Excitation

PubMed Central

Lee, Nam Ki; Kapanidis, Achillefs N.; Wang, You; Michalet, Xavier; Mukhopadhyay, Jayanta; Ebright, Richard H.; Weiss, Shimon

2005-01-01

Fluorescence resonance energy transfer (FRET) between a donor (D) and an acceptor (A) at the single-molecule level currently provides qualitative information about distance, and quantitative information about kinetics of distance changes. Here, we used the sorting ability of confocal microscopy equipped with alternating-laser excitation (ALEX) to measure accurate FRET efficiencies and distances from single molecules, using corrections that account for cross-talk terms that contaminate the FRET-induced signal, and for differences in the detection efficiency and quantum yield of the probes. ALEX yields accurate FRET independent of instrumental factors, such as excitation intensity or detector alignment. Using DNA fragments, we showed that ALEX-based distances agree well with predictions from a cylindrical model of DNA; ALEX-based distances fit better to theory than distances obtained at the ensemble level. Distance measurements within transcription complexes agreed well with ensemble-FRET measurements, and with structural models based on ensemble-FRET and x-ray crystallography. ALEX can benefit structural analysis of biomolecules, especially when such molecules are inaccessible to conventional structural methods due to heterogeneity or transient nature. PMID:15653725

NEANDC specialists meeting on yields and decay data of fission product nuclides

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

Chrien, R.E.; Burrows, T.W.

Separate abstracts were prepared for the 29 papers presented. Workshop reports on decay heat, fission yields, beta- and gamma-ray spectroscopy, and delayed neutrons are included. An appendix contains a survey of the most recent compilations and evaluations containing fission product yield, fission product decay data, and delayed neutron yield information. (WHK)

Spatial and Temporal Uncertainty of Crop Yield Aggregations

NASA Technical Reports Server (NTRS)

Porwollik, Vera; Mueller, Christoph; Elliott, Joshua; Chryssanthacopoulos, James; Iizumi, Toshichika; Ray, Deepak K.; Ruane, Alex C.; Arneth, Almut; Balkovic, Juraj; Ciais, Philippe;

Protein Dynamics from NMR: The Slowly Relaxing Local Structure Analysis Compared with Model-Free Analysis

PubMed Central

Meirovitch, Eva; Shapiro, Yury E.; Polimeno, Antonino; Freed, Jack H.

2009-01-01

15N-1H spin relaxation is a powerful method for deriving information on protein dynamics. The traditional method of data analysis is model-free (MF), where the global and local N-H motions are independent and the local geometry is simplified. The common MF analysis consists of fitting single-field data. The results are typically field-dependent, and multi-field data cannot be fit with standard fitting schemes. Cases where known functional dynamics has not been detected by MF were identified by us and others. Recently we applied to spin relaxation in proteins the Slowly Relaxing Local Structure (SRLS) approach which accounts rigorously for mode-mixing and general features of local geometry. SRLS was shown to yield MF in appropriate asymptotic limits. We found that the experimental spectral density corresponds quite well to the SRLS spectral density. The MF formulae are often used outside of their validity ranges, allowing small data sets to be force-fitted with good statistics but inaccurate best-fit parameters. This paper focuses on the mechanism of force-fitting and its implications. It is shown that MF force-fits the experimental data because mode-mixing, the rhombic symmetry of the local ordering and general features of local geometry are not accounted for. Combined multi-field multi-temperature data analyzed by MF may lead to the detection of incorrect phenomena, while conformational entropy derived from MF order parameters may be highly inaccurate. On the other hand, fitting to more appropriate models can yield consistent physically insightful information. This requires that the complexity of the theoretical spectral densities matches the integrity of the experimental data. As shown herein, the SRLS densities comply with this requirement. PMID:16821820

Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980–2010

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

Leng, Guoyong

Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (RGST_CY) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in associationmore » with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K~-3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in RGST_CY are mainly observed in Midwest Corn Belt and central High Plains, and are well reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period.« less

Evidence for a weakening strength of temperature-corn yield relation in the United States during 1980-2010.

PubMed

Leng, Guoyong

2017-12-15

Temperature is known to be correlated with crop yields, causing reduction of crop yield with climate warming without adaptations or CO 2 fertilization effects. The historical temperature-crop yield relation has often been used for informing future changes. This relationship, however, may change over time following alternations in other environmental factors. Results show that the strength of the relationship between the interannual variability of growing season temperature and corn yield (R GST_CY ) has declined in the United States between 1980 and 2010 with a loss in the statistical significance. The regression slope which represents the anomalies in corn yield that occur in association with 1 degree temperature anomaly has decreased significantly from -6.9%/K of the first half period to -2.4%/K--3.5%/K of the second half period. This implies that projected corn yield reduction will be overestimated by a fact of 2 in a given warming scenario, if the corn-temperature relation is derived from the earlier historical period. Changes in R GST_CY are mainly observed in Midwest Corn Belt and central High Plains, but are partly reproduced by 11 process-based crop models. In Midwest rain-fed systems, the decrease of negative temperature effects coincides with an increase in water availability by precipitation. In irrigated areas where water stress is minimized, the decline of beneficial temperature effects is significantly related to the increase in extreme hot days. The results indicate that an extrapolation of historical yield response to temperature may bias the assessment of agriculture vulnerability to climate change. Efforts to reduce climate impacts on agriculture should pay attention not only to climate change, but also to changes in climate-crop yield relations. There are some caveats that should be acknowledged as the analysis is restricted to the changes in the linear relation between growing season mean temperature and corn yield for the specific study period. Copyright © 2017 Elsevier B.V. All rights reserved.

Non-destructive determination of floral staging in cereals using X-ray micro computed tomography (µCT).

PubMed

Tracy, Saoirse R; Gómez, José Fernández; Sturrock, Craig J; Wilson, Zoe A; Ferguson, Alison C

2017-01-01

Accurate floral staging is required to aid research into pollen and flower development, in particular male development. Pollen development is highly sensitive to stress and is critical for crop yields. Research into male development under environmental change is important to help target increased yields. This is hindered in monocots as the flower develops internally in the pseudostem. Floral staging studies therefore typically rely on destructive analysis, such as removal from the plant, fixation, staining and sectioning. This time-consuming analysis therefore prevents follow up studies and analysis past the point of the floral staging. This study focuses on using X-ray µCT scanning to allow quick and detailed non-destructive internal 3D phenotypic information to allow accurate staging of Arabidopsis thaliana L. and Barley ( Hordeum vulgare L.) flowers. X-ray µCT has previously relied on fixation methods for above ground tissue, therefore two contrast agents (Lugol's iodine and Bismuth) were observed in Arabidopsis and Barley in planta to circumvent this step. 3D models and 2D slices were generated from the X-ray µCT images providing insightful information normally only available through destructive time-consuming processes such as sectioning and microscopy. Barley growth and development was also monitored over three weeks by X-ray µCT to observe flower development in situ. By measuring spike size in the developing tillers accurate non-destructive staging at the flower and anther stages could be performed; this staging was confirmed using traditional destructive microscopic analysis. The use of X-ray micro computed tomography (µCT) scanning of living plant tissue offers immense benefits for plant phenotyping, for successive developmental measurements and for accurate developmental timing for scientific measurements. Nevertheless, X-ray µCT remains underused in plant sciences, especially in above-ground organs, despite its unique potential in delivering detailed non-destructive internal 3D phenotypic information. This work represents a novel application of X-ray µCT that could enhance research undertaken in monocot species to enable effective non-destructive staging and developmental analysis for molecular genetic studies and to determine effects of stresses at particular growth stages.

Novel methods for parameter-based analysis of myocardial tissue in MR images

NASA Astrophysics Data System (ADS)

Hennemuth, A.; Behrens, S.; Kuehnel, C.; Oeltze, S.; Konrad, O.; Peitgen, H.-O.

2007-03-01

The analysis of myocardial tissue with contrast-enhanced MR yields multiple parameters, which can be used to classify the examined tissue. Perfusion images are often distorted by motion, while late enhancement images are acquired with a different size and resolution. Therefore, it is common to reduce the analysis to a visual inspection, or to the examination of parameters related to the 17-segment-model proposed by the American Heart Association (AHA). As this simplification comes along with a considerable loss of information, our purpose is to provide methods for a more accurate analysis regarding topological and functional tissue features. In order to achieve this, we implemented registration methods for the motion correction of the perfusion sequence and the matching of the late enhancement information onto the perfusion image and vice versa. For the motion corrected perfusion sequence, vector images containing the voxel enhancement curves' semi-quantitative parameters are derived. The resulting vector images are combined with the late enhancement information and form the basis for the tissue examination. For the exploration of data we propose different modes: the inspection of the enhancement curves and parameter distribution in areas automatically segmented using the late enhancement information, the inspection of regions segmented in parameter space by user defined threshold intervals and the topological comparison of regions segmented with different settings. Results showed a more accurate detection of distorted regions in comparison to the AHA-model-based evaluation.

Comprehension and Analysis of Information in Text. III. Sentence Construction, Evaluation and Use. Addendum.

DTIC Science & Technology

1980-07-01

companies. 6) Dividends --past and anticipated payments to stockholders. Next, we selected 211 sentences from various sources of financial data, such as...share can be expected in the near future, the payout ratio may decline. 232 Company dividend yield is normal for the industry. 233 Directors recently...Disappointing performance of the new series 𔃺’ printers put ECTEX in the red. 24 DIVIDENDS 333 Dividend payout has grown appreciably in the past 2

Analysis of CSIRT/SOC Incidents and Continuous Monitoring of Threats

NASA Technical Reports Server (NTRS)

Wang, John; Ishisoko, Katsutoshi C.

2012-01-01

Security Operations Centers (SOC) contain a wealth of data which, if properly classified and tagged upfront, can yield a wealth of real-time information about your organizations IT Security posture, risks, and threats. These include answers to relevant and actionable questions such as: What are our biggest threats? Who is attacking us and what do they want? What controls are working or not working? How effective was the new technology we just implemented? What is our ROI?

Separable Bilayer Microfiltration Device for Label-Free Enrichment of Viable Circulating Tumor Cells.

PubMed

Hao, Sijie; Nisic, Merisa; He, Hongzhang; Tai, Yu-Chong; Zheng, Si-Yang

2017-01-01

Analysis of rare circulating tumor cells enriched from metastatic cancer patients yields critical information on disease progression, therapy response, and the mechanism of cancer metastasis. Here we describe in detail a label-free enrichment process of circulating tumor cells based on its unique physical properties (size and deformability). Viable circulating tumor cells can be successfully enriched and analyzed, or easily released for further characterization due to the novel separable two-layer design.

Semantic classification of business images

NASA Astrophysics Data System (ADS)

Erol, Berna; Hull, Jonathan J.

2006-01-01

Digital cameras are becoming increasingly common for capturing information in business settings. In this paper, we describe a novel method for classifying images into the following semantic classes: document, whiteboard, business card, slide, and regular images. Our method is based on combining low-level image features, such as text color, layout, and handwriting features with high-level OCR output analysis. Several Support Vector Machine Classifiers are combined for multi-class classification of input images. The system yields 95% accuracy in classification.

Covariance Matrix Evaluations for Independent Mass Fission Yields

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

Terranova, N., E-mail: nicholas.terranova@unibo.it; Serot, O.; Archier, P.

2015-01-15

Recent needs for more accurate fission product yields include covariance information to allow improved uncertainty estimations of the parameters used by design codes. The aim of this work is to investigate the possibility to generate more reliable and complete uncertainty information on independent mass fission yields. Mass yields covariances are estimated through a convolution between the multi-Gaussian empirical model based on Brosa's fission modes, which describe the pre-neutron mass yields, and the average prompt neutron multiplicity curve. The covariance generation task has been approached using the Bayesian generalized least squared method through the CONRAD code. Preliminary results on mass yieldsmore » variance-covariance matrix will be presented and discussed from physical grounds in the case of {sup 235}U(n{sub th}, f) and {sup 239}Pu(n{sub th}, f) reactions.« less

Influence of management and environment on Australian wheat: information for sustainable intensification and closing yield gaps

NASA Astrophysics Data System (ADS)

Bryan, B. A.; King, D.; Zhao, G.

2014-04-01

In the future, agriculture will need to produce more, from less land, more sustainably. But currently, in many places, actual crop yields are below those attainable. We quantified the ability for agricultural management to increase wheat yields across 179 Mha of potentially arable land in Australia. Using the Agricultural Production Systems Simulator (APSIM), we simulated the impact on wheat yield of 225 fertilization and residue management scenarios at a high spatial, temporal, and agronomic resolution from 1900 to 2010. The influence of management and environmental variables on wheat yield was then assessed using Spearman’s non-parametric correlation test with bootstrapping. While residue management showed little correlation, fertilization strongly increased wheat yield up to around 100 kg N ha-1 yr-1. However, this effect was highly dependent on the key environment variables of rainfall, temperature, and soil water holding capacity. The influence of fertilization on yield was stronger in cooler, wetter climates, and in soils with greater water holding capacity. We conclude that the effectiveness of management intensification to increase wheat yield is highly dependent upon local climate and soil conditions. We provide context-specific information on the yield benefits of fertilization to support adaptive agronomic decision-making and contribute to the closure of yield gaps. We also suggest that future assessments consider the economic and environmental sustainability of management intensification for closing yield gaps.

Relationships among ultrasonic and mechanical properties of cancellous bone in human calcaneus in vitro.

PubMed

Wear, Keith A; Nagaraja, Srinidhi; Dreher, Maureen L; Sadoughi, Saghi; Zhu, Shan; Keaveny, Tony M

2017-10-01

Clinical bone sonometers applied at the calcaneus measure broadband ultrasound attenuation and speed of sound. However, the relation of ultrasound measurements to bone strength is not well-characterized. Addressing this issue, we assessed the extent to which ultrasonic measurements convey in vitro mechanical properties in 25 human calcaneal cancellous bone specimens (approximately 2×4×2cm). Normalized broadband ultrasound attenuation, speed of sound, and broadband ultrasound backscatter were measured with 500kHz transducers. To assess mechanical properties, non-linear finite element analysis, based on micro-computed tomography images (34-micron cubic voxel), was used to estimate apparent elastic modulus, overall specimen stiffness, and apparent yield stress, with models typically having approximately 25-30 million elements. We found that ultrasound parameters were correlated with mechanical properties with R=0.70-0.82 (p<0.001). Multiple regression analysis indicated that ultrasound measurements provide additional information regarding mechanical properties beyond that provided by bone quantity alone (p≤0.05). Adding ultrasound variables to linear regression models based on bone quantity improved adjusted squared correlation coefficients from 0.65 to 0.77 (stiffness), 0.76 to 0.81 (apparent modulus), and 0.67 to 0.73 (yield stress). These results indicate that ultrasound can provide complementary (to bone quantity) information regarding mechanical behavior of cancellous bone. Published by Elsevier Inc.

Static time-of-flight secondary ion mass spectrometry analysis of microelectronics related substrates using a polyatomic ion source

NASA Astrophysics Data System (ADS)

Ravanel, X.; Trouiller, C.; Juhel, M.; Wyon, C.; Kwakman, L. F. Tz.; Léonard, D.

2008-12-01

Recent time-of-flight secondary ion mass spectrometry studies using primary ion cluster sources such as Au n+, SF 5+, Bi n+ or C 60+ have shown the great advantages in terms of secondary ion yield enhancement and ion formation efficiency of polyatomic ion sources as compared to monoatomic ion sources like the commonly used Ga +. In this work, the effective gains provided by such a source in the static ToF-SIMS analysis of microelectronics devices were investigated. Firstly, the influence of the number of atoms in the primary cluster ion on secondary ion formation was studied for physically adsorbed di-isononyl phthalate (DNP) (plasticizer) and perfluoropolyether (PFPE). A drastic increase in secondary ion formation efficiency and a much lower detection limit were observed when using a polyatomic primary ion. Moreover, the yield of the higher mass species was much enhanced indicating a lower degree of fragmentation that can be explained by the fact that the primary ion energy is spread out more widely, or that there is a lower energy per incoming ion. Secondly, the influence of the number of Bi atoms in the Bi n primary ion on the information depth was studied using reference thermally grown silicon oxide samples. The information depth provided by a Bi n cluster was shown to be lowered when the number of atoms in the aggregate was increased.

A numerical investigation of the scale-up effects on flow, heat transfer, and kinetics processes of FCC units.

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

Chang, S. L.

1998-08-25

Fluid Catalytic Cracking (FCC) technology is the most important process used by the refinery industry to convert crude oil to valuable lighter products such as gasoline. Process development is generally very time consuming especially when a small pilot unit is being scaled-up to a large commercial unit because of the lack of information to aide in the design of scaled-up units. Such information can now be obtained by analysis based on the pilot scale measurements and computer simulation that includes controlling physics of the FCC system. A Computational fluid dynamic (CFD) code, ICRKFLO, has been developed at Argonne National Laboratorymore » (ANL) and has been successfully applied to the simulation of catalytic petroleum cracking risers. It employs hybrid hydrodynamic-chemical kinetic coupling techniques, enabling the analysis of an FCC unit with complex chemical reaction sets containing tens or hundreds of subspecies. The code has been continuously validated based on pilot-scale experimental data. It is now being used to investigate the effects of scaled-up FCC units. Among FCC operating conditions, the feed injection conditions are found to have a strong impact on the product yields of scaled-up FCC units. The feed injection conditions appear to affect flow and heat transfer patterns and the interaction of hydrodynamics and cracking kinetics causes the product yields to change accordingly.« less

Molecular and systems approaches towards drought-tolerant canola crops.

PubMed

Zhu, Mengmeng; Monroe, J Grey; Suhail, Yasir; Villiers, Florent; Mullen, Jack; Pater, Dianne; Hauser, Felix; Jeon, Byeong Wook; Bader, Joel S; Kwak, June M; Schroeder, Julian I; McKay, John K; Assmann, Sarah M

2016-06-01

1169 I. 1170 II. 1170 III. 1172 IV. 1176 V. 1181 VI. 1182 1183 References 1183 SUMMARY: Modern agriculture is facing multiple challenges including the necessity for a substantial increase in production to meet the needs of a burgeoning human population. Water shortage is a deleterious consequence of both population growth and climate change and is one of the most severe factors limiting global crop productivity. Brassica species, particularly canola varieties, are cultivated worldwide for edible oil, animal feed, and biodiesel, and suffer dramatic yield loss upon drought stress. The recent release of the Brassica napus genome supplies essential genetic information to facilitate identification of drought-related genes and provides new information for agricultural improvement in this species. Here we summarize current knowledge regarding drought responses of canola, including physiological and -omics effects of drought. We further discuss knowledge gained through translational biology based on discoveries in the closely related reference species Arabidopsis thaliana and through genetic strategies such as genome-wide association studies and analysis of natural variation. Knowledge of drought tolerance/resistance responses in canola together with research outcomes arising from new technologies and methodologies will inform novel strategies for improvement of drought tolerance and yield in this and other important crop species. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Computing wheat nitrogen requirements from grain yield and protein maps

USDA-ARS?s Scientific Manuscript database

Optical protein sensors and mass-flow yield monitors provide the opportunity to continuously measure grain quality and quantity during harvesting. This chapter illustrates how yield monitor and grain protein measurements may provide useful postharvest information for evaluating water or nitrogen (N)...

Computing wheat nitrogen requirements from grain yield and protein maps

USDA-ARS?s Scientific Manuscript database

Optical protein sensors and mass-flow yield monitors provide the opportunity to continuously measure grain quality and quantity during harvesting. This chapter illustrates how yield monitor and grain protein measurements may provide useful post-harvest information for evaluating water or nitrogen (...

Hyperspectral imagery for mapping crop yield for precision agriculture

USDA-ARS?s Scientific Manuscript database

Crop yield is perhaps the most important piece of information for crop management in precision agriculture. It integrates the effects of various spatial variables such as soil properties, topographic attributes, tillage, plant population, fertilization, irrigation, and pest infestations. A yield map...

Water relation, leaf gas exchange and chlorophyll a fluorescence imaging of soybean leaves infected with Colletotrichum truncatum.

PubMed

Dias, Carla Silva; Araujo, Leonardo; Alves Chaves, Joicy Aparecida; DaMatta, Fábio M; Rodrigues, Fabrício A

2018-06-01

Considering the potential of anthracnose to decrease soybean yield and the need to gain more information regarding its effect on soybean physiology, the present study performed an in-depth analysis of the photosynthetic performance of soybean leaflets challenged with Colletotrichum truncatum by combining chlorophyll a fluorescence images with gas-exchange measurements and photosynthetic pigment pools. There were no significant differences between non-inoculated and inoculated plants in leaf water potential, apparent hydraulic conductance, net CO 2 assimilation rate, stomatal conductance to water vapor and transpiration rate. For internal CO 2 concentration, significant difference between non-inoculated and inoculated plants occurred only at 36 h after inoculation. Reductions in the values of the chlorophyll a fluorescence parameters [initial fluorescence (F 0 ), maximal fluorescence (F m ), maximal photosystem II quantum yield (F v /F m ), quantum yield of regulated energy dissipation (Y(NPQ))] and increases in effective PS II quantum yield (Y(II)), quantum yield of non-regulated energy dissipation Y(NO) and photochemical quenching coefficient (q P ) were noticed on the necrotic vein tissue in contrast to the surrounding leaf tissue. It appears that the impact of the infection by C. truncatum on the photosynthetic performance of the leaflets was minimal considering the preference of the fungus to colonize the veins. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Operation of the yield estimation subsystem

NASA Technical Reports Server (NTRS)

Mccrary, D. G.; Rogers, J. L.; Hill, J. D. (Principal Investigator)

1979-01-01

The organization and products of the yield estimation subsystem (YES) are described with particular emphasis on meteorological data acquisition, yield estimation, crop calendars, weekly weather summaries, and project reports. During the three phases of LACIE, YES demonstrated that it is possible to use the flow of global meteorological data and provide valuable information regarding global wheat production. It was able to establish a capability to collect, in a timely manner, detailed weather data from all regions of the world, and to evaluate and convert that data into information appropriate to the project's needs.

Otolith shape analysis for stock discrimination of two Collichthys genus croaker (Pieces: Sciaenidae,) from the northern Chinese coast

NASA Astrophysics Data System (ADS)

Zhao, Bo; Liu, Jinhu; Song, Junjie; Cao, Liang; Dou, Shuozeng

2017-08-01

The otolith morphology of two croaker species (Collichthys lucidus and Collichthys niveatus) from three areas (Liaodong Bay, LD; Huanghe (Yellow) River estuary, HRE; Jiaozhou Bay, JZ) along the northern Chinese coast were investigated for species identification and stock discrimination. The otolith contour shape described by elliptic Fourier coefficients (EFC) were analysed using principal components analysis (PCA) and stepwise canonical discriminant analysis (CDA) to identify species and stocks. The two species were well differentiated, with an overall classification success rate of 97.8%. And variations in the otolith shapes were significant enough to discriminate among the three geographical samples of C. lucidus (67.7%) or C. niveatus (65.2%). Relatively high mis-assignment occurred between the geographically adjacent LD and HRE samples, which implied that individual mixing may exist between the two samples. This study yielded information complementary to that derived from genetic studies and provided information for assessing the stock structure of C. lucidus and C. niveatus in the Bohai Sea and the Yellow Sea.

Automated segmentation of retinal pigment epithelium cells in fluorescence adaptive optics images.

PubMed

Rangel-Fonseca, Piero; Gómez-Vieyra, Armando; Malacara-Hernández, Daniel; Wilson, Mario C; Williams, David R; Rossi, Ethan A

2013-12-01

Adaptive optics (AO) imaging methods allow the histological characteristics of retinal cell mosaics, such as photoreceptors and retinal pigment epithelium (RPE) cells, to be studied in vivo. The high-resolution images obtained with ophthalmic AO imaging devices are rich with information that is difficult and/or tedious to quantify using manual methods. Thus, robust, automated analysis tools that can provide reproducible quantitative information about the cellular mosaics under examination are required. Automated algorithms have been developed to detect the position of individual photoreceptor cells; however, most of these methods are not well suited for characterizing the RPE mosaic. We have developed an algorithm for RPE cell segmentation and show its performance here on simulated and real fluorescence AO images of the RPE mosaic. Algorithm performance was compared to manual cell identification and yielded better than 91% correspondence. This method can be used to segment RPE cells for morphometric analysis of the RPE mosaic and speed the analysis of both healthy and diseased RPE mosaics.

Design principles and operating principles: the yin and yang of optimal functioning.

PubMed

Voit, Eberhard O

2003-03-01

Metabolic engineering has as a goal the improvement of yield of desired products from microorganisms and cell lines. This goal has traditionally been approached with experimental biotechnological methods, but it is becoming increasingly popular to precede the experimental phase by a mathematical modeling step that allows objective pre-screening of possible improvement strategies. The models are either linear and represent the stoichiometry and flux distribution in pathways or they are non-linear and account for the full kinetic behavior of the pathway, which is often significantly effected by regulatory signals. Linear flux analysis is simpler and requires less input information than a full kinetic analysis, and the question arises whether the consideration of non-linearities is really necessary for devising optimal strategies for yield improvements. The article analyzes this question with a generic, representative pathway. It shows that flux split ratios, which are the key criterion for linear flux analysis, are essentially sufficient for unregulated, but not for regulated branch points. The interrelationships between regulatory design on one hand and optimal patterns of operation on the other suggest the investigation of operating principles that complement design principles, like a user's manual complements the hardwiring of electronic equipment.

Bridging the gap between fluxomics and industrial biotechnology.

PubMed

Feng, Xueyang; Page, Lawrence; Rubens, Jacob; Chircus, Lauren; Colletti, Peter; Pakrasi, Himadri B; Tang, Yinjie J

2010-01-01

Metabolic flux analysis is a vital tool used to determine the ultimate output of cellular metabolism and thus detect biotechnologically relevant bottlenecks in productivity. ¹³C-based metabolic flux analysis (¹³C-MFA) and flux balance analysis (FBA) have many potential applications in biotechnology. However, noteworthy hurdles in fluxomics study are still present. First, several technical difficulties in both ¹³C-MFA and FBA severely limit the scope of fluxomics findings and the applicability of obtained metabolic information. Second, the complexity of metabolic regulation poses a great challenge for precise prediction and analysis of metabolic networks, as there are gaps between fluxomics results and other omics studies. Third, despite identified metabolic bottlenecks or sources of host stress from product synthesis, it remains difficult to overcome inherent metabolic robustness or to efficiently import and express nonnative pathways. Fourth, product yields often decrease as the number of enzymatic steps increases. Such decrease in yield may not be caused by rate-limiting enzymes, but rather is accumulated through each enzymatic reaction. Fifth, a high-throughput fluxomics tool hasnot been developed for characterizing nonmodel microorganisms and maximizing their application in industrial biotechnology. Refining fluxomics tools and understanding these obstacles will improve our ability to engineer highly efficient metabolic pathways in microbial hosts.

MALDI-MS/MS with Traveling Wave Ion Mobility for the Structural Analysis of N-Linked Glycans

NASA Astrophysics Data System (ADS)

Harvey, David J.; Scarff, Charlotte A.; Crispin, Max; Scanlan, Christopher N.; Bonomelli, Camille; Scrivens, James H.

2012-11-01

The preference for singly charged ion formation by MALDI makes it a better choice than electrospray ionization for profiling mixtures of N-glycans. For structural analysis, fragmentation of negative ions often yields more informative spectra than fragmentation of positive ones but such ions are more difficult to produce from neutral glycans under MALDI conditions. This work investigates conditions for the formation of both positive and negative ions by MALDI from N-linked glycans released from glycoproteins and their subsequent MS/MS and ion mobility behaviour. 2,4,6-Trihydroxyacetophenone (THAP) doped with ammonium nitrate was found to give optimal ion yields in negative ion mode. Ammonium chloride or phosphate also yielded prominent adducts but anionic carbohydrates such as sulfated N-glycans tended to ionize preferentially. Carbohydrates adducted with all three adducts (phosphate, chloride, and nitrate) produced good negative ion CID spectra but those adducted with iodide and sulfate did not yield fragment ions although they gave stronger signals. Fragmentation paralleled that seen following electrospray ionization providing superior spectra than could be obtained by PSD on MALDI-TOF instruments or with ion traps. In addition, ion mobility drift times of the adducted glycans and the ability of this technique to separate isomers also mirrored those obtained following ESI sample introduction. Ion mobility also allowed profiles to be obtained from samples whose MALDI spectra showed no evidence of such ions allowing the technique to be used in conditions where sample amounts were limiting. The method was applied to N-glycans released from the recombinant human immunodeficiency virus glycoprotein, gp120.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications.

PubMed

Silvestro, Paolo Cosmo; Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio; Casa, Raffaele

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.

Sensitivity analysis of the Aquacrop and SAFYE crop models for the assessment of water limited winter wheat yield in regional scale applications

PubMed Central

Pignatti, Stefano; Yang, Hao; Yang, Guijun; Pascucci, Simone; Castaldi, Fabio

2017-01-01

Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations. PMID:29107963

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

2001-10-01

- The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

Classical and Bayesian Seismic Yield Estimation: The 1998 Indian and Pakistani Tests

NASA Astrophysics Data System (ADS)

Shumway, R. H.

The nuclear tests in May, 1998, in India and Pakistan have stimulated a renewed interest in yield estimation, based on limited data from uncalibrated test sites. We study here the problem of estimating yields using classical and Bayesian methods developed by Shumway (1992), utilizing calibration data from the Semipalatinsk test site and measured magnitudes for the 1998 Indian and Pakistani tests given by Murphy (1998). Calibration is done using multivariate classical or Bayesian linear regression, depending on the availability of measured magnitude-yield data and prior information. Confidence intervals for the classical approach are derived applying an extension of Fieller's method suggested by Brown (1982). In the case where prior information is available, the posterior predictive magnitude densities are inverted to give posterior intervals for yield. Intervals obtained using the joint distribution of magnitudes are comparable to the single-magnitude estimates produced by Murphy (1998) and reinforce the conclusion that the announced yields of the Indian and Pakistani tests were too high.

On the analysis of Canadian Holstein dairy cow lactation curves using standard growth functions.

PubMed

López, S; France, J; Odongo, N E; McBride, R A; Kebreab, E; AlZahal, O; McBride, B W; Dijkstra, J

2015-04-01

Six classical growth functions (monomolecular, Schumacher, Gompertz, logistic, Richards, and Morgan) were fitted to individual and average (by parity) cumulative milk production curves of Canadian Holstein dairy cows. The data analyzed consisted of approximately 91,000 daily milk yield records corresponding to 122 first, 99 second, and 92 third parity individual lactation curves. The functions were fitted using nonlinear regression procedures, and their performance was assessed using goodness-of-fit statistics (coefficient of determination, residual mean squares, Akaike information criterion, and the correlation and concordance coefficients between observed and adjusted milk yields at several days in milk). Overall, all the growth functions evaluated showed an acceptable fit to the cumulative milk production curves, with the Richards equation ranking first (smallest Akaike information criterion) followed by the Morgan equation. Differences among the functions in their goodness-of-fit were enlarged when fitted to average curves by parity, where the sigmoidal functions with a variable point of inflection (Richards and Morgan) outperformed the other 4 equations. All the functions provided satisfactory predictions of milk yield (calculated from the first derivative of the functions) at different lactation stages, from early to late lactation. The Richards and Morgan equations provided the most accurate estimates of peak yield and total milk production per 305-d lactation, whereas the least accurate estimates were obtained with the logistic equation. In conclusion, classical growth functions (especially sigmoidal functions with a variable point of inflection) proved to be feasible alternatives to fit cumulative milk production curves of dairy cows, resulting in suitable statistical performance and accurate estimates of lactation traits. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Association of SNP and STR polymorphisms of insulin-like growth factor 2 receptor (IGF2R) gene with milk traits in Holstein-Friesian cows.

PubMed

Dux, Marta; Muranowicz, Magdalena; Siadkowska, Eulalia; Robakowska-Hyżorek, Dagmara; Flisikowski, Krzysztof; Bagnicka, Emilia; Zwierzchowski, Lech

2018-05-01

The objective of the study reported in this Research Communication was to investigate the association of polymorphisms in the insulin-like growth factor receptor 2 (IGF2R) gene with milk traits in 283 Polish Holstein-Friesian (PHF) cows from the IGAB PAS farm in Jastrzębiec. IGF2R regulates the availability of biologically active IGF2 which is considered as a genetic marker for milk or meat production in farm animals. Two novel genetic polymorphisms were identified in the bovine IGF2R gene: a polymorphic TG-repeat in intron 23 (g.72389 (TG)15-67), and a g.72479 G > A SNP RFLP-StyI in exon 24. The following milk traits were investigated: milk yield, protein and fat yield, SCC and lactose content. To determine the influence of the IGF2R STR and SNP genotypes on the milk traits, we used the AI-REML (average information restricted maximum likelihood) method with repeatability, multi-trait animal model based on test-day information using DMU package. Statistical analysis revealed that the G/A genotype (P ≤ 0·01) was associated with milk and protein yield, lactose content and somatic cell count (SCC) in Polish HF cows. TGn (29/22, 28/29, 28/22, 28/28) genotypes were associated with high values for milk, (28/22, 28/23) with protein and fat yield, (25/20) with lactose content, and (29/33, 28/28) with low SCC. We suggest that the IGF2R gene polymorphisms could be useful genetic markers for dairy production traits in cattle.

Quantifying the thermal heat requirement of Brassica in assessing biophysical parameters under semi-arid microenvironments

NASA Astrophysics Data System (ADS)

Adak, Tarun; Chakravarty, N. V. K.

2010-07-01

Evaluation of the thermal heat requirement of Brassica spp. across agro-ecological regions is required in order to understand the further effects of climate change. Spatio-temporal changes in hydrothermal regimes are likely to affect the physiological growth pattern of the crop, which in turn will affect economic yields and crop quality. Such information is helpful in developing crop simulation models to describe the differential thermal regimes that prevail at different phenophases of the crop. Thus, the current lack of quantitative information on the thermal heat requirement of Brassica crops under debranched microenvironments prompted the present study, which set out to examine the response of biophysical parameters [leaf area index (LAI), dry biomass production, seed yield and oil content] to modified microenvironments. Following 2 years of field experiments on Typic Ustocrepts soils under semi-arid climatic conditions, it was concluded that the Brassica crop is significantly responsive to microenvironment modification. A highly significant and curvilinear relationship was observed between LAI and dry biomass production with accumulated heat units, with thermal accumulation explaining ≥80% of the variation in LAI and dry biomass production. It was further observed that the economic seed yield and oil content, which are a function of the prevailing weather conditions, were significantly responsive to the heat units accumulated from sowing to 50% physiological maturity. Linear regression analysis showed that growing degree days (GDD) could indicate 60-70% variation in seed yield and oil content, probably because of the significant response to differential thermal microenvironments. The present study illustrates the statistically strong and significant response of biophysical parameters of Brassica spp. to microenvironment modification in semi-arid regions of northern India.

Estimating rice yield from MODIS-Landsat fusion data in Taiwan

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Nguyen, S. T.

2017-12-01

Rice production monitoring with remote sensing is an important activity in Taiwan due to official initiatives. Yield estimation is a challenge in Taiwan because rice fields are small and fragmental. High spatiotemporal satellite data providing phenological information of rice crops is thus required for this monitoring purpose. This research aims to develop data fusion approaches to integrate daily Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat data for rice yield estimation in Taiwan. In this study, the low-resolution MODIS LST and emissivity data are used as reference data sources to obtain the high-resolution LST from Landsat data using the mixed-pixel analysis technique, and the time-series EVI data were derived the fusion of MODIS and Landsat spectral band data using STARFM method. The LST and EVI simulated results showed the close agreement between the LST and EVI obtained by the proposed methods with the reference data. The rice-yield model was established using EVI and LST data based on information of rice crop phenology collected from 371 ground survey sites across the country in 2014. The results achieved from the fusion datasets compared with the reference data indicated the close relationship between the two datasets with the correlation coefficient (R2) of 0.75 and root mean square error (RMSE) of 338.7 kgs, which were more accurate than those using the coarse-resolution MODIS LST data (R2 = 0.71 and RMSE = 623.82 kgs). For the comparison of total production, 64 towns located in the west part of Taiwan were used. The results also confirmed that the model using fusion datasets produced more accurate results (R2 = 0.95 and RMSE = 1,243 tons) than that using the course-resolution MODIS data (R2 = 0.91 and RMSE = 1,749 tons). This study demonstrates the application of MODIS-Landsat fusion data for rice yield estimation at the township level in Taiwan. The results obtained from the methods used in this study could be useful to policymakers; and thus, the methods can be transferable to other regions in the world for rice yield estimation.

Estimating the impact of mineral aerosols on crop yields in food insecure regions using statistical crop models

NASA Astrophysics Data System (ADS)

Hoffman, A.; Forest, C. E.; Kemanian, A.

2016-12-01

A significant number of food-insecure nations exist in regions of the world where dust plays a large role in the climate system. While the impacts of common climate variables (e.g. temperature, precipitation, ozone, and carbon dioxide) on crop yields are relatively well understood, the impact of mineral aerosols on yields have not yet been thoroughly investigated. This research aims to develop the data and tools to progress our understanding of mineral aerosol impacts on crop yields. Suspended dust affects crop yields by altering the amount and type of radiation reaching the plant, modifying local temperature and precipitation. While dust events (i.e. dust storms) affect crop yields by depleting the soil of nutrients or by defoliation via particle abrasion. The impact of dust on yields is modeled statistically because we are uncertain which impacts will dominate the response on national and regional scales considered in this study. Multiple linear regression is used in a number of large-scale statistical crop modeling studies to estimate yield responses to various climate variables. In alignment with previous work, we develop linear crop models, but build upon this simple method of regression with machine-learning techniques (e.g. random forests) to identify important statistical predictors and isolate how dust affects yields on the scales of interest. To perform this analysis, we develop a crop-climate dataset for maize, soybean, groundnut, sorghum, rice, and wheat for the regions of West Africa, East Africa, South Africa, and the Sahel. Random forest regression models consistently model historic crop yields better than the linear models. In several instances, the random forest models accurately capture the temperature and precipitation threshold behavior in crops. Additionally, improving agricultural technology has caused a well-documented positive trend that dominates time series of global and regional yields. This trend is often removed before regression with traditional crop models, but likely at the cost of removing climate information. Our random forest models consistently discover the positive trend without removing any additional data. The application of random forests as a statistical crop model provides insight into understanding the impact of dust on yields in marginal food producing regions.

Comparison of RS/GIS analysis with classic mapping approaches for siting low-yield boreholes for hand pumps in crystalline terrains. An application to rural communities of the Caimbambo province, Angola

NASA Astrophysics Data System (ADS)

Martín-Loeches, Miguel; Reyes-López, Jaime; Ramírez-Hernández, Jorge; Temiño-Vela, Javier; Martínez-Santos, Pedro

2018-02-01

In poverty-stricken regions of Sub-Saharan Africa, groundwater for supply is often obtained by means of hand pumps, which means that low-yield boreholes are acceptable. However, boreholes are often sited without sufficient hydrogeological information due to budget constraints, which leads to high failure rates. Cost-effective techniques for borehole siting need to be developed in order to maximize the success rate. In regions underlain by granite, weathered formations are usually targeted for drilling, as these are generally presented as a better cost-benefit ratio than the fractured basement. Within this context, this research focuses on a granite region of Angola. A comparison of two mapping techniques for borehole siting-groundwater prospect is presented. A classic hydrogeomorphological map was developed first based on aerial photographs, field mapping and a geophysical survey. This map represents a considerable time investment and was developed by qualified technicians. The second map (RS/GIS) is considerably simpler and more cost-effective. It was developed by the integration in a GIS platform of six maps of equal importance-slope, drainage density, vegetation vigor, presence of clay in the soil, lineaments and rock outcrops-prepared from Landsat 8 imagery and a Digital Elevation Model (DEM). Similar results were obtained in both cases. By means of a supervised classification of Landsat images, RS/GIS analysis allows for the identification of granitic outcrops, house clusters and sandy alluvial valleys. This in turn allows for the delineation of low-interest or contamination-prone areas, thus contributing additional qualitative information. The position of a well that is going to be powered by a handpump is chosen also upon social and local matters as the distance to the stakeholders, information that are not difficult to integrate in the GIS. Although the second map needs some field inputs (i.e. surveys to determine the thickness of the weathered pack), results show that RS/GIS analyses such as this one provide a valuable and cost-effective alternative for siting low-yield boreholes in remote regions.

Genetic Variance Partitioning and Genome-Wide Prediction with Allele Dosage Information in Autotetraploid Potato.

PubMed

Endelman, Jeffrey B; Carley, Cari A Schmitz; Bethke, Paul C; Coombs, Joseph J; Clough, Mark E; da Silva, Washington L; De Jong, Walter S; Douches, David S; Frederick, Curtis M; Haynes, Kathleen G; Holm, David G; Miller, J Creighton; Muñoz, Patricio R; Navarro, Felix M; Novy, Richard G; Palta, Jiwan P; Porter, Gregory A; Rak, Kyle T; Sathuvalli, Vidyasagar R; Thompson, Asunta L; Yencho, G Craig

2018-05-01

As one of the world's most important food crops, the potato ( Solanum tuberosum L.) has spurred innovation in autotetraploid genetics, including in the use of SNP arrays to determine allele dosage at thousands of markers. By combining genotype and pedigree information with phenotype data for economically important traits, the objectives of this study were to (1) partition the genetic variance into additive vs. nonadditive components, and (2) determine the accuracy of genome-wide prediction. Between 2012 and 2017, a training population of 571 clones was evaluated for total yield, specific gravity, and chip fry color. Genomic covariance matrices for additive ( G ), digenic dominant ( D ), and additive × additive epistatic ( G # G ) effects were calculated using 3895 markers, and the numerator relationship matrix ( A ) was calculated from a 13-generation pedigree. Based on model fit and prediction accuracy, mixed model analysis with G was superior to A for yield and fry color but not specific gravity. The amount of additive genetic variance captured by markers was 20% of the total genetic variance for specific gravity, compared to 45% for yield and fry color. Within the training population, including nonadditive effects improved accuracy and/or bias for all three traits when predicting total genotypic value. When six F 1 populations were used for validation, prediction accuracy ranged from 0.06 to 0.63 and was consistently lower (0.13 on average) without allele dosage information. We conclude that genome-wide prediction is feasible in potato and that it will improve selection for breeding value given the substantial amount of nonadditive genetic variance in elite germplasm. Copyright © 2018 by the Genetics Society of America.

AMMI adjustment for statistical analysis of an international wheat yield trial.

PubMed

Crossa, J; Fox, P N; Pfeiffer, W H; Rajaram, S; Gauch, H G

1991-01-01

Multilocation trials are important for the CIMMYT Bread Wheat Program in producing high-yielding, adapted lines for a wide range of environments. This study investigated procedures for improving predictive success of a yield trial, grouping environments and genotypes into homogeneous subsets, and determining the yield stability of 18 CIMMYT bread wheats evaluated at 25 locations. Additive Main effects and Multiplicative Interaction (AMMI) analysis gave more precise estimates of genotypic yields within locations than means across replicates. This precision facilitated formation by cluster analysis of more cohesive groups of genotypes and locations for biological interpretation of interactions than occurred with unadjusted means. Locations were clustered into two subsets for which genotypes with positive interactions manifested in high, stable yields were identified. The analyses highlighted superior selections with both broad and specific adaptation.

How model and input uncertainty impact maize yield simulations in West Africa

NASA Astrophysics Data System (ADS)

Waha, Katharina; Huth, Neil; Carberry, Peter; Wang, Enli

2015-02-01

Crop models are common tools for simulating crop yields and crop production in studies on food security and global change. Various uncertainties however exist, not only in the model design and model parameters, but also and maybe even more important in soil, climate and management input data. We analyze the performance of the point-scale crop model APSIM and the global scale crop model LPJmL with different climate and soil conditions under different agricultural management in the low-input maize-growing areas of Burkina Faso, West Africa. We test the models’ response to different levels of input information from little to detailed information on soil, climate (1961-2000) and agricultural management and compare the models’ ability to represent the observed spatial (between locations) and temporal variability (between years) in crop yields. We found that the resolution of different soil, climate and management information influences the simulated crop yields in both models. However, the difference between models is larger than between input data and larger between simulations with different climate and management information than between simulations with different soil information. The observed spatial variability can be represented well from both models even with little information on soils and management but APSIM simulates a higher variation between single locations than LPJmL. The agreement of simulated and observed temporal variability is lower due to non-climatic factors e.g. investment in agricultural research and development between 1987 and 1991 in Burkina Faso which resulted in a doubling of maize yields. The findings of our study highlight the importance of scale and model choice and show that the most detailed input data does not necessarily improve model performance.

Yield and yield gaps in central U.S. corn production systems

USDA-ARS?s Scientific Manuscript database

The magnitude of yield gaps (YG) (potential yield – farmer yield) provides some indication of the prospects for increasing crop yield. Quantile regression analysis was applied to county maize (Zea mays L.) yields (1972 – 2011) from Kentucky, Iowa and Nebraska (irrigated) (total of 115 counties) to e...

Yield gaps and yield relationships in US soybean production systems

USDA-ARS?s Scientific Manuscript database

The magnitude of yield gaps (YG) (potential yield – farmer yield) provides some indication of the prospects for increasing crop yield to meet the food demands of future populations. Quantile regression analysis was applied to county soybean [Glycine max (L.) Merrill] yields (1971 – 2011) from Kentuc...

Social support and support groups among people with HIV/AIDS in Ghana.

PubMed

Abrefa-Gyan, Tina; Wu, Liyun; Lewis, Marilyn W

2016-01-01

HIV/AIDS, a chronic burden in Ghana, poses social and health outcome concerns to those infected. Examining the Medical Outcome Study Social Support Survey (MOS-SSS) instrument among 300 Ghanaians from a cross-sectional design, Principal Component Analysis yielded four factors (positive interaction, trust building, information giving, and essential support), which accounted for 85.73% of the total variance in the MOS-SSS. A logistic regression analysis showed that essential support was the strongest predictor of the length of time an individual stayed in the support group, whereas positive interaction indicated negative association. The study's implications for policy, research, and practice were discussed.

Perception: a concept analysis.

PubMed

McDonald, Susan M

2012-02-01

Concept analysis methodology by Walker and Avant (2005) was used to define, describe, and delimit the concept of perception. Nursing literature in the Medline database was searched for definitions of "perception." Definitions, uses, and defining attributes of perception were identified; model and contrary cases were developed; and antecedents, consequences, and empirical referents were determined. An operational definition for the concept was developed. Nurses need to be cognizant of how perceptual differences impact the delivery of nursing care. In research, a mixed methodology approach may yield a richer description of the phenomenon and provide useful information for clinical practice. © 2011, The Author. International Journal of Nursing Knowledge © 2011, NANDA International.

An Ideal Observer Analysis of Visual Working Memory

PubMed Central

Sims, Chris R.; Jacobs, Robert A.; Knill, David C.

2013-01-01

Limits in visual working memory (VWM) strongly constrain human performance across many tasks. However, the nature of these limits is not well understood. In this paper we develop an ideal observer analysis of human visual working memory, by deriving the expected behavior of an optimally performing, but limited-capacity memory system. This analysis is framed around rate–distortion theory, a branch of information theory that provides optimal bounds on the accuracy of information transmission subject to a fixed information capacity. The result of the ideal observer analysis is a theoretical framework that provides a task-independent and quantitative definition of visual memory capacity and yields novel predictions regarding human performance. These predictions are subsequently evaluated and confirmed in two empirical studies. Further, the framework is general enough to allow the specification and testing of alternative models of visual memory (for example, how capacity is distributed across multiple items). We demonstrate that a simple model developed on the basis of the ideal observer analysis—one which allows variability in the number of stored memory representations, but does not assume the presence of a fixed item limit—provides an excellent account of the empirical data, and further offers a principled re-interpretation of existing models of visual working memory. PMID:22946744

Examining social, physical, and environmental dimensions of tornado vulnerability in Texas.

PubMed

Siebeneck, Laura

2016-01-01

To develop a vulnerability model that captures the social, physical, and environmental dimensions of tornado vulnerability of Texas counties. Guided by previous research and methodologies proposed in the hazards and emergency management literature, a principle components analysis is used to create a tornado vulnerability index. Data were gathered from open source information available through the US Census Bureau, American Community Surveys, and the Texas Natural Resources Information System. Texas counties. The results of the model yielded three indices that highlight geographic variability of social vulnerability, built environment vulnerability, and tornado hazard throughout Texas. Further analyses suggest that counties with the highest tornado vulnerability include those with high population densities and high tornado risk. This article demonstrates one method for assessing statewide tornado vulnerability and presents how the results of this type of analysis can be applied by emergency managers towards the reduction of tornado vulnerability in their communities.

Scissors mode of Gd nuclei studied from resonance neutron capture

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

Kroll, J.; Baramsai, B.; Becker, J. A.

2012-10-20

Spectra of {gamma} rays following the neutron capture at isolated resonances of stable Gd nuclei were measured. The objectives were to get new information on photon strength of {sup 153,155-159}Gd with emphasis on the role of the M1 scissors-mode vibration. An analysis of the data obtained clearly indicates that the scissors mode is coupled not only to the ground state, but also to all excited levels of the nuclei studied. The specificity of our approach ensures unbiasedness in estimating the sumed scissors-mode strength {Sigma}B(M1){up_arrow}, even for odd product nuclei, for which conventional nuclear resonance fluorescence measurements yield only limited information.more » Our analysis indicates that for these nuclei the sum {Sigma}B(M1){up_arrow} increases with A and for {sup 157,159}Gd it is significantly higher compared to {sup 156,158}Gd.« less

Estimation of treatment effect in a subpopulation: An empirical Bayes approach.

PubMed

Shen, Changyu; Li, Xiaochun; Jeong, Jaesik

2016-01-01

It is well recognized that the benefit of a medical intervention may not be distributed evenly in the target population due to patient heterogeneity, and conclusions based on conventional randomized clinical trials may not apply to every person. Given the increasing cost of randomized trials and difficulties in recruiting patients, there is a strong need to develop analytical approaches to estimate treatment effect in subpopulations. In particular, due to limited sample size for subpopulations and the need for multiple comparisons, standard analysis tends to yield wide confidence intervals of the treatment effect that are often noninformative. We propose an empirical Bayes approach to combine both information embedded in a target subpopulation and information from other subjects to construct confidence intervals of the treatment effect. The method is appealing in its simplicity and tangibility in characterizing the uncertainty about the true treatment effect. Simulation studies and a real data analysis are presented.

Probabilistic peak detection in CE-LIF for STR DNA typing.

PubMed

Woldegebriel, Michael; van Asten, Arian; Kloosterman, Ate; Vivó-Truyols, Gabriel

2017-07-01

In this work, we present a novel probabilistic peak detection algorithm based on a Bayesian framework for forensic DNA analysis. The proposed method aims at an exhaustive use of raw electropherogram data from a laser-induced fluorescence multi-CE system. As the raw data are informative up to a single data point, the conventional threshold-based approaches discard relevant forensic information early in the data analysis pipeline. Our proposed method assigns a posterior probability reflecting the data point's relevance with respect to peak detection criteria. Peaks of low intensity generated from a truly existing allele can thus constitute evidential value instead of fully discarding them and contemplating a potential allele drop-out. This way of working utilizes the information available within each individual data point and thus avoids making early (binary) decisions on the data analysis that can lead to error propagation. The proposed method was tested and compared to the application of a set threshold as is current practice in forensic STR DNA profiling. The new method was found to yield a significant improvement in the number of alleles identified, regardless of the peak heights and deviation from Gaussian shape. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Electronic Health Record Implementation: A SWOT Analysis.

PubMed

Shahmoradi, Leila; Darrudi, Alireza; Arji, Goli; Farzaneh Nejad, Ahmadreza

2017-10-01

Electronic Health Record (EHR) is one of the most important achievements of information technology in healthcare domain, and if deployed effectively, it can yield predominant results. The aim of this study was a SWOT (strengths, weaknesses, opportunities, and threats) analysis in electronic health record implementation. This is a descriptive, analytical study conducted with the participation of a 90-member work force from Hospitals affiliated to Tehran University of Medical Sciences (TUMS). The data were collected by using a self-structured questionnaire and analyzed by SPSS software. Based on the results, the highest priority in strength analysis was related to timely and quick access to information. However, lack of hardware and infrastructures was the most important weakness. Having the potential to share information between different sectors and access to a variety of health statistics was the significant opportunity of EHR. Finally, the most substantial threats were the lack of strategic planning in the field of electronic health records together with physicians' and other clinical staff's resistance in the use of electronic health records. To facilitate successful adoption of electronic health record, some organizational, technical and resource elements contribute; moreover, the consideration of these factors is essential for HER implementation.

Risk Informed Margins Management as part of Risk Informed Safety Margin Characterization

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

Curtis Smith

2014-06-01

The ability to better characterize and quantify safety margin is important to improved decision making about Light Water Reactor (LWR) design, operation, and plant life extension. A systematic approach to characterization of safety margins and the subsequent margin management options represents a vital input to the licensee and regulatory analysis and decision making that will be involved. In addition, as research and development in the LWR Sustainability (LWRS) Program and other collaborative efforts yield new data, sensors, and improved scientific understanding of physical processes that govern the aging and degradation of plant SSCs needs and opportunities to better optimize plantmore » safety and performance will become known. To support decision making related to economics, readability, and safety, the Risk Informed Safety Margin Characterization (RISMC) Pathway provides methods and tools that enable mitigation options known as risk informed margins management (RIMM) strategies.« less

Evaluation of a liquid chromatography method for compound-specific δ13C analysis of plant carbohydrates in alkaline media.

PubMed

Rinne, Katja T; Saurer, Matthias; Streit, Kathrin; Siegwolf, Rolf T W

2012-09-30

Isotope analysis of carbohydrates is important for improved understanding of plant carbon metabolism and plant physiological response to the environment. High-performance liquid chromatography/isotope ratio mass spectrometry (HPLC/IRMS) for direct compound-specific δ(13)C measurements of soluble carbohydrates has recently been developed, but the still challenging sample preparation and the fact that no single method is capable of separating all compounds of interest hinder its wide-spread application. Here we tested in detail a chromatography method in alkaline media. We examined the most suitable chromatographic conditions for HPLC/IRMS analysis of carbohydrates in aqueous conifer needle extracts using a CarboPac PA20 anion-exchange column with NaOH eluent, paying specific attention to compound yields, carbon isotope fractionation processes and the reproducibility of the method. Furthermore, we adapted and calibrated sample preparation methods for HPLC/IRMS analysis. OnGuard II cartridges were used for sample purification. Good peak separation and highly linear and reproducible concentration and δ(13)C measurements were obtained. The alkaline eluent was observed to induce isomerization of hexoses, detected as reduced yields and (13)C fractionation of the affected compounds. A reproducible pre-purification method providing ~100% yield for the carbohydrate compounds of interest was calibrated. The good level of peak separation obtained in this study is reflected in the good precision and linearity of concentration and δ(13)C results. The data provided crucial information on the behaviour of sugars in LC analysis with alkaline media. The observations highlight the importance for the application of compound-matched standard solution for the detection and correction of instrumental biases in concentration and δ(13)C analysis performed under identical chromatographic conditions. The calibrated pre-purification method is well suited for studies with complex matrices that disable the use of a spiked internal standard for the detection of procedural losses. Copyright © 2012 John Wiley & Sons, Ltd.

Survey of patient-oriented total hip replacement information on the World Wide Web.

PubMed

Mabrey, J D

2000-12-01

The author conducted an informal survey of materials relating to diseases of the hip and total hip replacement as they appeared on the World Wide Web. The results varied depending on the key words used: hip and replacement yielded 1,818 matches; total hip replacement yielded 1,740 matches; hip replacement yielded 4,565 sites; and hip surgery yielded 1,073 sites. The number of sites for total hip replacement was observed to increase with time, having found an additional 30 sites from an identical search performed only 6 weeks earlier. The nature and quality of these sites varied from well-organized and informative, to personal testaments, to obvious commercial endeavors. Overall, this survey found an abundance of material regarding the hip and hip replacements on the World Wide Web, but orthopaedic societies need to take a more active role in constructing, maintaining, and monitoring these sites to best serve the needs of their patients and their members.

A quality assessment of the MARS crop yield forecasting system for the European Union

NASA Astrophysics Data System (ADS)

van der Velde, Marijn; Bareuth, Bettina

2015-04-01

Timely information on crop production forecasts can become of increasing importance as commodity markets are more and more interconnected. Impacts across large crop production areas due to (e.g.) extreme weather and pest outbreaks can create ripple effects that may affect food prices and availability elsewhere. The MARS Unit (Monitoring Agricultural ResourceS), DG Joint Research Centre, European Commission, has been providing forecasts of European crop production levels since 1993. The operational crop production forecasting is carried out with the MARS Crop Yield Forecasting System (M-CYFS). The M-CYFS is used to monitor crop growth development, evaluate short-term effects of anomalous meteorological events, and provide monthly forecasts of crop yield at national and European Union level. The crop production forecasts are published in the so-called MARS bulletins. Forecasting crop yield over large areas in the operational context requires quality benchmarks. Here we present an analysis of the accuracy and skill of past crop yield forecasts of the main crops (e.g. soft wheat, grain maize), throughout the growing season, and specifically for the final forecast before harvest. Two simple benchmarks to assess the skill of the forecasts were defined as comparing the forecasts to 1) a forecast equal to the average yield and 2) a forecast using a linear trend established through the crop yield time-series. These reveal a variability in performance as a function of crop and Member State. In terms of production, the yield forecasts of 67% of the EU-28 soft wheat production and 80% of the EU-28 maize production have been forecast superior to both benchmarks during the 1993-2013 period. In a changing and increasingly variable climate crop yield forecasts can become increasingly valuable - provided they are used wisely. We end our presentation by discussing research activities that could contribute to this goal.

(I Can't Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research.

PubMed

van Rijnsoever, Frank J

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: "random chance," which is based on probability sampling, "minimal information," which yields at least one new code per sampling step, and "maximum information," which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario.

Information filtering based on corrected redundancy-eliminating mass diffusion

PubMed Central

Zhu, Xuzhen; Yang, Yujie; Chen, Guilin; Medo, Matus; Tian, Hui

2017-01-01

Methods used in information filtering and recommendation often rely on quantifying the similarity between objects or users. The used similarity metrics often suffer from similarity redundancies arising from correlations between objects’ attributes. Based on an unweighted undirected object-user bipartite network, we propose a Corrected Redundancy-Eliminating similarity index (CRE) which is based on a spreading process on the network. Extensive experiments on three benchmark data sets—Movilens, Netflix and Amazon—show that when used in recommendation, the CRE yields significant improvements in terms of recommendation accuracy and diversity. A detailed analysis is presented to unveil the origins of the observed differences between the CRE and mainstream similarity indices. PMID:28749976

Phase transition phenomenon: A compound measure analysis

NASA Astrophysics Data System (ADS)

Kang, Bo Soo; Park, Chanhi; Ryu, Doojin; Song, Wonho

2015-06-01

This study investigates the well-documented phenomenon of phase transition in financial markets using combined information from both return and volume changes within short time intervals. We suggest a new measure for the phase transition behaviour of markets, calculated as a return distribution conditional on local variance in volume imbalance, and show that this measure successfully captures phase transition behaviour under various conditions. We analyse the intraday trade and quote dataset from the KOSPI 200 index futures, which includes detailed information on the original order size and the type of each initiating investor. We find that among these two competing factors, the submitted order size yields more explanatory power on the phenomenon of market phase transition than the investor type.

Isotopic Ratios of Samarium by TIMS for Nuclear Forensic Application

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

Louis Jean, James; Inglis, Jeremy David

The isotopic ratio of Nd, Sm, and Gd can provide important information regarding fissile material (nuclear devices, reactors), neutron environment, and device yield. These studies require precise measurement of Sm isotope ratios, by either TIMS or MC-ICP-MS. There has been an increasing trend to measure smaller and smaller quantities of Sm bearing samples. In nuclear forensics 10-100 ng of Sm are needed for precise measurement. To measure sub-ng Sm samples using TIMS for nuclear forensic analysis.

[Bacteriological aspects of trichomonal vaginitis (author's transl)].

PubMed

Brockmann, J; Höhne, C

1979-01-01

An analysis was made of the vaginal flora of 25 gynaecological patients with acute trichomomal vaginitis, with the view to elucidating the bacteriological situation. Eighty-four isolates, an average of 3.4 per patient, were taken and included a wide range of aerobic and anaerobic bacteria. - Obligate anaerobic species, such as bacteriodes and peptostreptococci, with susceptibility to metronidazole were among the predominant pathogens. - The differentiated susceptibility of the most common bacteria to antibiotics may yield information useful to therapy in the case of aggravated infection.

Streak Spectrograph Temperature Analysis from Electrically Exploded Ni/Al Nanolaminates

DTIC Science & Technology

2011-01-01

present. Using the spectral information of Ar, we analyzed the relative intensities of four Ar peaks between 425 and 455 nm, with respect to their...Ar peaks and their expected Boltzmann distribution functions yielded temperature values for each sample as a function of time. The following section...in the circuit was d2i dt2 + R L di dt + 1 LC i = 0 ð1Þ where L and R represent the total series inductance and resistance, respectively. By fitting

Selected bibliography on the modeling and control of plant processes

NASA Technical Reports Server (NTRS)

Viswanathan, M. M.; Julich, P. M.

1972-01-01

A bibliography of information pertinent to the problem of simulating plants is presented. Detailed simulations of constituent pieces are necessary to justify simple models which may be used for analysis. Thus, this area of study is necessary to support the Earth Resources Program. The report sums up the present state of the problem of simulating vegetation. This area holds the hope of major benefits to mankind through understanding the ecology of a region and in improving agricultural yield.

Teachers' instructional efficacy and teachers' efficacy toward integration of information technologies in the classroom.

PubMed

Dussault, Marc; Deaudelin, Colette; Brodeur, Monique

2004-06-01

The aim of the study was to investigate the relationship between teachers' instructional efficacy and their efficacy toward integration of technologies in the classroom. A sample of 309 French Canadian elementary school teachers volunteered and were administered a French Canadian version of the Teacher Efficacy Scale and Teachers' efficacy scale toward integration of technologies in the classroom. Analysis yielded, as expected, a positive and significant partial correlation between the two types of self-efficacy beliefs (.27 and .36).

Bimolecular reaction dynamics from photoelectron spectroscopy of negative ions

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

Bradforth, S.E.

1992-11-01

The transition state region of a neutral bimolecular reaction may be experimentally investigated by photoelectron spectroscopy of an appropriate negative ion. The photoelectron spectrum provides information on the spectroscopy and dynamics of the short lived transition state and may be used to develop model potential energy surfaces that are semi-quantitative in this important region. The principles of bound [yields] bound negative ion photoelectron spectroscopy are illustrated by way of an example: a full analysis of the photoelectron bands of CN[sup [minus

Short-time Lyapunov exponent analysis and the transition to chaos in Taylor-Couette flow

NASA Technical Reports Server (NTRS)

Vastano, John A.; Moser, Robert D.

1991-01-01

The physical mechanism driving the weakly chaotic Taylor-Couette flow is investigated using the short-time Liapunov exponent analysis. In this procedure, the transition from quasi-periodicity to chaos is studied using direct numerical 3D simulations of axially periodic Taylor-Couette flow, and a partial Liapunov exponent spectrum for the flow is computed by simultaneously advancing the full solution and a set of perturbations. It is shown that the short-time Liapunov exponent analysis yields more information on the exponents and dimension than that obtained from the common Liapunov exponent calculations. Results show that the chaotic state studied here is caused by a Kelvin-Helmholtz-type instability of the outflow boundary jet of Taylor vortices.

Response-restriction analysis: I. Assessment of activity preferences.

PubMed

Hanley, Gregory P; Iwata, Brian A; Lindberg, Jana S; Conners, Juliet

2003-01-01

We used procedures based on response-restriction (RR) analysis to assess vocational and leisure activity preferences for 3 adults with developmental disabilities. To increase the efficiency of the analysis relative to that reported in previous research, we used criteria that allowed activities to be restricted at the earliest point at which a preference could be determined. Results obtained across two consecutive RR assessments showed some variability in overall preference rankings but a high degree of consistency for highly ranked items. Finally, we compared results of the RR assessment with those of an extended free-operant assessment and found that the RR assessment yielded (a) more differentiated patterns of preference and (b) more complete information about engagement with all of the target activities.

Multi-trait analysis of genome-wide association summary statistics using MTAG.

PubMed

Turley, Patrick; Walters, Raymond K; Maghzian, Omeed; Okbay, Aysu; Lee, James J; Fontana, Mark Alan; Nguyen-Viet, Tuan Anh; Wedow, Robbee; Zacher, Meghan; Furlotte, Nicholas A; Magnusson, Patrik; Oskarsson, Sven; Johannesson, Magnus; Visscher, Peter M; Laibson, David; Cesarini, David; Neale, Benjamin M; Benjamin, Daniel J

2018-02-01

We introduce multi-trait analysis of GWAS (MTAG), a method for joint analysis of summary statistics from genome-wide association studies (GWAS) of different traits, possibly from overlapping samples. We apply MTAG to summary statistics for depressive symptoms (N eff  = 354,862), neuroticism (N = 168,105), and subjective well-being (N = 388,538). As compared to the 32, 9, and 13 genome-wide significant loci identified in the single-trait GWAS (most of which are themselves novel), MTAG increases the number of associated loci to 64, 37, and 49, respectively. Moreover, association statistics from MTAG yield more informative bioinformatics analyses and increase the variance explained by polygenic scores by approximately 25%, matching theoretical expectations.

Polarimetric Decomposition Analysis of the Deepwater Horizon Oil Slick Using L-Band UAVSAR Data

NASA Technical Reports Server (NTRS)

Jones, Cathleen; Minchew, Brent; Holt, Benjamin

2011-01-01

We report here an analysis of the polarization dependence of L-band radar backscatter from the main slick of the Deepwater Horizon oil spill, with specific attention to the utility of polarimetric decomposition analysis for discrimination of oil from clean water and identification of variations in the oil characteristics. For this study we used data collected with the UAVSAR instrument from opposing look directions directly over the main oil slick. We find that both the Cloude-Pottier and Shannon entropy polarimetric decomposition methods offer promise for oil discrimination, with the Shannon entropy method yielding the same information as contained in the Cloude-Pottier entropy and averaged in tensity parameters, but with significantly less computational complexity

Meta-analysis of Polyploid Cotton QTL Shows Unequal Contributions of Subgenomes to a Complex Network of Genes and Gene Clusters Implicated in Lint Fiber Development

PubMed Central

Rong, Junkang; Feltus, F. Alex; Waghmare, Vijay N.; Pierce, Gary J.; Chee, Peng W.; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J.; Wilkins, Thea A.; May, O. Lloyd; Smith, C. Wayne; Gannaway, John R.; Wendel, Jonathan F.; Paterson, Andrew H.

2007-01-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks. PMID:17565937

Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development.

PubMed

Rong, Junkang; Feltus, F Alex; Waghmare, Vijay N; Pierce, Gary J; Chee, Peng W; Draye, Xavier; Saranga, Yehoshua; Wright, Robert J; Wilkins, Thea A; May, O Lloyd; Smith, C Wayne; Gannaway, John R; Wendel, Jonathan F; Paterson, Andrew H

2007-08-01

QTL mapping experiments yield heterogeneous results due to the use of different genotypes, environments, and sampling variation. Compilation of QTL mapping results yields a more complete picture of the genetic control of a trait and reveals patterns in organization of trait variation. A total of 432 QTL mapped in one diploid and 10 tetraploid interspecific cotton populations were aligned using a reference map and depicted in a CMap resource. Early demonstrations that genes from the non-fiber-producing diploid ancestor contribute to tetraploid lint fiber genetics gain further support from multiple populations and environments and advanced-generation studies detecting QTL of small phenotypic effect. Both tetraploid subgenomes contribute QTL at largely non-homeologous locations, suggesting divergent selection acting on many corresponding genes before and/or after polyploid formation. QTL correspondence across studies was only modest, suggesting that additional QTL for the target traits remain to be discovered. Crosses between closely-related genotypes differing by single-gene mutants yield profoundly different QTL landscapes, suggesting that fiber variation involves a complex network of interacting genes. Members of the lint fiber development network appear clustered, with cluster members showing heterogeneous phenotypic effects. Meta-analysis linked to synteny-based and expression-based information provides clues about specific genes and families involved in QTL networks.

Space Radiation Induced Cytogenetic Damage in the Blood Lymphocytes of Astronauts: Persistence of Damage After Flight and the Effects of Repeat Long Duration Missions

NASA Technical Reports Server (NTRS)

George, Kerry; Rhone, Jordan; Chappell, L. J.; Cucinotta, F. A.

2010-01-01

Cytogenetic damage was assessed in blood lymphocytes from astronauts before and after they participated in long-duration space missions of three months or more. The frequency of chromosome damage was measured by fluorescence in situ hybridization (FISH) chromosome painting before flight and at various intervals from a few days to many months after return from the mission. For all individuals, the frequency of chromosome exchanges measured within a month of return from space was higher than their prefight yield. However, some individuals showed a temporal decline in chromosome damage with time after flight. Statistical analysis using combined data for all astronauts indicated a significant overall decreasing trend in total chromosome exchanges with time after flight, although this trend was not seen for all astronauts and the yield of chromosome damage in some individuals actually increased with time after flight. The decreasing trend in total exchanges was slightly more significant when statistical analysis was restricted to data collected more than 220 days after return from flight. In addition, limited data on multiple flights show a lack of correlation between time in space and translocation yields. Data from three crewmembers who has participated in two separate long-duration space missions provide limited information on the effect of repeat flights and show a possible adaptive response to space radiation exposure.

Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

PubMed Central

Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

2013-01-01

Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species. PMID:23223793

Osmylation of C[sub 60]: Proof and characterization of the soccer-ball framework

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

Hawkins, J.M.

1992-03-01

When C[sub 60] was isolated in macroscopic quantities in 1990, it transcended the realm of gas-phase physical chemistry and availed itself to the characterization and utilizations of condensed matter. On one hand, it became a new material, a new allotrope of carbon. On the other hand, it became a new organic compound, one that did not contain elements other than carbon, and one that could serve as the parent and precursors to a whole class of novel organic compounds. When first available in macroscopic quantities, C[sub 60] was probed spectroscopically in a number of laboratories. The authors probed the structuremore » of C[sub 60] chemically and found that the characterization of pure derivatives of C[sub 60] could yield information about C[sub 60] which could not be obtained directly. They prepared the first pure fullerene derivative, C[sub 60](OsO[sub 4])(4-tert-butylpyridine)[sub 2]. The characterization of this species yielded the first time atomic-resolution X-ray crystallographic analysis of the carbon framework of C[sub 60], thereby providing the first definitive proof of the buckminsterfullerene structure. Further analysis of 1 yielded the first measurement of coupling constants and hybridizations corresponding to that two types of bonds in C[sub 60] and the first quantitative labeling study probing the mechanism of C[sub 60] formation. 34 refs., 9 figs., 2 tabs.« less

Quantitative Analysis of Cotton Canopy Size in Field Conditions Using a Consumer-Grade RGB-D Camera.

PubMed

Jiang, Yu; Li, Changying; Paterson, Andrew H; Sun, Shangpeng; Xu, Rui; Robertson, Jon

2017-01-01

Plant canopy structure can strongly affect crop functions such as yield and stress tolerance, and canopy size is an important aspect of canopy structure. Manual assessment of canopy size is laborious and imprecise, and cannot measure multi-dimensional traits such as projected leaf area and canopy volume. Field-based high throughput phenotyping systems with imaging capabilities can rapidly acquire data about plants in field conditions, making it possible to quantify and monitor plant canopy development. The goal of this study was to develop a 3D imaging approach to quantitatively analyze cotton canopy development in field conditions. A cotton field was planted with 128 plots, including four genotypes of 32 plots each. The field was scanned by GPhenoVision (a customized field-based high throughput phenotyping system) to acquire color and depth images with GPS information in 2016 covering two growth stages: canopy development, and flowering and boll development. A data processing pipeline was developed, consisting of three steps: plot point cloud reconstruction, plant canopy segmentation, and trait extraction. Plot point clouds were reconstructed using color and depth images with GPS information. In colorized point clouds, vegetation was segmented from the background using an excess-green (ExG) color filter, and cotton canopies were further separated from weeds based on height, size, and position information. Static morphological traits were extracted on each day, including univariate traits (maximum and mean canopy height and width, projected canopy area, and concave and convex volumes) and a multivariate trait (cumulative height profile). Growth rates were calculated for univariate static traits, quantifying canopy growth and development. Linear regressions were performed between the traits and fiber yield to identify the best traits and measurement time for yield prediction. The results showed that fiber yield was correlated with static traits after the canopy development stage ( R 2 = 0.35-0.71) and growth rates in early canopy development stages ( R 2 = 0.29-0.52). Multi-dimensional traits (e.g., projected canopy area and volume) outperformed one-dimensional traits, and the multivariate trait (cumulative height profile) outperformed univariate traits. The proposed approach would be useful for identification of quantitative trait loci (QTLs) controlling canopy size in genetics/genomics studies or for fiber yield prediction in breeding programs and production environments.

Spatially explicit measures of production of young alewives in Lake Michigan: Linkage between essential fish habitat and recruitment

USGS Publications Warehouse

Hook, Tomas O.; Rutherford, Edward S.; Brines, Shannon J.; Mason, Doran M.; Schwab, David J.; McCormick, Michael; Desorcie, Timothy J.

2003-01-01

The identification and protection of essential habitats for early life stages of fishes are necessary to sustain fish stocks. Essential fish habitat for early life stages may be defined as areas where fish densities, growth, survival, or production rates are relatively high. To identify critical habitats for young-of-year (YOY) alewives (Alosa pseud oharengus) in Lake Michigan, we integrated bioenergetics models with GIS (Geographic Information Systems) to generate spatially explicit estimates of potential population production (an index of habitat quality). These estimates were based upon YOY alewife bioenergetic growth rate potential and their salmonine predators’ consumptive demand. We compared estimates of potential population production to YOY alewife yield (an index of habitat importance). Our analysis suggested that during 1994–1995, YOY alewife habitat quality and yield varied widely throughout Lake Michigan. Spatial patterns of alewife yield were not significantly correlated to habitat quality. Various mechanisms (e.g., predator migrations, lake circulation patterns, alternative strategies) may preclude YOY alewives from concentrating in areas of high habitat quality in Lake Michigan.

Optimized pH method for DNA elution from buccal cells collected in Whatman FTA cards.

PubMed

Lema, Carolina; Kohl-White, Kendra; Lewis, Laurie R; Dao, Dat D

2006-01-01

DNA is the most accessible biologic material for obtaining information from the human genome because of its molecular stability and its presence in every nucleated cell. Currently, single nucleotide polymorphism genotyping and DNA methylation are the main DNA-based approaches to deriving genomic and epigenomic disease biomarkers. Upon the discontinuation of the Schleicher & Schuell IsoCode product (Dassel, Germany), which was a treated paper system to elute DNA from several biologic sources for polymerase chain reaction (PCR) analysis, a high-yielding DNA elution method was imperative. We describe here an improved procedure of the not fully validated Whatman pH-based elution protocol. Our DNA elution procedure from buccal cells collected in Whatman FTA cards (Whatman Inc., Florham Park, NJ) yielded approximately 4 microg of DNA from a 6-mm FTA card punch and was successfully applied for HLA-DQB1 genotyping. The genotypes showed complete concordance with data obtained from blood of the same subjects. The achieved high DNA yield from buccal cells suggests a potential cost-effective tool for genomic and epigenomic disease biomarkers development.

Bayesian inference for the genetic control of water deficit tolerance in spring wheat by stochastic search variable selection.

PubMed

Safari, Parviz; Danyali, Syyedeh Fatemeh; Rahimi, Mehdi

2018-06-02

Drought is the main abiotic stress seriously influencing wheat production. Information about the inheritance of drought tolerance is necessary to determine the most appropriate strategy to develop tolerant cultivars and populations. In this study, generation means analysis to identify the genetic effects controlling grain yield inheritance in water deficit and normal conditions was considered as a model selection problem in a Bayesian framework. Stochastic search variable selection (SSVS) was applied to identify the most important genetic effects and the best fitted models using different generations obtained from two crosses applying two water regimes in two growing seasons. The SSVS is used to evaluate the effect of each variable on the dependent variable via posterior variable inclusion probabilities. The model with the highest posterior probability is selected as the best model. In this study, the grain yield was controlled by the main effects (additive and non-additive effects) and epistatic. The results demonstrate that breeding methods such as recurrent selection and subsequent pedigree method and hybrid production can be useful to improve grain yield.

Uncertainty in simulating wheat yields under climate change

NASA Astrophysics Data System (ADS)

Asseng, S.; Ewert, F.; Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P. J.; Rötter, R. P.; Cammarano, D.; Brisson, N.; Basso, B.; Martre, P.; Aggarwal, P. K.; Angulo, C.; Bertuzzi, P.; Biernath, C.; Challinor, A. J.; Doltra, J.; Gayler, S.; Goldberg, R.; Grant, R.; Heng, L.; Hooker, J.; Hunt, L. A.; Ingwersen, J.; Izaurralde, R. C.; Kersebaum, K. C.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.; Olesen, J. E.; Osborne, T. M.; Palosuo, T.; Priesack, E.; Ripoche, D.; Semenov, M. A.; Shcherbak, I.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Travasso, M.; Waha, K.; Wallach, D.; White, J. W.; Williams, J. R.; Wolf, J.

2013-09-01

Projections of climate change impacts on crop yields are inherently uncertain. Uncertainty is often quantified when projecting future greenhouse gas emissions and their influence on climate. However, multi-model uncertainty analysis of crop responses to climate change is rare because systematic and objective comparisons among process-based crop simulation models are difficult. Here we present the largest standardized model intercomparison for climate change impacts so far. We found that individual crop models are able to simulate measured wheat grain yields accurately under a range of environments, particularly if the input information is sufficient. However, simulated climate change impacts vary across models owing to differences in model structures and parameter values. A greater proportion of the uncertainty in climate change impact projections was due to variations among crop models than to variations among downscaled general circulation models. Uncertainties in simulated impacts increased with CO2 concentrations and associated warming. These impact uncertainties can be reduced by improving temperature and CO2 relationships in models and better quantified through use of multi-model ensembles. Less uncertainty in describing how climate change may affect agricultural productivity will aid adaptation strategy development andpolicymaking.

Temporal Correlations and Neural Spike Train Entropy

NASA Astrophysics Data System (ADS)

Schultz, Simon R.; Panzeri, Stefano

2001-06-01

Sampling considerations limit the experimental conditions under which information theoretic analyses of neurophysiological data yield reliable results. We develop a procedure for computing the full temporal entropy and information of ensembles of neural spike trains, which performs reliably for limited samples of data. This approach also yields insight to the role of correlations between spikes in temporal coding mechanisms. The method, when applied to recordings from complex cells of the monkey primary visual cortex, results in lower rms error information estimates in comparison to a ``brute force'' approach.

Pre-K Benefits: The Facts on Fade-Out

ERIC Educational Resources Information Center

Southern Regional Education Board (SREB), 2015

2015-01-01

As policymakers adopt policies for pre-K programs, they want to know that the programs are effective. Do the gains last? This brief report presents information that pre-k yields short-term academic gains; pre-k yields long-term academic gains; and pre-k yields substantial nonacademic benefits.

Loblolly Pine Growth and Yield Prediction for Managed West Gulf Plantations

Treesearch

V. Clark Baldwin; D.P. Feduccia

1987-01-01

Complete description, including tables, graphs, computer output, of a growth and yield prediction system providing volume and weight yields in stand and stock table format. An example of system use is given along with information about the computer program, COMPUTE P-LOB, that operates the system.

Responses of inulin content and inulin yield of Jerusalem artichoke genotypes to seasonal environments

USDA-ARS?s Scientific Manuscript database

Seasonal variation (e.g. temperature and photoperiod) between growing seasons might affect inulin content and inulin yield of Jerusalem artichoke. However, there is limited information on genotypic response to seasons for inulin content and inulin yield. The objective of this study was to investig...

Reference evapotranspiration forecasting based on local meteorological and global climate information screened by partial mutual information

NASA Astrophysics Data System (ADS)

Fang, Wei; Huang, Shengzhi; Huang, Qiang; Huang, Guohe; Meng, Erhao; Luan, Jinkai

2018-06-01

In this study, reference evapotranspiration (ET0) forecasting models are developed for the least economically developed regions subject to meteorological data scarcity. Firstly, the partial mutual information (PMI) capable of capturing the linear and nonlinear dependence is investigated regarding its utility to identify relevant predictors and exclude those that are redundant through the comparison with partial linear correlation. An efficient input selection technique is crucial for decreasing model data requirements. Then, the interconnection between global climate indices and regional ET0 is identified. Relevant climatic indices are introduced as additional predictors to comprise information regarding ET0, which ought to be provided by meteorological data unavailable. The case study in the Jing River and Beiluo River basins, China, reveals that PMI outperforms the partial linear correlation in excluding the redundant information, favouring the yield of smaller predictor sets. The teleconnection analysis identifies the correlation between Nino 1 + 2 and regional ET0, indicating influences of ENSO events on the evapotranspiration process in the study area. Furthermore, introducing Nino 1 + 2 as predictors helps to yield more accurate ET0 forecasts. A model performance comparison also shows that non-linear stochastic models (SVR or RF with input selection through PMI) do not always outperform linear models (MLR with inputs screen by linear correlation). However, the former can offer quite comparable performance depending on smaller predictor sets. Therefore, efforts such as screening model inputs through PMI and incorporating global climatic indices interconnected with ET0 can benefit the development of ET0 forecasting models suitable for data-scarce regions.

Multiattribute evaluation of regional cotton variety trials.

PubMed

Basford, K E; Kroonenberg, P M; Delacy, I H; Lawrence, P K

1990-02-01

The Australian Cotton Cultivar Trials (ACCT) are designed to investigate various cotton [Gossypium hirsutum (L.)] lines in several locations in New South Wales and Queensland each year. If these lines are to be assessed by the simultaneous use of yield and lint quality data, then a multivariate technique applicable to three-way data is desirable. Two such techniques, the mixture maximum likelihood method of clustering and three-mode principal component analysis, are described and used to analyze these data. Applied together, the methods enhance each other's usefulness in interpreting the information on the line response patterns across the locations. The methods provide a good integration of the responses across environments of the entries for the different attributes in the trials. For instance, using yield as the sole criterion, the excellence of the namcala and coker group for quality is overlooked. The analyses point to a decision in favor of either high yields of moderate to good quality lint or moderate yield but superior lint quality. The decisions indicated by the methods confirmed the selections made by the plant breeders. The procedures provide a less subjective, relatively easy to apply and interpret analytical method of describing the patterns of performance and associations in complex multiattribute and multilocation trials. This should lead to more efficient selection among lines in such trials.

Global Synthesis of Drought Effects on Food Legume Production

PubMed Central

Daryanto, Stefani; Wang, Lixin; Jacinthe, Pierre-André

2015-01-01

Food legume crops play important roles in conservation farming systems and contribute to food security in the developing world. However, in many regions of the world, their production has been adversely affected by drought. Although water scarcity is a severe abiotic constraint of legume crops productivity, it remains unclear how the effects of drought co-vary with legume species, soil texture, agroclimatic region, and drought timing. To address these uncertainties, we collected literature data between 1980 and 2014 that reported monoculture legume yield responses to drought under field conditions, and analyzed this data set using meta-analysis techniques. Our results showed that the amount of water reduction was positively related with yield reduction, but the extent of the impact varied with legume species and the phenological state during which drought occurred. Overall, lentil (Lens culinaris), groundnut (Arachis hypogaea), and pigeon pea (Cajanus cajan) were found to experience lower drought-induced yield reduction compared to legumes such as cowpea (Vigna unguiculata) and green gram (Vigna radiate). Yield reduction was generally greater when legumes experienced drought during their reproductive stage compared to during their vegetative stage. Legumes grown in soil with medium texture also exhibited greater yield reduction compared to those planted on soil of either coarse or fine texture. In contrast, regions and their associated climatic factors did not significantly affect legume yield reduction. In the face of changing climate, our study provides useful information for agricultural planning and research directions for development of drought-resistant legume species to improve adaptation and resilience of agricultural systems in the drought-prone regions of the world. PMID:26061704

Multitrait, Random Regression, or Simple Repeatability Model in High-Throughput Phenotyping Data Improve Genomic Prediction for Wheat Grain Yield.

PubMed

Sun, Jin; Rutkoski, Jessica E; Poland, Jesse A; Crossa, José; Jannink, Jean-Luc; Sorrells, Mark E

2017-07-01

High-throughput phenotyping (HTP) platforms can be used to measure traits that are genetically correlated with wheat ( L.) grain yield across time. Incorporating such secondary traits in the multivariate pedigree and genomic prediction models would be desirable to improve indirect selection for grain yield. In this study, we evaluated three statistical models, simple repeatability (SR), multitrait (MT), and random regression (RR), for the longitudinal data of secondary traits and compared the impact of the proposed models for secondary traits on their predictive abilities for grain yield. Grain yield and secondary traits, canopy temperature (CT) and normalized difference vegetation index (NDVI), were collected in five diverse environments for 557 wheat lines with available pedigree and genomic information. A two-stage analysis was applied for pedigree and genomic selection (GS). First, secondary traits were fitted by SR, MT, or RR models, separately, within each environment. Then, best linear unbiased predictions (BLUPs) of secondary traits from the above models were used in the multivariate prediction models to compare predictive abilities for grain yield. Predictive ability was substantially improved by 70%, on average, from multivariate pedigree and genomic models when including secondary traits in both training and test populations. Additionally, (i) predictive abilities slightly varied for MT, RR, or SR models in this data set, (ii) results indicated that including BLUPs of secondary traits from the MT model was the best in severe drought, and (iii) the RR model was slightly better than SR and MT models under drought environment. Copyright © 2017 Crop Science Society of America.

Towards a Probabilistic Preliminary Design Criterion for Buckling Critical Composite Shells

NASA Technical Reports Server (NTRS)

Arbocz, Johann; Hilburger, Mark W.

2003-01-01

A probability-based analysis method for predicting buckling loads of compression-loaded laminated-composite shells is presented, and its potential as a basis for a new shell-stability design criterion is demonstrated and discussed. In particular, a database containing information about specimen geometry, material properties, and measured initial geometric imperfections for a selected group of laminated-composite cylindrical shells is used to calculate new buckling-load "knockdown factors". These knockdown factors are shown to be substantially improved, and hence much less conservative than the corresponding deterministic knockdown factors that are presently used by industry. The probability integral associated with the analysis is evaluated by using two methods; that is, by using the exact Monte Carlo method and by using an approximate First-Order Second- Moment method. A comparison of the results from these two methods indicates that the First-Order Second-Moment method yields results that are conservative for the shells considered. Furthermore, the results show that the improved, reliability-based knockdown factor presented always yields a safe estimate of the buckling load for the shells examined.

Measuring leader perceptions of school readiness for reforms: use of an iterative model combining classical and Rasch methods.

PubMed

Chatterji, Madhabi

2002-01-01

This study examines validity of data generated by the School Readiness for Reforms: Leader Questionnaire (SRR-LQ) using an iterative procedure that combines classical and Rasch rating scale analysis. Following content-validation and pilot-testing, principal axis factor extraction and promax rotation of factors yielded a five factor structure consistent with the content-validated subscales of the original instrument. Factors were identified based on inspection of pattern and structure coefficients. The rotated factor pattern, inter-factor correlations, convergent validity coefficients, and Cronbach's alpha reliability estimates supported the hypothesized construct properties. To further examine unidimensionality and efficacy of the rating scale structures, item-level data from each factor-defined subscale were subjected to analysis with the Rasch rating scale model. Data-to-model fit statistics and separation reliability for items and persons met acceptable criteria. Rating scale results suggested consistency of expected and observed step difficulties in rating categories, and correspondence of step calibrations with increases in the underlying variables. The combined approach yielded more comprehensive diagnostic information on the quality of the five SRR-LQ subscales; further research is continuing.

Deep sub-wavelength metrology for advanced defect classification

NASA Astrophysics Data System (ADS)

van der Walle, P.; Kramer, E.; van der Donck, J. C. J.; Mulckhuyse, W.; Nijsten, L.; Bernal Arango, F. A.; de Jong, A.; van Zeijl, E.; Spruit, H. E. T.; van den Berg, J. H.; Nanda, G.; van Langen-Suurling, A. K.; Alkemade, P. F. A.; Pereira, S. F.; Maas, D. J.

2017-06-01

Particle defects are important contributors to yield loss in semi-conductor manufacturing. Particles need to be detected and characterized in order to determine and eliminate their root cause. We have conceived a process flow for advanced defect classification (ADC) that distinguishes three consecutive steps; detection, review and classification. For defect detection, TNO has developed the Rapid Nano (RN3) particle scanner, which illuminates the sample from nine azimuth angles. The RN3 is capable of detecting 42 nm Latex Sphere Equivalent (LSE) particles on XXX-flat Silicon wafers. For each sample, the lower detection limit (LDL) can be verified by an analysis of the speckle signal, which originates from the surface roughness of the substrate. In detection-mode (RN3.1), the signal from all illumination angles is added. In review-mode (RN3.9), the signals from all nine arms are recorded individually and analyzed in order to retrieve additional information on the shape and size of deep sub-wavelength defects. This paper presents experimental and modelling results on the extraction of shape information from the RN3.9 multi-azimuth signal such as aspect ratio, skewness, and orientation of test defects. Both modeling and experimental work confirm that the RN3.9 signal contains detailed defect shape information. After review by RN3.9, defects are coarsely classified, yielding a purified Defect-of-Interest (DoI) list for further analysis on slower metrology tools, such as SEM, AFM or HIM, that provide more detailed review data and further classification. Purifying the DoI list via optical metrology with RN3.9 will make inspection time on slower review tools more efficient.

A simple and reliable method reducing sulfate to sulfide for multiple sulfur isotope analysis.

PubMed

Geng, Lei; Savarino, Joel; Savarino, Clara A; Caillon, Nicolas; Cartigny, Pierre; Hattori, Shohei; Ishino, Sakiko; Yoshida, Naohiro

2018-02-28

Precise analysis of four sulfur isotopes of sulfate in geological and environmental samples provides the means to extract unique information in wide geological contexts. Reduction of sulfate to sulfide is the first step to access such information. The conventional reduction method suffers from a cumbersome distillation system, long reaction time and large volume of the reducing solution. We present a new and simple method enabling the process of multiple samples at one time with a much reduced volume of reducing solution. One mL of reducing solution made of HI and NaH 2 PO 2 was added to a septum glass tube with dry sulfate. The tube was heated at 124°C and the produced H 2 S was purged with inert gas (He or N 2 ) through gas-washing tubes and then collected by NaOH solution. The collected H 2 S was converted into Ag 2 S by adding AgNO 3 solution and the co-precipitated Ag 2 O was removed by adding a few drops of concentrated HNO 3 . Within 2-3 h, a 100% yield was observed for samples with 0.2-2.5 μmol Na 2 SO 4 . The reduction rate was much slower for BaSO 4 and a complete reduction was not observed. International sulfur reference materials, NBS-127, SO-5 and SO-6, were processed with this method, and the measured against accepted δ 34 S values yielded a linear regression line which had a slope of 0.99 ± 0.01 and a R 2 value of 0.998. The new methodology is easy to handle and allows us to process multiple samples at a time. It has also demonstrated good reproducibility in terms of H 2 S yield and for further isotope analysis. It is thus a good alternative to the conventional manual method, especially when processing samples with limited amount of sulfate available. © 2017 The Authors. Rapid Communications in Mass Spectrometry Pubished by John Wiley & Sons Ltd.

Yakima/Klickitat Fisheries Project Genetic Studies; Yakima/Klickitat Fisheries Project Monitoring and Evaluation, 2000-2001 Annual Report.

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

Busack, Craig A.; Schroder, Steven L.; Young, Sewall F.

2002-11-01

Genetic work for 2001 consisted of two major phases, both reported on here. The first is a DNA microsatellite analysis of several hundred juveniles from the experimental spawning channel at the Cle Elum Supplementation Research Facility, using the genetic markers to assign the juveniles to parents, and thus judge reproductive success of individual fish. The second is a reevaluation and revision of plans for studying domestication in the spring chinook supplementation effort. The pedigree analysis was significant in three respects. First, it showed that this approach can be successfully applied to the spawning channel research. Secondly it showed that thismore » approach does indeed yield very useful information about the relative reproductive success of fish in the channel. Finally, it showed that this information can yield additional information about the experimental design. Of the 961 juveniles on which analysis was attempted, 774 yielded enough genetic information to be used in the pedigree analysis. Of these, 754 were assigned to males and females known to have been placed into the channel. Of the other 20, all were assignable to females, but sires were unknown. The genotypes of 17 of these were consistent with a single theoretical male genotype, suggesting a single precocial male sired them. The inferred parentage of the fish demonstrated that there had been substantial leakage of juveniles from one section of the channel into another. Reproductive success of females was fairly even, but success of males varied considerably. In a group of seven males (including the hypothetical one), one contributed 79% of the progeny analyzed, and three contributed none. The domestication experimental design evaluation was prompted by a critical review of the project by the Independent Scientific Review Panel (ISRP). The ISRP review set into motion a design revision process which extended beyond the contract period; the report presented here is intended to be an account of our work through the end of the contract period, so does not include developments beyond that point. As such, combined with the upcoming 2002 report, it will provide a complete record of our process through the experimental design revision process. The current report contains the following: (1) An explanation of the general concept of domestication, and why domestication is a concern in the YKFP spring chinook program; (2) A discussion of the basics of experimental design for domestication; (3) A history of domestication experimental design for domestication in the YKFP; (4) A review of potential designs that would answer the ISRP's criticisms; (5) A revised design containing the following elements--A control line under continuous hatchery culture (i.e.; no spawning in the wild); use of the Naches population, where appropriate, as a wild control line; (6) Cryopreservation of sperm for later evaluation of long-term genetic trend; and (7) Continuous monitoring of phenotypic trend in the supplemented line.« less

Cost-Effectiveness and Value of Information Analysis of Brief Interventions to Promote Physical Activity in Primary Care.

PubMed

Gc, Vijay Singh; Suhrcke, Marc; Hardeman, Wendy; Sutton, Stephen; Wilson, Edward C F

2018-01-01

Brief interventions (BIs) delivered in primary care have shown potential to increase physical activity levels and may be cost-effective, at least in the short-term, when compared with usual care. Nevertheless, there is limited evidence on their longer term costs and health benefits. To estimate the cost-effectiveness of BIs to promote physical activity in primary care and to guide future research priorities using value of information analysis. A decision model was used to compare the cost-effectiveness of three classes of BIs that have been used, or could be used, to promote physical activity in primary care: 1) pedometer interventions, 2) advice/counseling on physical activity, and (3) action planning interventions. Published risk equations and data from the available literature or routine data sources were used to inform model parameters. Uncertainty was investigated with probabilistic sensitivity analysis, and value of information analysis was conducted to estimate the value of undertaking further research. In the base-case, pedometer interventions yielded the highest expected net benefit at a willingness to pay of £20,000 per quality-adjusted life-year. There was, however, a great deal of decision uncertainty: the expected value of perfect information surrounding the decision problem for the National Health Service Health Check population was estimated at £1.85 billion. Our analysis suggests that the use of pedometer BIs is the most cost-effective strategy to promote physical activity in primary care, and that there is potential value in further research into the cost-effectiveness of brief (i.e., <30 minutes) and very brief (i.e., <5 minutes) pedometer interventions in this setting. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Relative fission product yield determination in the USGS TRIGA Mark I reactor

NASA Astrophysics Data System (ADS)

Koehl, Michael A.

Fission product yield data sets are one of the most important and fundamental compilations of basic information in the nuclear industry. This data has a wide range of applications which include nuclear fuel burnup and nonproliferation safeguards. Relative fission yields constitute a major fraction of the reported yield data and reduce the number of required absolute measurements. Radiochemical separations of fission products reduce interferences, facilitate the measurement of low level radionuclides, and are instrumental in the analysis of low-yielding symmetrical fission products. It is especially useful in the measurement of the valley nuclides and those on the extreme wings of the mass yield curve, including lanthanides, where absolute yields have high errors. This overall project was conducted in three stages: characterization of the neutron flux in irradiation positions within the U.S. Geological Survey TRIGA Mark I Reactor (GSTR), determining the mass attenuation coefficients of precipitates used in radiochemical separations, and measuring the relative fission products in the GSTR. Using the Westcott convention, the Westcott flux, modified spectral index, neutron temperature, and gold-based cadmium ratios were determined for various sampling positions in the USGS TRIGA Mark I reactor. The differential neutron energy spectrum measurement was obtained using the computer iterative code SAND-II-SNL. The mass attenuation coefficients for molecular precipitates were determined through experiment and compared to results using the EGS5 Monte Carlo computer code. Difficulties associated with sufficient production of fission product isotopes in research reactors limits the ability to complete a direct, experimental assessment of mass attenuation coefficients for these isotopes. Experimental attenuation coefficients of radioisotopes produced through neutron activation agree well with the EGS5 calculated results. This suggests mass attenuation coefficients of molecular precipitates can be approximated using EGS5, especially in the instance of radioisotopes produced predominantly through uranium fission. Relative fission product yields were determined for three sampling positions in the USGS TRIGA Mark I reactor through radiochemical analysis. The relative mass yield distribution for valley nuclides decreases with epithermal neutrons compared to thermal neutrons. Additionally, a proportionality constant which related the measured beta activity of a fission product to the number of fissions that occur in a sample of irradiated uranium was determined for the detector used in this study and used to determine the thermal and epithermal flux. These values agree well with a previous study which used activation foils to determine the flux. The results of this project clearly demonstrate that R-values can be measured in the GSTR.

Taming Big Data: An Information Extraction Strategy for Large Clinical Text Corpora.

PubMed

Gundlapalli, Adi V; Divita, Guy; Carter, Marjorie E; Redd, Andrew; Samore, Matthew H; Gupta, Kalpana; Trautner, Barbara

2015-01-01

Concepts of interest for clinical and research purposes are not uniformly distributed in clinical text available in electronic medical records. The purpose of our study was to identify filtering techniques to select 'high yield' documents for increased efficacy and throughput. Using two large corpora of clinical text, we demonstrate the identification of 'high yield' document sets in two unrelated domains: homelessness and indwelling urinary catheters. For homelessness, the high yield set includes homeless program and social work notes. For urinary catheters, concepts were more prevalent in notes from hospitalized patients; nursing notes accounted for a majority of the high yield set. This filtering will enable customization and refining of information extraction pipelines to facilitate extraction of relevant concepts for clinical decision support and other uses.

Computing algebraic transfer entropy and coupling directions via transcripts

NASA Astrophysics Data System (ADS)

Amigó, José M.; Monetti, Roberto; Graff, Beata; Graff, Grzegorz

2016-11-01

Most random processes studied in nonlinear time series analysis take values on sets endowed with a group structure, e.g., the real and rational numbers, and the integers. This fact allows to associate with each pair of group elements a third element, called their transcript, which is defined as the product of the second element in the pair times the first one. The transfer entropy of two such processes is called algebraic transfer entropy. It measures the information transferred between two coupled processes whose values belong to a group. In this paper, we show that, subject to one constraint, the algebraic transfer entropy matches the (in general, conditional) mutual information of certain transcripts with one variable less. This property has interesting practical applications, especially to the analysis of short time series. We also derive weak conditions for the 3-dimensional algebraic transfer entropy to yield the same coupling direction as the corresponding mutual information of transcripts. A related issue concerns the use of mutual information of transcripts to determine coupling directions in cases where the conditions just mentioned are not fulfilled. We checked the latter possibility in the lowest dimensional case with numerical simulations and cardiovascular data, and obtained positive results.

The Efficient Utilization of Open Source Information

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

Baty, Samuel R.

These are a set of slides on the efficient utilization of open source information. Open source information consists of a vast set of information from a variety of sources. Not only does the quantity of open source information pose a problem, the quality of such information can hinder efforts. To show this, two case studies are mentioned: Iran and North Korea, in order to see how open source information can be utilized. The huge breadth and depth of open source information can complicate an analysis, especially because open information has no guarantee of accuracy. Open source information can provide keymore » insights either directly or indirectly: looking at supporting factors (flow of scientists, products and waste from mines, government budgets, etc.); direct factors (statements, tests, deployments). Fundamentally, it is the independent verification of information that allows for a more complete picture to be formed. Overlapping sources allow for more precise bounds on times, weights, temperatures, yields or other issues of interest in order to determine capability. Ultimately, a "good" answer almost never comes from an individual, but rather requires the utilization of a wide range of skill sets held by a team of people.« less

Study on an agricultural environment monitoring server system using Wireless Sensor Networks.

PubMed

Hwang, Jeonghwan; Shin, Changsun; Yoe, Hyun

2010-01-01

This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information.

Item Banks for Measuring Emotional Distress From the Patient-Reported Outcomes Measurement Information System (PROMIS®): Depression, Anxiety, and Anger

PubMed Central

Pilkonis, Paul A.; Choi, Seung W.; Reise, Steven P.; Stover, Angela M.; Riley, William T.; Cella, David

2011-01-01

The authors report on the development and calibration of item banks for depression, anxiety, and anger as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®). Comprehensive literature searches yielded an initial bank of 1,404 items from 305 instruments. After qualitative item analysis (including focus groups and cognitive interviewing), 168 items (56 for each construct) were written in a first person, past tense format with a 7-day time frame and five response options reflecting frequency. The calibration sample included nearly 15,000 respondents. Final banks of 28, 29, and 29 items were calibrated for depression, anxiety, and anger, respectively, using item response theory. Test information curves showed that the PROMIS item banks provided more information than conventional measures in a range of severity from approximately −1 to +3 standard deviations (with higher scores indicating greater distress). Short forms consisting of seven to eight items provided information comparable to legacy measures containing more items. PMID:21697139

Item banks for measuring emotional distress from the Patient-Reported Outcomes Measurement Information System (PROMIS®): depression, anxiety, and anger.

PubMed

Pilkonis, Paul A; Choi, Seung W; Reise, Steven P; Stover, Angela M; Riley, William T; Cella, David

2011-09-01

The authors report on the development and calibration of item banks for depression, anxiety, and anger as part of the Patient-Reported Outcomes Measurement Information System (PROMIS®). Comprehensive literature searches yielded an initial bank of 1,404 items from 305 instruments. After qualitative item analysis (including focus groups and cognitive interviewing), 168 items (56 for each construct) were written in a first person, past tense format with a 7-day time frame and five response options reflecting frequency. The calibration sample included nearly 15,000 respondents. Final banks of 28, 29, and 29 items were calibrated for depression, anxiety, and anger, respectively, using item response theory. Test information curves showed that the PROMIS item banks provided more information than conventional measures in a range of severity from approximately -1 to +3 standard deviations (with higher scores indicating greater distress). Short forms consisting of seven to eight items provided information comparable to legacy measures containing more items.

Spatial planning using probabilistic flood maps

NASA Astrophysics Data System (ADS)

Alfonso, Leonardo; Mukolwe, Micah; Di Baldassarre, Giuliano

2015-04-01

Probabilistic flood maps account for uncertainty in flood inundation modelling and convey a degree of certainty in the outputs. Major sources of uncertainty include input data, topographic data, model structure, observation data and parametric uncertainty. Decision makers prefer less ambiguous information from modellers; this implies that uncertainty is suppressed to yield binary flood maps. Though, suppressing information may potentially lead to either surprise or misleading decisions. Inclusion of uncertain information in the decision making process is therefore desirable and transparent. To this end, we utilise the Prospect theory and information from a probabilistic flood map to evaluate potential decisions. Consequences related to the decisions were evaluated using flood risk analysis. Prospect theory explains how choices are made given options for which probabilities of occurrence are known and accounts for decision makers' characteristics such as loss aversion and risk seeking. Our results show that decision making is pronounced when there are high gains and loss, implying higher payoffs and penalties, therefore a higher gamble. Thus the methodology may be appropriately considered when making decisions based on uncertain information.

Closing the N-use efficiency gap to achieve food and environmental security.

PubMed

Cui, Zhenling; Wang, Guiliang; Yue, Shanchao; Wu, Liang; Zhang, Weifeng; Zhang, Fusuo; Chen, Xinping

2014-05-20

To achieve food and environmental security, closing the gap between actual and attainable N-use efficiency should be as important as closing yield gaps. Using a meta-analysis of 205 published studies from 317 study sites, including 1332 observations from rice, wheat, and maize system in China, reactive N (Nr) losses, and total N2O emissions from N fertilization both increased exponentially with increasing N application rate. On the basis of the N loss response curves from the literature meta-analysis, the direct N2O emission, NH3 volatilization, N leaching, and N runoff, and total N2O emission (direct + indirect) were calculated using information from the survey of farmers. The PFP-N (kilogram of harvested product per kilogram of N applied (kg (kg of N)(-1))) for 6259 farmers were relative low with only 37, 23, and 32 kg (kg of N)(-1) for rice, wheat, and maize systems, respectively. In comparison, the PFP-N for highest yield and PFP-N group (refers to fields where the PFP-N was within the 80-100th percentile among those fields that achieved yields within the 80-100th percentile) averaged 62, 42, and 53 kg (kg of N)(-1) for rice, wheat, and maize systems, respectively. The corresponding grain yield would increase by 1.6-2.3 Mg ha(-1), while the N application rate would be reduced by 56-100 kg of N ha(-1) from average farmer field to highest yield and PFP-N group. In return, the Nr loss intensity (4-11 kg of N (Mg of grain)(-1)) and total N2O emission intensity (0.15-0.29 kg of N (Mg of grain)(-1)) would both be reduced significantly as compared to current agricultural practices. In many circumstances, closing the PFP-N gap in intensive cropping systems is compatible with increased crop productivity and reductions in both Nr losses and total N2O emissions.

An efficient scan diagnosis methodology according to scan failure mode for yield enhancement

NASA Astrophysics Data System (ADS)

Kim, Jung-Tae; Seo, Nam-Sik; Oh, Ghil-Geun; Kim, Dae-Gue; Lee, Kyu-Taek; Choi, Chi-Young; Kim, InSoo; Min, Hyoung Bok

2008-12-01

Yield has always been a driving consideration during fabrication of modern semiconductor industry. Statistically, the largest portion of wafer yield loss is defective scan failure. This paper presents efficient failure analysis methods for initial yield ramp up and ongoing product with scan diagnosis. Result of our analysis shows that more than 60% of the scan failure dies fall into the category of shift mode in the very deep submicron (VDSM) devices. However, localization of scan shift mode failure is very difficult in comparison to capture mode failure because it is caused by the malfunction of scan chain. Addressing the biggest challenge, we propose the most suitable analysis method according to scan failure mode (capture / shift) for yield enhancement. In the event of capture failure mode, this paper describes the method that integrates scan diagnosis flow and backside probing technology to obtain more accurate candidates. We also describe several unique techniques, such as bulk back-grinding solution, efficient backside probing and signal analysis method. Lastly, we introduce blocked chain analysis algorithm for efficient analysis of shift failure mode. In this paper, we contribute to enhancement of the yield as a result of the combination of two methods. We confirm the failure candidates with physical failure analysis (PFA) method. The direct feedback of the defective visualization is useful to mass-produce devices in a shorter time. The experimental data on mass products show that our method produces average reduction by 13.7% in defective SCAN & SRAM-BIST failure rates and by 18.2% in wafer yield rates.

A review and rationalisation of journal subscriptions undertaken by a library and information service in a mental health trust in north-east England in 2009.

PubMed

Steele, Rachel

2011-12-01

To describe the methods and processes used in an evaluation of local journal subscriptions in a mental health trust and to suggest possible further areas of investigation were similar exercises to be undertaken again. Results from a user questionnaire were analysed along with e-journal usage statistics and data from local document supply activity. Journal reviews can yield surprising results. Carrying out a user survey is valuable in highlighting awareness of e-resources more generally and thus in providing evidence for marketing/information literacy initiatives. Future journal reviews should undertake impact analysis as potent evidence for continued expenditure on journals in this age of austerity. © 2011 The authors. Health Information and Libraries Journal © 2011 Health Libraries Group.

Application of a rising plate meter to estimate forage yield on dairy farms in Pennsylvania

USDA-ARS?s Scientific Manuscript database

Accurately assessing pasture forage yield is necessary for producers who want to budget feed expenses and make informed pasture management decisions. Clipping and weighing forage from a known area is a direct method to measure pasture forage yield, however it is time consuming. The rising plate mete...

Harvesting number and timing effects on shoot yield and flavonoid content in American skullcap (Scutellaria lateriflora)

USDA-ARS?s Scientific Manuscript database

Information on optimal management practices for high dry matter and flavonoid yield in American skullcap is lacking. A field experiment was conducted in central Alabama to determine the effect of timing and frequency of harvest on shoot yield and flavonoid content of American skullcap. In the first ...

Comprehensive Genetic Characterization of Intraprostatic Chronic Inflammation and Prostate Cancer in African American Men

DTIC Science & Technology

2017-09-01

with new methodologies of intratumoral phylogenetic analyses, will yield pivotal information in elucidating the key genes involved evolution of PCa...combined with both clinical and experimental genetic data produced by this study may empower patients and doctors to make personalized treatment decisions...sequencing, paired with new methodologies of intratumoral phylogenetic analyses, will yield pivotal information in elucidating the key genes involved

Naval Weapons Station Earle Reassessment

DTIC Science & Technology

2013-12-01

property, or site is understood and its meaning (and ultimately its significance) within prehistory or history is made clear” (NPS 1991). A historic...components may lack individual distinction; or D. Information Potential—yielded, or is likely to yield, information important in prehistory or history...period in history or prehistory . Feeling Feeling is a property’s expression of the aesthetic or historic sense of a particular time period. Association

Incorporation of MRI-AIF Information For Improved Kinetic Modelling of Dynamic PET Data

NASA Astrophysics Data System (ADS)

Sari, Hasan; Erlandsson, Kjell; Thielemans, Kris; Atkinson, David; Ourselin, Sebastien; Arridge, Simon; Hutton, Brian F.

2015-06-01

In the analysis of dynamic PET data, compartmental kinetic analysis methods require an accurate knowledge of the arterial input function (AIF). Although arterial blood sampling is the gold standard of the methods used to measure the AIF, it is usually not preferred as it is an invasive method. An alternative method is the simultaneous estimation method (SIME), where physiological parameters and the AIF are estimated together, using information from different anatomical regions. Due to the large number of parameters to estimate in its optimisation, SIME is a computationally complex method and may sometimes fail to give accurate estimates. In this work, we try to improve SIME by utilising an input function derived from a simultaneously obtained DSC-MRI scan. With the assumption that the true value of one of the six parameter PET-AIF model can be derived from an MRI-AIF, the method is tested using simulated data. The results indicate that SIME can yield more robust results when the MRI information is included with a significant reduction in absolute bias of Ki estimates.

An Interoperable, Agricultural Information System Based on Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Teng, William; Chiu, Long; Doraiswamy, Paul; Kempler, Steven; Liu, Zhong; Pham, Long; Rui, Hualan

2005-01-01

Monitoring global agricultural crop conditions during the growing season and estimating potential seasonal production are critically important for market development of US. agricultural products and for global food security. The Goddard Space Flight Center Earth Sciences Data and Information Services Center Distributed Active Archive Center (GES DISC DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide satellite remote sensing data products (e.g., rainfall) and services. The data products will include crop condition and yield prediction maps, generated from a crop growth model with satellite data inputs, in collaboration with the USDA Agricultural Research Service. The AIS will enable the remote, interoperable access to distributed data, by using the GrADS-DODS Server (GDS) and by being compliant with Open GIS Consortium standards. Users will be able to download individual files, perform interactive online analysis, as well as receive operational data flows. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as those of the USDA Foreign Agricultural Service and the U.N. World Food Program.

Robust high-resolution quantification of time signals encoded by in vivo magnetic resonance spectroscopy

NASA Astrophysics Data System (ADS)

Belkić, Dževad; Belkić, Karen

2018-01-01

This paper on molecular imaging emphasizes improving specificity of magnetic resonance spectroscopy (MRS) for early cancer diagnostics by high-resolution data analysis. Sensitivity of magnetic resonance imaging (MRI) is excellent, but specificity is insufficient. Specificity is improved with MRS by going beyond morphology to assess the biochemical content of tissue. This is contingent upon accurate data quantification of diagnostically relevant biomolecules. Quantification is spectral analysis which reconstructs chemical shifts, amplitudes and relaxation times of metabolites. Chemical shifts inform on electronic shielding of resonating nuclei bound to different molecular compounds. Oscillation amplitudes in time signals retrieve the abundance of MR sensitive nuclei whose number is proportional to metabolite concentrations. Transverse relaxation times, the reciprocal of decay probabilities of resonances, arise from spin-spin coupling and reflect local field inhomogeneities. In MRS single voxels are used. For volumetric coverage, multi-voxels are employed within a hybrid of MRS and MRI called magnetic resonance spectroscopic imaging (MRSI). Common to MRS and MRSI is encoding of time signals and subsequent spectral analysis. Encoded data do not provide direct clinical information. Spectral analysis of time signals can yield the quantitative information, of which metabolite concentrations are the most clinically important. This information is equivocal with standard data analysis through the non-parametric, low-resolution fast Fourier transform and post-processing via fitting. By applying the fast Padé transform (FPT) with high-resolution, noise suppression and exact quantification via quantum mechanical signal processing, advances are made, presented herein, focusing on four areas of critical public health importance: brain, prostate, breast and ovarian cancers.

Persistence of Space Radiation Induced Cytogenetic Damage in the Blood Lymphocytes of Astronauts

NASA Technical Reports Server (NTRS)

George, Kerry; Cucinotta, Francis A.

2008-01-01

Cytogenetic damage in astronaut's peripheral blood lymphocytes is a useful in vivo marker of space radiation induced damage. Moreover, if radiation induced chromosome translocations persist in peripheral blood lymphocytes for many years, as has been assumed, they could potentially be used to measure retrospective doses or prolonged low dose rate exposures. However, as more data becomes available, evidence suggests that the yield of translocations may decline with time after exposure, at least in the case of space radiation exposures. We present our latest follow-up measurements of chromosome aberrations in astronauts blood lymphocytes assessed by FISH painting and collected a various times beginning directly after return from space to several years after flight. For most individuals the analysis of individual time-courses for translocations revealed a temporal decline of yields with different half-lives. Since the level of stable aberrations depends on the interplay between natural loss of circulating T-lymphocytes and replenishment from the stem or progenitor cells, the differences in the rates of decay could be explained by inter-individual variation in lymphocyte turn over. Biodosimetry estimates derived from cytogenetic analysis of samples collected a few days after return to earth lie within the range expected from physical dosimetry. However, a temporal decline in yields may indicate complications with the use of stable aberrations for retrospective dose reconstruction, and the differences in the decay time may reflect individual variability in risk from space radiation exposure. In addition, limited data on multiple flights show a lack of correlation between time in space and translocation yields. Data from one crewmember who has participated in two separate long-duration space missions and has been followed up for over 10 years provides limited information on the effect of repeat flights and show a possible adaptive response to space radiation exposure.

Channel morphology and bed-load yield in fluvial, formerly-glaciated headwater streams of the Columbia Mountains, Canada

NASA Astrophysics Data System (ADS)

Green, K. C.; Brardinoni, F.; Alila, Y.

2013-04-01

This study examines channel-reach morphology and bedload yield dynamics in relation to landscape structure and snowmelt hydrology in headwater streams of the Columbia Mountains, Canada. Data collection relies on field surveys and geographic information systems analysis in conjunction with a nested monitoring network of water discharge and bedload transfer. The landscape is characterized by subdued, formerly-glaciated upland topography in which the geomorphic significance of landslides and debris flows is negligible and fluvial processes prevail. While the spatial organization of channel morphology is chiefly controlled by glacially imposed local slope in conjunction with wood abundance and availability of glacigenic deposits, downstream patterns of the coarse grain-size fraction, bankfull width, bankfull depth, and stream power are all insensitive to systematic changes of local slope along the typically stepped long profiles. This is an indication that these alluvial systems have adjusted to the contemporary snowmelt-driven water and sediment transport regimes, and as such are able to compensate for the glacially-imposed boundary conditions. Bedload specific yield increases with drainage area suggesting that fluvial re-mobilization of glacial and paraglacial deposits dominate the sedimentary dynamics of basins as small as 2 km2. Stepwise multiple regression analysis shows that annual rates of sediment transfer are mainly controlled by the number of peak events over threshold discharge. During such events, repeated destabilization of channel bed armoring and re-mobilization of sediment temporarily stored behind LWD structures can generate bedload transport across the entire snowmelt season. In particular, channel morphology controls the variability of bedload response to hydrologic forcing. In the present case studies, we show that the observed spatial variability in annual bedload yield appears to be modulated by inter-basin differences in morphometric characteristics, among which slope aspect plays a critical part.

Projecting Future Land Use Changes in West Africa Driven by Climate and Socioeconomic Factors: Uncertainties and Implications for Adaptation

NASA Astrophysics Data System (ADS)

Wang, G.; Ahmed, K. F.; You, L.

2015-12-01

Land use changes constitute an important regional climate change forcing in West Africa, a region of strong land-atmosphere coupling. At the same time, climate change can be an important driver for land use, although its importance relative to the impact of socio-economic factors may vary significant from region to region. This study compares the contributions of climate change and socioeconomic development to potential future changes of agricultural land use in West Africa and examines various sources of uncertainty using a land use projection model (LandPro) that accounts for the impact of socioeconomic drivers on the demand side and the impact of climate-induced crop yield changes on the supply side. Future crop yield changes were simulated by a process-based crop model driven with future climate projections from a regional climate model, and future changes of food demand is projected using a model for policy analysis of agricultural commodities and trade. The impact of human decision-making on land use was explicitly considered through multiple "what-if" scenarios to examine the range of uncertainties in projecting future land use. Without agricultural intensification, the climate-induced decrease of crop yield together with increase of food demand are found to cause a significant increase in agricultural land use at the expense of forest and grassland by the mid-century, and the resulting land use land cover changes are found to feed back to the regional climate in a way that exacerbates the negative impact of climate on crop yield. Analysis of results from multiple decision-making scenarios suggests that human adaptation characterized by science-informed decision making to minimize land use could be very effective in many parts of the region.

Assessing the biophysical and socio-economic potential of Sustainable Land Management and Water Harvesting Technologies for rainfed agriculture across semi-arid Africa.

NASA Astrophysics Data System (ADS)

Irvine, Brian; Fleskens, Luuk; Kirkby, Mike

2016-04-01

Stakeholders in recent EU projects identified soil erosion as the most frequent driver of land degradation in semi-arid environments. In a number of sites, historic land management and rainfall variability are recognised as contributing to the serious environmental impact. In order to consider the potential of sustainable land management and water harvesting techniques stakeholders and study sites from the projects selected and trialled both local technologies and promising technologies reported from other sites . The combined PESERA and DESMICE modelling approach considered the regional effects of the technologies in combating desertification both in environmental and socio-economical terms. Initial analysis was based on long term average climate data with the model run to equilibrium. Current analysis, primarily based on the WAHARA study sites considers rainfall variability more explicitly in time series mode. The PESERA-DESMICE approach considers the difference between a baseline scenario and a (water harvesting) technology scenario, typically, in terms of productivity, financial viability and scope for reducing erosion risk. A series of 50 year rainfall realisations are generated from observed data to capture a full range of the climatic variability. Each realisation provides a unique time-series of rainfall and through modelling can provide a simulated time-series of crop yield and erosion risk for both baseline conditions and technology scenarios. Subsequent realisations and model simulations add to an envelope of the potential crop yield and cost-benefit relations. The development of such envelopes helps express the agricultural and erosional risk associated with climate variability and the potential for conservation measures to absorb the risk, highlighting the probability of achieving a given crop yield or erosion limit. Information that can directly inform or influence the local adoption of conservation measures under the climatic variability in semi-arid areas

Combinatorial life cycle assessment to inform process design of industrial production of algal biodiesel.

PubMed

Brentner, Laura B; Eckelman, Matthew J; Zimmerman, Julie B

2011-08-15

The use of algae as a feedstock for biodiesel production is a rapidly growing industry, in the United States and globally. A life cycle assessment (LCA) is presented that compares various methods, either proposed or under development, for algal biodiesel to inform the most promising pathways for sustainable full-scale production. For this analysis, the system is divided into five distinct process steps: (1) microalgae cultivation, (2) harvesting and/or dewatering, (3) lipid extraction, (4) conversion (transesterification) into biodiesel, and (5) byproduct management. A number of technology options are considered for each process step and various technology combinations are assessed for their life cycle environmental impacts. The optimal option for each process step is selected yielding a best case scenario, comprised of a flat panel enclosed photobioreactor and direct transesterification of algal cells with supercritical methanol. For a functional unit of 10 GJ biodiesel, the best case production system yields a cumulative energy demand savings of more than 65 GJ, reduces water consumption by 585 m(3) and decreases greenhouse gas emissions by 86% compared to a base case scenario typical of early industrial practices, highlighting the importance of technological innovation in algae processing and providing guidance on promising production pathways.

A Large-Scale Design Integration Approach Developed in Conjunction with the Ares Launch Vehicle Program

NASA Technical Reports Server (NTRS)

Redmon, John W.; Shirley, Michael C.; Kinard, Paul S.

2012-01-01

This paper presents a method for performing large-scale design integration, taking a classical 2D drawing envelope and interface approach and applying it to modern three dimensional computer aided design (3D CAD) systems. Today, the paradigm often used when performing design integration with 3D models involves a digital mockup of an overall vehicle, in the form of a massive, fully detailed, CAD assembly; therefore, adding unnecessary burden and overhead to design and product data management processes. While fully detailed data may yield a broad depth of design detail, pertinent integration features are often obscured under the excessive amounts of information, making them difficult to discern. In contrast, the envelope and interface method results in a reduction in both the amount and complexity of information necessary for design integration while yielding significant savings in time and effort when applied to today's complex design integration projects. This approach, combining classical and modern methods, proved advantageous during the complex design integration activities of the Ares I vehicle. Downstream processes, benefiting from this approach by reducing development and design cycle time, include: Creation of analysis models for the Aerodynamic discipline; Vehicle to ground interface development; Documentation development for the vehicle assembly.

A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study.

PubMed

Kaplan, David; Chen, Jianshen

2012-07-01

A two-step Bayesian propensity score approach is introduced that incorporates prior information in the propensity score equation and outcome equation without the problems associated with simultaneous Bayesian propensity score approaches. The corresponding variance estimators are also provided. The two-step Bayesian propensity score is provided for three methods of implementation: propensity score stratification, weighting, and optimal full matching. Three simulation studies and one case study are presented to elaborate the proposed two-step Bayesian propensity score approach. Results of the simulation studies reveal that greater precision in the propensity score equation yields better recovery of the frequentist-based treatment effect. A slight advantage is shown for the Bayesian approach in small samples. Results also reveal that greater precision around the wrong treatment effect can lead to seriously distorted results. However, greater precision around the correct treatment effect parameter yields quite good results, with slight improvement seen with greater precision in the propensity score equation. A comparison of coverage rates for the conventional frequentist approach and proposed Bayesian approach is also provided. The case study reveals that credible intervals are wider than frequentist confidence intervals when priors are non-informative.

Effects of feeding organic trace minerals on milk production and reproductive performance in lactating dairy cows: a meta-analysis.

PubMed

Rabiee, A R; Lean, I J; Stevenson, M A; Socha, M T

2010-09-01

The objectives of this meta-analysis were to evaluate the effectiveness of supplementation with the organic trace minerals (OTM; Availa-4 and 4-Plex, Zinpro Corp., Eden Prairie, MN) on milk yield, composition, and component yields and reproductive performance in dairy cows. Twenty research papers and reports on the effects of OTM were considered in this meta-analysis. Criteria for inclusion in the study were information on the form of OTM, an adequate description of randomization, production and reproduction data, and associated measures of variance (SE or SD) and P-values. The OTM increased milk production by 0.93 kg [95% confidence interval (CI)=0.61 to 1.25], milk fat by 0.04 kg (95% CI=0.02 to 0.05), and milk protein by 0.03 kg (95% CI=0.02 to 0.04) per day. Milk SCC was not different in cows supplemented with OTM. All production outcomes except milk solids (yield) and milk SCC were heterogeneous. Meta-regression analysis showed that feeding before calving, feeding for a full lactation after calving, and the use of other supplements increased responses over feeding after calving only, feeding for part of lactation, or not using other supplements, respectively. Supplementation of cows with OTM reduced days open (weighted mean difference=13.5 d) and number of services per conception (weighted mean difference=0.27) in lactating dairy cows. The risk of pregnancy on d 150 of lactation was greater in cows fed OTM (risk ratio=1.07), but OTM had no significant effect on the interval from calving to first service and 21-d pregnancy rate. There was no evidence of heterogeneity for any of the reproductive outcomes evaluated. The results of this meta-analysis showed that organic trace mineral supplementation could improve production and reproduction in lactating dairy cows. Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A protocol for pressurized liquid extraction and processing methods to isolate modern and ancient bone cholesterol for compound-specific stable isotope analysis.

PubMed

Laffey, Ann O; Krigbaum, John; Zimmerman, Andrew R

2017-02-15

Bone lipid compound-specific isotope analysis (CSIA) and bone collagen and apatite stable isotope ratio analysis are important sources of ecological and paleodietary information. Pressurized liquid extraction (PLE) is quicker and utilizes less solvent than traditional methods of lipid extraction such as soxhlet and ultrasonication. This study facilitates dietary analysis by optimizing and testing a standardized methodology for PLE of bone cholesterol. Modern and archaeological bones were extracted by PLE using varied temperatures, solvent solutions, and sample weights. The efficiency of PLE was assessed via quantification of cholesterol yields. Stable isotopic ratio integrity was evaluated by comparing isotopic signatures (δ 13 C and δ 18 O values) of cholesterol derived from whole bone, bone collagen and bone apatite. Gas chromatography/mass spectrometry (GC/MS) and gas chromatography isotope ratio mass spectrometry (GC/IRMS) were conducted on purified collagen and lipid extracts to assess isotopic responses to PLE. Lipid yield was optimized at two PLE extraction cycles of 75 °C using dichloromethane/methanol (2:1 v/v) as a solvent with 0.25-0.75 g bone sample. Following lipid extraction, saponification combined with the derivatization of the neutral fraction using trimethylsilylation yielded nearly twice the cholesterol of non-saponified or non-derivatized samples. It was also found that lipids extracted from purified bone collagen and apatite could be used for cholesterol CSIA. There was no difference in the bulk δ 13 C values of collagen extracted from bone with or without lipid. However, there was a significant depletion in 18 O of bone apatite due to lipid presence or processing. These results should assist sample selection and provide an effective, alternative extraction method for bone cholesterol that may be used for isotopic and paleodietary analysis. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

How yield relates to ash content, Δ13C and Δ18O in maize grown under different water regimes

PubMed Central

Cabrera-Bosquet, Llorenç; Sánchez, Ciro; Araus, José Luis

2009-01-01

Background and Aims Stable isotopes have proved a valuable phenotyping tool when breeding for yield potential and drought adaptation; however, the cost and technical skills involved in isotope analysis limit its large-scale application in breeding programmes. This is particularly so for Δ18O despite the potential relevance of this trait in C4 crops. The accumulation of minerals (measured as ash content) has been proposed as an inexpensive way to evaluate drought adaptation and yield in C3 cereals, but little is known of the usefulness of this measure in C4 cereals such as maize (Zea mays). The present study investigates how yield relates to ash content, Δ13C and Δ18O, and evaluates the use of ash content as an alternative or complementary criterion to stable isotopes in assessing yield potential and drought resistance in maize. Methods A set of tropical maize hybrids developed by CIMMYT were subjected to different water availabilities, in order to induce water stress during the reproductive stages under field conditions. Ash content and Δ13C were determined in leaves and kernels. In addition, Δ18O was measured in kernels. Key Results Water regime significantly affected yield, ash content and stable isotopes. The results revealed a close relationship between ash content in leaves and the traits informing about plant water status. Ash content in kernels appeared to reflect differences in sink–source balance. Genotypic variation in grain yield was mainly explained by the combination of ash content and Δ18O, whilst Δ13C did not explain a significant percentage of such variation. Conclusions Ash content in leaves and kernels proved a useful alternative or complementary criterion to Δ18O in kernels for assessing yield performance in maize grown under drought conditions. PMID:19773272

Information theory analysis of Australian humpback whale song.

PubMed

Miksis-Olds, Jennifer L; Buck, John R; Noad, Michael J; Cato, Douglas H; Stokes, M Dale

2008-10-01

Songs produced by migrating whales were recorded off the coast of Queensland, Australia, over six consecutive weeks in 2003. Forty-eight independent song sessions were analyzed using information theory techniques. The average length of the songs estimated by correlation analysis was approximately 100 units, with song sessions lasting from 300 to over 3100 units. Song entropy, a measure of structural constraints, was estimated using three different methodologies: (1) the independently identically distributed model, (2) a first-order Markov model, and (3) the nonparametric sliding window match length (SWML) method, as described by Suzuki et al. [(2006). "Information entropy of humpback whale song," J. Acoust. Soc. Am. 119, 1849-1866]. The analysis finds that the song sequences of migrating Australian whales are consistent with the hierarchical structure proposed by Payne and McVay [(1971). "Songs of humpback whales," Science 173, 587-597], and recently supported mathematically by Suzuki et al. (2006) for singers on the Hawaiian breeding grounds. Both the SWML entropy estimates and the song lengths for the Australian singers in 2003 were lower than that reported by Suzuki et al. (2006) for Hawaiian whales in 1976-1978; however, song redundancy did not differ between these two populations separated spatially and temporally. The average total information in the sequence of units in Australian song was approximately 35 bits/song. Aberrant songs (8%) yielded entropies similar to the typical songs.

Type 2 Diabetes Research Yield, 1951-2012: Bibliometrics Analysis and Density-Equalizing Mapping

PubMed Central

Geaney, Fiona; Scutaru, Cristian; Kelly, Clare; Glynn, Ronan W.; Perry, Ivan J.

2015-01-01

The objective of this paper is to provide a detailed evaluation of type 2 diabetes mellitus research output from 1951-2012, using large-scale data analysis, bibliometric indicators and density-equalizing mapping. Data were retrieved from the Science Citation Index Expanded database, one of the seven curated databases within Web of Science. Using Boolean operators "OR", "AND" and "NOT", a search strategy was developed to estimate the total number of published items. Only studies with an English abstract were eligible. Type 1 diabetes and gestational diabetes items were excluded. Specific software developed for the database analysed the data. Information including titles, authors’ affiliations and publication years were extracted from all files and exported to excel. Density-equalizing mapping was conducted as described by Groenberg-Kloft et al, 2008. A total of 24,783 items were published and cited 476,002 times. The greatest number of outputs were published in 2010 (n=2,139). The United States contributed 28.8% to the overall output, followed by the United Kingdom (8.2%) and Japan (7.7%). Bilateral cooperation was most common between the United States and United Kingdom (n=237). Harvard University produced 2% of all publications, followed by the University of California (1.1%). The leading journals were Diabetes, Diabetologia and Diabetes Care and they contributed 9.3%, 7.3% and 4.0% of the research yield, respectively. In conclusion, the volume of research is rising in parallel with the increasing global burden of disease due to type 2 diabetes mellitus. Bibliometrics analysis provides useful information to scientists and funding agencies involved in the development and implementation of research strategies to address global health issues. PMID:26208117

Music of the 7Ts: Predicting and Decoding Multivoxel fMRI Responses with Acoustic, Schematic, and Categorical Music Features

PubMed Central

Casey, Michael A.

2017-01-01

Underlying the experience of listening to music are parallel streams of auditory, categorical, and schematic qualia, whose representations and cortical organization remain largely unresolved. We collected high-field (7T) fMRI data in a music listening task, and analyzed the data using multivariate decoding and stimulus-encoding models. Twenty subjects participated in the experiment, which measured BOLD responses evoked by naturalistic listening to twenty-five music clips from five genres. Our first analysis applied machine classification to the multivoxel patterns that were evoked in temporal cortex. Results yielded above-chance levels for both stimulus identification and genre classification–cross-validated by holding out data from multiple of the stimuli during model training and then testing decoding performance on the held-out data. Genre model misclassifications were significantly correlated with those in a corresponding behavioral music categorization task, supporting the hypothesis that geometric properties of multivoxel pattern spaces underlie observed musical behavior. A second analysis employed a spherical searchlight regression analysis which predicted multivoxel pattern responses to music features representing melody and harmony across a large area of cortex. The resulting prediction-accuracy maps yielded significant clusters in the temporal, frontal, parietal, and occipital lobes, as well as in the parahippocampal gyrus and the cerebellum. These maps provide evidence in support of our hypothesis that geometric properties of music cognition are neurally encoded as multivoxel representational spaces. The maps also reveal a cortical topography that differentially encodes categorical and absolute-pitch information in distributed and overlapping networks, with smaller specialized regions that encode tonal music information in relative-pitch representations. PMID:28769835

A compilation of nuclear weapons test detonation data for U.S. Pacific ocean tests.

PubMed

Simon, S L; Robison, W L

1997-07-01

Prior to December 1993, the explosive yields of 44 of 66 nuclear tests conducted by the United States in the Marshall Islands were still classified. Following a request from the Government of the Republic of the Marshall Islands to the U.S. Department of Energy to release this information, the Secretary of Energy declassified and released to the public the explosive yields of the Pacific nuclear tests. This paper presents a synopsis of information on nuclear test detonations in the Marshall Islands and other locations in the mid-Pacific including dates, explosive yields, locations, weapon placement, and summary statistics.

ENSO and PDO-related climate variability impacts on Midwestern United States crop yields.

PubMed

Henson, Chasity; Market, Patrick; Lupo, Anthony; Guinan, Patrick

2017-05-01

An analysis of crop yields for the state of Missouri was completed to determine if an interannual or multidecadal variability existed as a result of the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). Corn and soybean yields were recorded in kilograms per hectare for each of the six climate regions of Missouri. An analysis using the Mokhov "method of cycles" demonstrated interannual, interdecadal, and multidecadal variations in crop yields. Cross-spectral analysis was used to determine which region was most impacted by ENSO and PDO influenced seasonal (April-September) temperature and precipitation. Interannual (multidecadal) variations found in the spectral analysis represent a relationship to ENSO (PDO) phase, while interdecadal variations represent a possible interaction between ENSO and PDO. Average crop yields were then calculated for each combination of ENSO and PDO phase, displaying a pronounced increase in corn and soybean yields when ENSO is warm and PDO is positive. Climate regions 1, 2, 4, and 6 displayed significant differences (p value of 0.10 or less) in yields between El Niño and La Niña years, representing 55-70 % of Missouri soybean and corn productivity, respectively. Final results give the opportunity to produce seasonal predictions of corn and soybean yields, specific to each climate region in Missouri, based on the combination of ENSO and PDO phases.

(I Can’t Get No) Saturation: A simulation and guidelines for sample sizes in qualitative research

PubMed Central

2017-01-01

I explore the sample size in qualitative research that is required to reach theoretical saturation. I conceptualize a population as consisting of sub-populations that contain different types of information sources that hold a number of codes. Theoretical saturation is reached after all the codes in the population have been observed once in the sample. I delineate three different scenarios to sample information sources: “random chance,” which is based on probability sampling, “minimal information,” which yields at least one new code per sampling step, and “maximum information,” which yields the largest number of new codes per sampling step. Next, I use simulations to assess the minimum sample size for each scenario for systematically varying hypothetical populations. I show that theoretical saturation is more dependent on the mean probability of observing codes than on the number of codes in a population. Moreover, the minimal and maximal information scenarios are significantly more efficient than random chance, but yield fewer repetitions per code to validate the findings. I formulate guidelines for purposive sampling and recommend that researchers follow a minimum information scenario. PMID:28746358

Active sensing: An innovative tool for evaluating grain yield and nitrogen use efficiency of multiple wheat genotypes

NASA Astrophysics Data System (ADS)

Naser, Mohammed Abdulridha

Precision agricultural practices have significantly contributed to the improvement of crop productivity and profitability. Remote sensing based indices, such as Normalized Difference Vegetative Index (NDVI) have been used to obtain crop information. It is used to monitor crop development and to provide rapid and nondestructive estimates of plant biomass, nitrogen (N) content and grain yield. Remote sensing tools are helping improve nitrogen use efficiency (NUE) through nitrogen management and could also be useful for high NUE genotype selection. The objectives of this study were: (i) to determine if active sensor based NDVI readings can differentiate wheat genotypes, (ii) to determine if NDVI readings can be used to classify wheat genotypes into grain yield productivity classes, (iii) to identify and quantify the main sources of variation in NUE across wheat genotypes, and (iv) to determine if normalized difference vegetation index (NDVI) could characterize variability in NUE across wheat genotypes. This study was conducted in north eastern Colorado for two years, 2010 and 2011. The NDVI readings were taken weekly during the winter wheat growing season from March to late June, in 2010 and 2011 and NUE were calculated as partial factor productivity and as partial nitrogen balance at the end of the season. For objectives i and ii, the correlation between NDVI and grain yield was determined using Pearson's product-moment correlation coefficient (r) and linear regression analysis was used to explain the relationship between NDVI and grain yield. The K-means clustering algorithm was used to classify mean NDVI and mean grain yield into three classes. For objectives iii and iv, the parameters related to NUE were also calculated to measure their relative importance in genotypic variation of NUE and power regression analysis between NDVI and NUE was used to characterize the relationship between NDVI and NUE. The results indicate more consistent association between grain yield and NDVI and between NDVI and NUE later in the season, after anthesis and during mid-grain filling stage under dryland and a poor association in wheat grown in irrigated conditions. The results suggest that below saturation of NDVI values (about 0.9), (i.e. prior to full canopy closure and after the beginning of senescence or most of the season under dryland conditions) NDVI could assess grain yield and NUE. The results also indicate that nitrogen uptake efficiency was the main source of variation of NUE among genotypes grown in site-years with lower yield. Overall, results from this study demonstrate that NDVI readings successfully classified wheat genotypes into grain yield classes across dryland and irrigated conditions and characterized variability in NUE across wheat genotypes.

Simplified combustion noise theory yielding a prediction of fluctuating pressure level

NASA Technical Reports Server (NTRS)

Huff, R. G.

1984-01-01

The first order equations for the conservation of mass and momentum in differential form are combined for an ideal gas to yield a single second order partial differential equation in one dimension and time. Small perturbation analysis is applied. A Fourier transformation is performed that results in a second order, constant coefficient, nonhomogeneous equation. The driving function is taken to be the source of combustion noise. A simplified model describing the energy addition via the combustion process gives the required source information for substitution in the driving function. This enables the particular integral solution of the nonhomogeneous equation to be found. This solution multiplied by the acoustic pressure efficiency predicts the acoustic pressure spectrum measured in turbine engine combustors. The prediction was compared with the overall sound pressure levels measured in a CF6-50 turbofan engine combustor and found to be in excellent agreement.

Fast, Low-Cost and Non-Destructive Physico-Chemical Analysis of Virgin Olive Oils Using Near-Infrared Reflectance Spectroscopy

PubMed Central

Garrido-Varo, Ana; Sánchez, María-Teresa; De la Haba, María-José; Torres, Irina; Pérez-Marín, Dolores

2017-01-01

Near-Infrared (NIR) Spectroscopy was used for the non-destructive assessment of physico-chemical quality parameters in olive oil. At the same time, the influence of the sample presentation mode (spinning versus static cup) was evaluated using two spectrophotometers with similar optical characteristics. A total of 478 olive oil samples were used to develop calibration models, testing various spectral signal pre-treatments. The models obtained by applying MPLS regression to spectroscopic data yielded promising results for olive oil quality measurements, particularly for acidity, the peroxide index and alkyl and ethyl ester content. The results obtained indicate that this non-invasive technology can be used successfully by the olive oil sector to categorize olive oils, to detect potential fraud and to provide consumers with more reliable information. Although both sample presentation modes yielded comparable results, equations constructed with samples scanned using the spinning mode provided greater predictive capacity. PMID:29144417

A redox beginning: Which came first phosphoryl, acyl, or electron transfer ?. [Abstract only

NASA Technical Reports Server (NTRS)

Weber, Arthur L.

1994-01-01

Thermodynamic and kinetic information available on the synthesis of prebiotic monomers and polymers will be examined in order to illuminate the prebiotic plausibility of polymer syntheses based on (a) phosphoryl transfer that yields phosphodiester polymers, (b) acyl transfer that gives polyamides, and (c) electron transfer that produces polydisulfide or poly(thio)ester polymers. New experimental results on the oxidative polymerization of 2,3-dimercaptopropanol by ferric ions on the surface of ferric hydroxide oxide will be discussed as a chemical model of polymerization by electron transfer. This redox polymerization that yields polymers with a polydisulfide backbone was found to give oligomers up to the 15-mer from 1 mM of 2,3-dimercaptopropanol after one day at 25 C. High pressure liquid chromatography (HPLC) analysis of the oligomers was carried out on an Alltech OH-100 column eluted with acetonitrile-water.

Near ground level sensing for spatial analysis of vegetation

NASA Technical Reports Server (NTRS)

Sauer, Tom; Rasure, John; Gage, Charlie

1991-01-01

Measured changes in vegetation indicate the dynamics of ecological processes and can identify the impacts from disturbances. Traditional methods of vegetation analysis tend to be slow because they are labor intensive; as a result, these methods are often confined to small local area measurements. Scientists need new algorithms and instruments that will allow them to efficiently study environmental dynamics across a range of different spatial scales. A new methodology that addresses this problem is presented. This methodology includes the acquisition, processing, and presentation of near ground level image data and its corresponding spatial characteristics. The systematic approach taken encompasses a feature extraction process, a supervised and unsupervised classification process, and a region labeling process yielding spatial information.

Biomechanical investigation of naso-orbitoethmoid trauma by finite element analysis.

PubMed

Huempfner-Hierl, Heike; Schaller, Andreas; Hemprich, Alexander; Hierl, Thomas

2014-11-01

Naso-orbitoethmoid fractures account for 5% of all facial fractures. We used data derived from a white 34-year-old man to make a transient dynamic finite element model, which consisted of about 740 000 elements, to simulate fist-like impacts to this anatomically complex area. Finite element analysis showed a pattern of von Mises stresses beyond the yield criterion of bone that corresponded with fractures commonly seen clinically. Finite element models can be used to simulate injuries to the human skull, and provide information about the pathogenesis of different types of fracture. Copyright © 2014 The British Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Using cosmic microwave background radiation analysis tools for flow anisotropies in relativistic heavy-ion collisions

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

Mishra, Ananta P.; Mohapatra, Ranjita K.; Saumia, P. S.

2010-03-15

Recently we have shown that there are crucial similarities in the physics of cosmic microwave background radiation (CMBR) anisotropies and the flow anisotropies in relativistic heavy-ion collision experiments (RHICE). We also argued that, following CMBR anisotropy analysis, a plot of root-mean-square values of the flow coefficients, calculated in a laboratory-fixed frame for RHICE, can yield important information about the nature of initial state anisotropies and their evolution. Here we demonstrate the strength of this technique by showing that elliptic flow for noncentral collisions can be directly determined from such a plot without any need for the determination of the eventmore » plane.« less

On-line multiple component analysis for efficient quantitative bioprocess development.

PubMed

Dietzsch, Christian; Spadiut, Oliver; Herwig, Christoph

2013-02-20

On-line monitoring devices for the precise determination of a multitude of components are a prerequisite for fast bioprocess quantification. On-line measured values have to be checked for quality and consistency, in order to extract quantitative information from these data. In the present study we characterized a novel on-line sampling and analysis device comprising an automatic photometric robot. We connected this on-line device to a bioreactor and concomitantly measured six components (i.e. glucose, glycerol, ethanol, acetate, phosphate and ammonium) during different batch cultivations of Pichia pastoris. The on-line measured data did not show significant deviations from off-line taken samples and were consequently used for incremental rate and yield calculations. In this respect we highlighted the importance of data quality and discussed the phenomenon of error propagation. On-line calculated rates and yields depicted the physiological responses of the P. pastoris cells in unlimited and limited cultures. A more detailed analysis of the physiological state was possible by considering the off-line determined biomass dry weight and the calculation of specific rates. Here we present a novel device for on-line monitoring of bioprocesses, which ensures high data quality in real-time and therefore refers to a valuable tool for Process Analytical Technology (PAT). Copyright © 2012 Elsevier B.V. All rights reserved.

The initial instability and finite-amplitude stability of alternate bars in straight channels

USGS Publications Warehouse

Nelson, J.M.

1990-01-01

The initial instability and fully developed stability of alternate bars in straight channels are investigated using linearized and nonlinear analyses. The fundamental instability leading to these features is identified through a linear stability analysis of the equations governing the flow and sediment transport fields. This instability is explained in terms of topographically induced steering of the flow and the associated pattern of erosion and deposition on the bed. While the linear theory is useful for examining the instability mechanism, this approach is shown to yield relatively little information about well-developed alternate bars and, specifically, the linear analysis is shown to yield poor predictions of the fully developed bar wavelength. A fully nonlinear approach is presented that permits computation of the evolution of these bed features from an initial perturbation to their fully developed morphology. This analysis indicates that there is typically substantial elongation of the bar wavelength during the evolution process, a result that is consistent with observations of bar development in flumes and natural channels. The nonlinear approach demonstrates that the eventual stability of these features is a result of the interplay between topographic steering effects, secondary flow production as a result of streamline curvature, and gravitationally induced modifications of sediment fluxes over a sloping bed. ?? 1990.

Application of an NLME-Stochastic Deconvolution Approach to Level A IVIVC Modeling.

PubMed

Kakhi, Maziar; Suarez-Sharp, Sandra; Shepard, Terry; Chittenden, Jason

2017-07-01

Stochastic deconvolution is a parameter estimation method that calculates drug absorption using a nonlinear mixed-effects model in which the random effects associated with absorption represent a Wiener process. The present work compares (1) stochastic deconvolution and (2) numerical deconvolution, using clinical pharmacokinetic (PK) data generated for an in vitro-in vivo correlation (IVIVC) study of extended release (ER) formulations of a Biopharmaceutics Classification System class III drug substance. The preliminary analysis found that numerical and stochastic deconvolution yielded superimposable fraction absorbed (F abs ) versus time profiles when supplied with exactly the same externally determined unit impulse response parameters. In a separate analysis, a full population-PK/stochastic deconvolution was applied to the clinical PK data. Scenarios were considered in which immediate release (IR) data were either retained or excluded to inform parameter estimation. The resulting F abs profiles were then used to model level A IVIVCs. All the considered stochastic deconvolution scenarios, and numerical deconvolution, yielded on average similar results with respect to the IVIVC validation. These results could be achieved with stochastic deconvolution without recourse to IR data. Unlike numerical deconvolution, this also implies that in crossover studies where certain individuals do not receive an IR treatment, their ER data alone can still be included as part of the IVIVC analysis. Published by Elsevier Inc.

Guidelines for collecting and processing samples of stream bed sediment for analysis of trace elements and organic contaminants for the National Water-Quality Assessment Program

USGS Publications Warehouse

Shelton, Larry R.; Capel, Paul D.

1994-01-01

A major component of the U.S. Geological Survey's National Water-Quality Assessment program is to assess the occurrence and distribution of trace elements and organic contaminants in streams. The first phase of the strategy for the assessment is to analyze samples of bed sediments from depositional zones. Fine-grained particles deposited in these zones are natural accumulators of trace elements and hydrophobic organic compounds. For the information to be comparable among studies in many different parts of the Nation, strategies for selecting stream sites and depositional zones are critical. Fine-grained surficial sediments are obtained from several depositional zones within a stream reach and composited to yield a sample representing average conditions. Sample collection and processing must be done consistently and by procedures specifically designed to separate the fine material into fractions that yield uncontaminated samples for trace-level analytes in the laboratory. Special coring samplers and other instruments made of Teflon are used for collection. Samples are processed through a 2.0-millimeter stainless-steel mesh sieve for organic contaminate analysis and a 63-micrometer nylon-cloth sieve for trace-element analysis. Quality assurance is maintained by strict collection and processing procedures, duplicate samplings, and a rigid cleaning procedure.

Effects of informed consent for individual genome sequencing on relevant knowledge.

PubMed

Kaphingst, K A; Facio, F M; Cheng, M-R; Brooks, S; Eidem, H; Linn, A; Biesecker, B B; Biesecker, L G

2012-11-01

Increasing availability of individual genomic information suggests that patients will need knowledge about genome sequencing to make informed decisions, but prior research is limited. In this study, we examined genome sequencing knowledge before and after informed consent among 311 participants enrolled in the ClinSeq™ sequencing study. An exploratory factor analysis of knowledge items yielded two factors (sequencing limitations knowledge; sequencing benefits knowledge). In multivariable analysis, high pre-consent sequencing limitations knowledge scores were significantly related to education [odds ratio (OR): 8.7, 95% confidence interval (CI): 2.45-31.10 for post-graduate education, and OR: 3.9; 95% CI: 1.05, 14.61 for college degree compared with less than college degree] and race/ethnicity (OR: 2.4, 95% CI: 1.09, 5.38 for non-Hispanic Whites compared with other racial/ethnic groups). Mean values increased significantly between pre- and post-consent for the sequencing limitations knowledge subscale (6.9-7.7, p < 0.0001) and sequencing benefits knowledge subscale (7.0-7.5, p < 0.0001); increase in knowledge did not differ by sociodemographic characteristics. This study highlights gaps in genome sequencing knowledge and underscores the need to target educational efforts toward participants with less education or from minority racial/ethnic groups. The informed consent process improved genome sequencing knowledge. Future studies could examine how genome sequencing knowledge influences informed decision making. © 2012 John Wiley & Sons A/S.

CROMAX : a crosscut-first computer simulation program to determine cutting yield

Treesearch

Pamela J. Giese; Jeanne D. Danielson

1983-01-01

CROMAX simulates crosscut-first, then rip operations as commonly practiced in furniture manufacture. This program calculates cutting yields from individual boards based on board size and defect location. Such information can be useful in predicting yield from various grades and grade mixes thereby allowing for better management decisions in the rough mill. The computer...

Cooperative synchronized assemblies enhance orientation discrimination.

PubMed

Samonds, Jason M; Allison, John D; Brown, Heather A; Bonds, A B

2004-04-27

There is no clear link between the broad tuning of single neurons and the fine behavioral capabilities of orientation discrimination. We recorded from populations of cells in the cat visual cortex (area 17) to examine whether the joint activity of cells can support finer discrimination than found in individual responses. Analysis of joint firing yields a substantial advantage (i.e., cooperation) in fine-angle discrimination. This cooperation increases to more considerable levels as the population of an assembly is increased. The cooperation in a population of six cells provides encoding of orientation with an information advantage that is at least 2-fold in terms of requiring either fewer cells or less time than independent coding. This cooperation suggests that correlated or synchronized activity can increase information.

Correlation, path analysis and heritability estimation for agronomic traits contribute to yield on soybean

NASA Astrophysics Data System (ADS)

Sulistyo, A.; Purwantoro; Sari, K. P.

2018-01-01

Selection is a routine activity in plant breeding programs that must be done by plant breeders in obtaining superior plant genotypes. The use of appropriate selection criteria will determine the effectiveness of selection activities. The purpose of this study was to analysis the inheritable agronomic traits that contribute to soybean yield. A total of 91 soybean lines were planted in Muneng Experimental Station, Probolinggo District, East Java Province, Indonesia in 2016. All soybean lines were arranged in randomized complete block design with two replicates. Correlation analysis, path analysis and heritability estimation were performed on days to flowering, days to maturing, plant height, number of branches, number of fertile nodes, number of filled pods, weight of 100 seeds, and yield to determine selection criteria on soybean breeding program. The results showed that the heritability value of almost all agronomic traits observed is high except for the number of fertile nodes with low heritability. The result of correlation analysis shows that days to flowering, plant height and number of fertile nodes have positive correlation with seed yield per plot (0.056, 0.444, and 0.100, respectively). In addition, path analysis showed that plant height and number of fertile nodes have highest positive direct effect on soybean yield. Based on this result, plant height can be selected as one of selection criteria in soybean breeding program to obtain high yielding soybean variety.

Contrast in Terahertz Images of Archival Documents—Part II: Influence of Topographic Features

NASA Astrophysics Data System (ADS)

Bardon, Tiphaine; May, Robert K.; Taday, Philip F.; Strlič, Matija

2017-04-01

We investigate the potential of terahertz time-domain imaging in reflection mode to reveal archival information in documents in a non-invasive way. In particular, this study explores the parameters and signal processing tools that can be used to produce well-contrasted terahertz images of topographic features commonly found in archival documents, such as indentations left by a writing tool, as well as sieve lines. While the amplitude of the waveforms at a specific time delay can provide the most contrasted and legible images of topographic features on flat paper or parchment sheets, this parameter may not be suitable for documents that have a highly irregular surface, such as water- or fire-damaged documents. For analysis of such documents, cross-correlation of the time-domain signals can instead yield images with good contrast. Analysis of the frequency-domain representation of terahertz waveforms can also provide well-contrasted images of topographic features, with improved spatial resolution when utilising high-frequency content. Finally, we point out some of the limitations of these means of analysis for extracting information relating to topographic features of interest from documents.

Biaxial Testing of 2219-T87 Aluminum Alloy Using Cruciform Specimens

NASA Technical Reports Server (NTRS)

Dawicke, D. S.; Pollock, W. D.

1997-01-01

A cruciform biaxial test specimen was designed and seven biaxial tensile tests were conducted on 2219-T87 aluminum alloy. An elastic-plastic finite element analysis was used to simulate each tests and predict the yield stresses. The elastic-plastic finite analysis accurately simulated the measured load-strain behavior for each test. The yield stresses predicted by the finite element analyses indicated that the yield behavior of the 2219-T87 aluminum alloy agrees with the von Mises yield criterion.

Prediction of sedimentation using integration of RS, RUSLE model and GIS in Cameron Highlands, Pahang, Malaysia

NASA Astrophysics Data System (ADS)

Ghani, A. H. A.; Lihan, T.; Rahim, S. A.; Musthapha, M. A.; Idris, W. M. R.; Rahman, Z. A.

2013-11-01

Soil erosion and sediment yield are strongly affected by land use change. Spatially distributed erosion models are of great interest to predict soil erosion loss and sediment yield. Hence, the objective of this study was to determine sediment yield using Revised Universal Soil Loss Equation (RUSLE) model in Geographical Information System (GIS) environment at Cameron Highlands, Pahang, Malaysia. Sediment yield at the study area was determined using RUSLE model in GIS environment The RUSLE factors were computed by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map and field measurement, vegetation cover (C) using satellite images, length and steepness (LS) using contour map and conservation practices using satellite images based on land use/land cover. Field observations were also done to verify the predicted sediment yield. The results indicated that the rate of sediment yield in the study area ranged from very low to extremely high. The higher SY value can be found at middle and lower catchments of Cameron Highland. Meanwhile, the lower SY value can be found at the north part of the study area. Sediment yield value turned out to be higher close to the river due to the topographic characteristic, vegetation type and density, climate and land use within the drainage basin.

Time-Resolved Transposon Insertion Sequencing Reveals Genome-Wide Fitness Dynamics during Infection.

PubMed

Yang, Guanhua; Billings, Gabriel; Hubbard, Troy P; Park, Joseph S; Yin Leung, Ka; Liu, Qin; Davis, Brigid M; Zhang, Yuanxing; Wang, Qiyao; Waldor, Matthew K

2017-10-03

Transposon insertion sequencing (TIS) is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection). Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE). From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant's fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen) collected over a 2-week infection period from a natural host (the flatfish turbot). PACE uncovered more genes that affect E. piscicida 's fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses. IMPORTANCE Transposon insertion sequencing (TIS) enables genome-wide mapping of the genetic determinants of fitness, typically based on observations at a single sampling point. Here, we move beyond analysis of endpoint TIS data to create a framework for analysis of time series TIS data, termed pattern analysis of conditional essentiality (PACE). We applied PACE to identify genes that contribute to colonization of a natural host by the fish pathogen Edwardsiella piscicida. PACE uncovered more genes that affect E. piscicida 's fitness in vivo than were detected using a terminal sampling point, and its clustering of mutants with related fitness profiles informed design of new live vaccine candidates. PACE yields insights into patterns of fitness dynamics and circumvents major limitations of existing methodologies. Finally, the PACE method should be applicable to additional "omic" time series data, including screens based on clustered regularly interspaced short palindromic repeats with Cas9 (CRISPR/Cas9). Copyright © 2017 Yang et al.

Adaptability and phenotypic stability of common bean genotypes through Bayesian inference.

PubMed

Corrêa, A M; Teodoro, P E; Gonçalves, M C; Barroso, L M A; Nascimento, M; Santos, A; Torres, F E

2016-04-27

This study used Bayesian inference to investigate the genotype x environment interaction in common bean grown in Mato Grosso do Sul State, and it also evaluated the efficiency of using informative and minimally informative a priori distributions. Six trials were conducted in randomized blocks, and the grain yield of 13 common bean genotypes was assessed. To represent the minimally informative a priori distributions, a probability distribution with high variance was used, and a meta-analysis concept was adopted to represent the informative a priori distributions. Bayes factors were used to conduct comparisons between the a priori distributions. The Bayesian inference was effective for the selection of upright common bean genotypes with high adaptability and phenotypic stability using the Eberhart and Russell method. Bayes factors indicated that the use of informative a priori distributions provided more accurate results than minimally informative a priori distributions. According to Bayesian inference, the EMGOPA-201, BAMBUÍ, CNF 4999, CNF 4129 A 54, and CNFv 8025 genotypes had specific adaptability to favorable environments, while the IAPAR 14 and IAC CARIOCA ETE genotypes had specific adaptability to unfavorable environments.

A functional-structural model of rice linking quantitative genetic information with morphological development and physiological processes.

PubMed

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-04-01

Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype-phenotype model, we present here a three-dimensional functional-structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed.

Analysis of the phase transition in the two-dimensional Ising ferromagnet using a Lempel-Ziv string-parsing scheme and black-box data-compression utilities

NASA Astrophysics Data System (ADS)

Melchert, O.; Hartmann, A. K.

2015-02-01

In this work we consider information-theoretic observables to analyze short symbolic sequences, comprising time series that represent the orientation of a single spin in a two-dimensional (2D) Ising ferromagnet on a square lattice of size L2=1282 for different system temperatures T . The latter were chosen from an interval enclosing the critical point Tc of the model. At small temperatures the sequences are thus very regular; at high temperatures they are maximally random. In the vicinity of the critical point, nontrivial, long-range correlations appear. Here we implement estimators for the entropy rate, excess entropy (i.e., "complexity"), and multi-information. First, we implement a Lempel-Ziv string-parsing scheme, providing seemingly elaborate entropy rate and multi-information estimates and an approximate estimator for the excess entropy. Furthermore, we apply easy-to-use black-box data-compression utilities, providing approximate estimators only. For comparison and to yield results for benchmarking purposes, we implement the information-theoretic observables also based on the well-established M -block Shannon entropy, which is more tedious to apply compared to the first two "algorithmic" entropy estimation procedures. To test how well one can exploit the potential of such data-compression techniques, we aim at detecting the critical point of the 2D Ising ferromagnet. Among the above observables, the multi-information, which is known to exhibit an isolated peak at the critical point, is very easy to replicate by means of both efficient algorithmic entropy estimation procedures. Finally, we assess how good the various algorithmic entropy estimates compare to the more conventional block entropy estimates and illustrate a simple modification that yields enhanced results.

A functional–structural model of rice linking quantitative genetic information with morphological development and physiological processes

PubMed Central

Xu, Lifeng; Henke, Michael; Zhu, Jun; Kurth, Winfried; Buck-Sorlin, Gerhard

2011-01-01

Background and Aims Although quantitative trait loci (QTL) analysis of yield-related traits for rice has developed rapidly, crop models using genotype information have been proposed only relatively recently. As a first step towards a generic genotype–phenotype model, we present here a three-dimensional functional–structural plant model (FSPM) of rice, in which some model parameters are controlled by functions describing the effect of main-effect and epistatic QTLs. Methods The model simulates the growth and development of rice based on selected ecophysiological processes, such as photosynthesis (source process) and organ formation, growth and extension (sink processes). It was devised using GroIMP, an interactive modelling platform based on the Relational Growth Grammar formalism (RGG). RGG rules describe the course of organ initiation and extension resulting in final morphology. The link between the phenotype (as represented by the simulated rice plant) and the QTL genotype was implemented via a data interface between the rice FSPM and the QTLNetwork software, which computes predictions of QTLs from map data and measured trait data. Key Results Using plant height and grain yield, it is shown how QTL information for a given trait can be used in an FSPM, computing and visualizing the phenotypes of different lines of a mapping population. Furthermore, we demonstrate how modification of a particular trait feeds back on the entire plant phenotype via the physiological processes considered. Conclusions We linked a rice FSPM to a quantitative genetic model, thereby employing QTL information to refine model parameters and visualizing the dynamics of development of the entire phenotype as a result of ecophysiological processes, including the trait(s) for which genetic information is available. Possibilities for further extension of the model, for example for the purposes of ideotype breeding, are discussed. PMID:21247905

Information-theoretic signatures of biodiversity in the barcoding gene.

PubMed

Barbosa, Valmir C

2018-08-14

Analyzing the information content of DNA, though holding the promise to help quantify how the processes of evolution have led to information gain throughout the ages, has remained an elusive goal. Paradoxically, one of the main reasons for this has been precisely the great diversity of life on the planet: if on the one hand this diversity is a rich source of data for information-content analysis, on the other hand there is so much variation as to make the task unmanageable. During the past decade or so, however, succinct fragments of the COI mitochondrial gene, which is present in all animal phyla and in a few others, have been shown to be useful for species identification through DNA barcoding. A few million such fragments are now publicly available through the BOLD systems initiative, thus providing an unprecedented opportunity for relatively comprehensive information-theoretic analyses of DNA to be attempted. Here we show how a generalized form of total correlation can yield distinctive information-theoretic descriptors of the phyla represented in those fragments. In order to illustrate the potential of this analysis to provide new insight into the evolution of species, we performed principal component analysis on standardized versions of the said descriptors for 23 phyla. Surprisingly, we found that, though based solely on the species represented in the data, the first principal component correlates strongly with the natural logarithm of the number of all known living species for those phyla. The new descriptors thus constitute clear information-theoretic signatures of the processes whereby evolution has given rise to current biodiversity, which suggests their potential usefulness in further related studies. Copyright © 2018 Elsevier Ltd. All rights reserved.

A computational intelligent approach to multi-factor analysis of violent crime information system

NASA Astrophysics Data System (ADS)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Useful ion yields for Cameca IMS 3f and 6f SIMS: Limits on quantitative analysis

USGS Publications Warehouse

Hervig, R.L.; Mazdab, F.K.; Williams, Pat; Guan, Y.; Huss, G.R.; Leshin, L.A.

2006-01-01

The useful yields (ions detected/atom sputtered) of major and trace elements in NIST 610 glass were measured by secondary ion mass spectrometry (SIMS) using Cameca IMS 3f and 6f instruments. Useful yields of positive ions at maximum transmission range from 10-4 to 0.2 and are negatively correlated with ionization potential. We quantified the decrease in useful yields when applying energy filtering or high mass resolution techniques to remove molecular interferences. The useful yields of selected negative ions (O, S, Au) in magnetite and pyrite were also determined. These data allow the analyst to determine if a particular analysis (trace element contents or isotopic ratio) can be achieved, given the amount of sample available and the conditions of the analysis. ?? 2005 Elsevier B.V. All rights reserved.

Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis

PubMed Central

Casadebaig, Pierre; Zheng, Bangyou; Chapman, Scott; Huth, Neil; Faivre, Robert; Chenu, Karine

2016-01-01

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the major most influential inputs, providing the simulation model is a credible description of the biological system. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A large set of traits (90) was evaluated in a wide target population of environments (4 sites × 125 years), management practices (3 sowing dates × 3 nitrogen fertilization levels) and CO2 (2 levels). The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait × environment × management landscape (∼ 82 million individual simulations in total). The patterns of parameter × environment × management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference cultivar. Main (i.e. linear) and interaction (i.e. non-linear and interaction) sensitivity indices calculated for most of APSIM-Wheat parameters allowed the identification of 42 parameters substantially impacting yield in most target environments. Among these, a subset of parameters related to phenology, resource acquisition, resource use efficiency and biomass allocation were identified as potential candidates for crop (and model) improvement. PMID:26799483

Assessment of the Potential Impacts of Wheat Plant Traits across Environments by Combining Crop Modeling and Global Sensitivity Analysis.

PubMed

Casadebaig, Pierre; Zheng, Bangyou; Chapman, Scott; Huth, Neil; Faivre, Robert; Chenu, Karine

2016-01-01

A crop can be viewed as a complex system with outputs (e.g. yield) that are affected by inputs of genetic, physiology, pedo-climatic and management information. Application of numerical methods for model exploration assist in evaluating the major most influential inputs, providing the simulation model is a credible description of the biological system. A sensitivity analysis was used to assess the simulated impact on yield of a suite of traits involved in major processes of crop growth and development, and to evaluate how the simulated value of such traits varies across environments and in relation to other traits (which can be interpreted as a virtual change in genetic background). The study focused on wheat in Australia, with an emphasis on adaptation to low rainfall conditions. A large set of traits (90) was evaluated in a wide target population of environments (4 sites × 125 years), management practices (3 sowing dates × 3 nitrogen fertilization levels) and CO2 (2 levels). The Morris sensitivity analysis method was used to sample the parameter space and reduce computational requirements, while maintaining a realistic representation of the targeted trait × environment × management landscape (∼ 82 million individual simulations in total). The patterns of parameter × environment × management interactions were investigated for the most influential parameters, considering a potential genetic range of +/- 20% compared to a reference cultivar. Main (i.e. linear) and interaction (i.e. non-linear and interaction) sensitivity indices calculated for most of APSIM-Wheat parameters allowed the identification of 42 parameters substantially impacting yield in most target environments. Among these, a subset of parameters related to phenology, resource acquisition, resource use efficiency and biomass allocation were identified as potential candidates for crop (and model) improvement.

A review of dark fermentative hydrogen production from biodegradable municipal waste fractions.

PubMed

De Gioannis, G; Muntoni, A; Polettini, A; Pomi, R

2013-06-01

Hydrogen is believed to play a potentially key role in the implementation of sustainable energy production, particularly when it is produced from renewable sources and low energy-demanding processes. In the present paper an attempt was made at critically reviewing more than 80 recent publications, in order to harmonize and compare the available results from different studies on hydrogen production from FW and OFMSW through dark fermentation, and derive reliable information about process yield and stability in view of building related predictive models. The review was focused on the effect of factors, recognized as potentially affecting process evolution (including type of substrate and co-substrate and relative ratio, type of inoculum, food/microorganisms [F/M] ratio, applied pre-treatment, reactor configuration, temperature and pH), on the fermentation yield and kinetics. Statistical analysis of literature data from batch experiments was also conducted, showing that the variables affecting the H2 production yield were ranked in the order: type of co-substrate, type of pre-treatment, operating pH, control of initial pH and fermentation temperature. However, due to the dispersion of data observed in some instances, the ambiguity about the presence of additional hidden variables cannot be resolved. The results from the analysis thus suggest that, for reliable predictive models of fermentative hydrogen production to be derived, a high level of consistency between data is strictly required, claiming for more systematic and comprehensive studies on the subject. Copyright © 2013 Elsevier Ltd. All rights reserved.

An innovative artificial recharge system to enhance groundwater storage in basaltic terrain: example from Maharashtra, India

NASA Astrophysics Data System (ADS)

Bhusari, Vijay; Katpatal, Y. B.; Kundal, Pradeep

2016-08-01

The management of groundwater poses challenges in basaltic terrain as its availability is not uniform due to the absence of primary porosity. Indiscriminate excessive withdrawal from shallow as well as deep aquifers for meeting increased demand can be higher than natural recharge, causing imbalance in demand and supply and leading to a scarcity condition. An innovative artificial recharge system has been conceived and implemented to augment the groundwater sources at the villages of Saoli and Sastabad in Wardha district of Maharashtra, India. The scheme involves resectioning of a stream bed to achieve a reverse gradient, building a subsurface dam to arrest subsurface flow, and installation of recharge shafts to recharge the deeper aquifers. The paper focuses on analysis of hydrogeological parameters like porosity, specific yield and transmissivity, and on temporal groundwater status. Results indicate that after the construction of the artificial recharge system, a rise of 0.8-2.8 m was recorded in the pre- and post-monsoon groundwater levels in 12 dug wells in the study area; an increase in the yield was also noticed which solved the drinking water and irrigation problems. Spatial analysis was performed using a geographic information system to demarcate the area of influence of the recharge system due to increase in yields of the wells. The study demonstrates efficacy, technical viability and applicability of an innovative artificial recharge system constructed in an area of basaltic terrain prone to water scarcity.

Remote sensing of forest canopy and leaf biochemical contents

NASA Technical Reports Server (NTRS)

Peterson, David L.; Matson, Pamela A.; Card, Don H.; Aber, John D.; Wessman, Carol; Swanberg, Nancy; Spanner, Michael

1988-01-01

Recent research on the remote sensing of forest leaf and canopy biochemical contents suggests that the shortwave IR region contains this information; laboratory analyses of dry ground leaves have yielded reliable predictive relationships between both leaf nitrogen and lignin with near-IR spectra. Attention is given to the application of these laboratory techniques to a limited set of spectra from fresh, whole leaves of conifer species. The analysis of Airborne Imaging Spectrometer data reveals that total water content variations in deciduous forest canopies appear as overall shifts in the brightness of raw spectra.

Sound propagation in a duct of periodic wall structure. [numerical analysis

NASA Technical Reports Server (NTRS)

Kurze, U.

1978-01-01

A boundary condition, which accounts for the coupling in the sections behind the duct boundary, is given for the sound-absorbing duct with a periodic structure of the wall lining and using regular partition walls. The soundfield in the duct is suitably described by the method of differences. For locally active walls this renders an explicit approximate solution for the propagation constant. Coupling may be accounted for by the method of differences in a clear manner. Numerical results agree with measurements and yield information which has technical applications.

Transmission Electron Microscopy Analysis of Skin Lesions from Sporotrichosis Epidemic in Rio de Janeiro, Brazil

PubMed Central

Porto Ferreira, Cassio; Oliveira de Almeida, Ana Cristina; Corte-Real, Suzana

2015-01-01

Transmission electron microscopy can yield useful information in a range of scientific fields; it is capable of imaging at a significantly higher resolution than light microscopes and has been a very useful tool in the identification of morphological changes of the dermis as well as assessment of changes in the extracellular matrix. Our aim is to characterize by electron microscopy the cellular profile of lesions caused by Sporothrix schenckii from the sporotrichosis epidemic in its zoonotic form that occurs in Rio de Janeiro, Brazil. PMID:25653392

Calcium quarks.

PubMed

Niggli, Ernst; Egger, Marcel

2002-05-01

Elementary subcellular Ca2+ signals arising from the opening of single ion channels may offer the possibility to examine the stochastic behavior and the microscopic chemical reaction rates of these channel proteins in their natural environment. Such an analysis can yield detailed information about the molecular function that cannot be derived from recordings obtained from an ensemble of channels. In this review, we summarize experimental evidence suggesting that Ca2+ sparks, elementary Ca2+ signaling events of cardiac and skeletal muscle excitation contraction coupling, may be comprised of a number of smaller Ca2+ signaling events, the Ca2+ quarks.

The Assessment of Climatological Impacts on Agricultural Production and Residential Energy Demand

NASA Astrophysics Data System (ADS)

Cooter, Ellen Jean

The assessment of climatological impacts on selected economic activities is presented as a multi-step, inter -disciplinary problem. The assessment process which is addressed explicitly in this report focuses on (1) user identification, (2) direct impact model selection, (3) methodological development, (4) product development and (5) product communication. Two user groups of major economic importance were selected for study; agriculture and gas utilities. The broad agricultural sector is further defined as U.S.A. corn production. The general category of utilities is narrowed to Oklahoma residential gas heating demand. The CERES physiological growth model was selected as the process model for corn production. The statistical analysis for corn production suggests that (1) although this is a statistically complex model, it can yield useful impact information, (2) as a result of output distributional biases, traditional statistical techniques are not adequate analytical tools, (3) the model yield distribution as a whole is probably non-Gausian, particularly in the tails and (4) there appears to be identifiable weekly patterns of forecasted yields throughout the growing season. Agricultural quantities developed include point yield impact estimates and distributional characteristics, geographic corn weather distributions, return period estimates, decision making criteria (confidence limits) and time series of indices. These products were communicated in economic terms through the use of a Bayesian decision example and an econometric model. The NBSLD energy load model was selected to represent residential gas heating consumption. A cursory statistical analysis suggests relationships among weather variables across the Oklahoma study sites. No linear trend in "technology -free" modeled energy demand or input weather variables which would correspond to that contained in observed state -level residential energy use was detected. It is suggested that this trend is largely the result of non-weather factors such as population and home usage patterns rather than regional climate change. Year-to-year changes in modeled residential heating demand on the order of 10('6) Btu's per household were determined and later related to state -level components of the Oklahoma economy. Products developed include the definition of regional forecast areas, likelihood estimates of extreme seasonal conditions and an energy/climate index. This information is communicated in economic terms through an input/output model which is used to estimate changes in Gross State Product and Household income attributable to weather variability.

Soybean Yield and Heterodera glycines Population Dynamics as Affected by Cultural Practices in Major Production Areas of the United States and Canada

USDA-ARS?s Scientific Manuscript database

Little information is available on the interactive effects of tillage and row spacing on yield of soybean and population dynamics of H. glycines. This study investigated the effects of rotation of soybean and corn, tillage, row spacing, and cultivar on yield of soybean and population dynamics of H. ...

A hybrid framework for assessing maize drought vulnerability in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Kamali, B.; Abbaspour, K. C.; Wehrli, B.; Yang, H.

2017-12-01

Drought has devastating impacts on crop yields. Quantifying drought vulnerability is the first step to better design of mitigation policies. The vulnerability of crop yield to drought has been assessed with different methods, however they lack a standardized base to measure its components and a procedure that facilitates spatial and temporal comparisons. This study attempts to quantify maize drought vulnerability through linking the Drought Exposure Index (DEI) to the Crop Failure Index (CFI). DEI and CFI were defined by fitting probability distribution functions to precipitation and maize yield respectively. To acquire crop drought vulnerability index (CDVI), DEI and CFI were combined in a hybrid framework which classifies CDVI with the same base as DEI and CFI. The analysis were implemented on Sub-Saharan African countries using maize yield simulated with the Environmental Policy Integrated Climate (EPIC) model at 0.5° resolution. The model was coupled with the Sequential Uncertainty Fitting algorithm for calibration at country level. Our results show that Central Africa and those Western African countries located below the Sahelian strip receive higher amount of precipitation, but experience high crop failure. Therefore, they are identified as more vulnerable regions compared to countries such as South Africa, Tanzania, and Kenya. We concluded that our hybrid approach complements information on crop drought vulnerability quantification and can be applied to different regions and scales.

Prediction of winter wheat high yield from remote sensing based model: application in United States and Ukraine

NASA Astrophysics Data System (ADS)

Franch, B.; Vermote, E.; Roger, J. C.; Skakun, S.; Becker-Reshef, I.; Justice, C. O.

2017-12-01

Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. In Becker-Reshef et al. (2010) and Franch et al. (2015) we developed an empirical generalized model for forecasting winter wheat yield. It is based on the relationship between the Normalized Difference Vegetation Index (NDVI) at the peak of the growing season and the Growing Degree Day (GDD) information extracted from NCEP/NCAR reanalysis data. These methods were applied to MODIS CMG data in Ukraine, the US and China with errors around 10%. However, the NDVI is saturated for yield values higher than 4 MT/ha. As a consequence, the model had to be re-calibrated in each country and the validation of the national yields showed low correlation coefficients. In this study we present a new model based on the extrapolation of the pure wheat signal (100% of wheat within the pixel) from MODIS data at 1km resolution and using the Difference Vegetation Index (DVI). The model has been applied to monitor the national yield of winter wheat in the United States and Ukraine from 2001 to 2016.

Credit market Jitters in the course of the financial crisis: A permutation entropy approach in measuring informational efficiency in financial assets

NASA Astrophysics Data System (ADS)

Siokis, Fotios M.

2018-06-01

We explore the evolution of the informational efficiency for specific instruments of the U.S. money, bond and stock exchange markets, prior and after the outbreak of the Great Recession. We utilize the permutation entropy and the complexity-entropy causality plane to rank the time series and measure the degree of informational efficiency. We find that after the credit crunch and the collapse of Lehman Brothers the efficiency level of specific money market instruments' yield falls considerably. This is an evidence of less uncertainty included in predicting the related yields throughout the financial disarray. Similar trend is depicted in the indices of the stock exchange markets but efficiency remains in much higher levels. On the other hand, bond market instruments maintained their efficiency levels even after the outbreak of the crisis, which could be interpreted into greater randomness and less predictability of their yields.

Analysis of the trade-off between high crop yield and low yield instability at the global scale

NASA Astrophysics Data System (ADS)

Ben-Ari, Tamara; Makowski, David

2016-10-01

Yield dynamics of major crops species vary remarkably among continents. Worldwide distribution of cropland influences both the expected levels and the interannual variability of global yields. An expansion of cultivated land in the most productive areas could theoretically increase global production, but also increase global yield instability if the most productive regions are characterized by high interannual yield variability. In this letter, we use portfolio analysis to quantify the tradeoff between the expected values and the interannual variance of global yield. We compute optimal frontiers for four crop species i.e., maize, rice, soybean and wheat and show how the distribution of cropland among large world regions can be optimized to either increase expected global crop production or decrease its interannual variability. We also show that a preferential allocation of cropland in the most productive regions can increase global expected yield at the expense of yield stability. Theoretically, optimizing the distribution of a small fraction of total cultivated areas can help find a good compromise between low instability and high crop yields at the global scale.

Understanding fall meaning and context in marketing balance classes to older adults.

PubMed

Clark, Lauren; Thoreson, Sallie; Goss, Cynthia W; Zimmer, Lorena Marquez; Marosits, Mark; DiGuiseppi, Carolyn

2013-02-01

This study explored older, community-dwelling adults' attitudes and values about proposed church-delivered balance classes for fall prevention. Community observation, group interviews with stakeholders, key informant interviews, and focus groups with church members ≥ 60 years of age were analyzed in two ways: first for inductive themes expressing community sentiment about fall prevention for older adults, then for content useful in creating locally tailored social marketing messages. Four themes expressed perceptions of fall-prevention programming: de-emphasizing fall risk and emphasizing strength and independence, moving older adults out of their "comfort zones" to join classes, identifying relationships to support fall-prevention activities, and considering gender-based differences in approaches to fall prevention. A content analysis of the same dataset yielded information about preferred places in the community, promotion through churches, a tolerable price, and the balance class product itself. The qualitative results will inform the social marketing program to increase intervention delivery success.

Assessing the utility of autofluorescence-based pulmonary optical endomicroscopy to predict the malignant potential of solitary pulmonary nodules in humans

NASA Astrophysics Data System (ADS)

Seth, Sohan; Akram, Ahsan R.; McCool, Paul; Westerfeld, Jody; Wilson, David; McLaughlin, Stephen; Dhaliwal, Kevin; Williams, Christopher K. I.

2016-08-01

Solitary pulmonary nodules are common, often incidental findings on chest CT scans. The investigation of pulmonary nodules is time-consuming and often leads to protracted follow-up with ongoing radiological surveillance, however, clinical calculators that assess the risk of the nodule being malignant exist to help in the stratification of patients. Furthermore recent advances in interventional pulmonology include the ability to both navigate to nodules and also to perform autofluorescence endomicroscopy. In this study we assessed the efficacy of incorporating additional information from label-free fibre-based optical endomicrosopy of the nodule on assessing risk of malignancy. Using image analysis and machine learning approaches, we find that this information does not yield any gain in predictive performance in a cohort of patients. Further advances with pulmonary endomicroscopy will require the addition of molecular tracers to improve information from this procedure.

The auxin response factor gene family in banana: genome-wide identification and expression analyses during development, ripening, and abiotic stress

PubMed Central

Hu, Wei; Zuo, Jiao; Hou, Xiaowan; Yan, Yan; Wei, Yunxie; Liu, Juhua; Li, Meiying; Xu, Biyu; Jin, Zhiqiang

2015-01-01

Auxin signaling regulates various auxin-responsive genes via two types of transcriptional regulators, Auxin Response Factors (ARF) and Aux/IAA. ARF transcription factors act as critical components of auxin signaling that play important roles in modulating various biological processes. However, limited information about this gene family in fruit crops is currently available. Herein, 47 ARF genes were identified in banana based on its genome sequence. Phylogenetic analysis of the ARFs from banana, rice, and Arabidopsis suggested that the ARFs could be divided into four subgroups, among which most ARFs from the banana showed a closer relationship with those from rice than those from Arabidopsis. Conserved motif analysis showed that all identified MaARFs had typical DNA-binding and ARF domains, but 12 members lacked the dimerization domain. Gene structure analysis showed that the number of exons in MaARF genes ranged from 5 to 21, suggesting large variation amongst banana ARF genes. The comprehensive expression profiles of MaARF genes yielded useful information about their involvement in diverse tissues, different stages of fruit development and ripening, and responses to abiotic stresses in different varieties. Interaction networks and co-expression assays indicated the strong transcriptional response of banana ARFs and ARF-mediated networks in early fruit development for different varieties. Our systematic analysis of MaARFs revealed robust tissue-specific, development-dependent, and abiotic stress-responsive candidate MaARF genes for further functional assays in planta. These findings could lead to potential applications in the genetic improvement of banana cultivars, and yield new insights into the complexity of the control of MaARF gene expression at the transcriptional level. Finally, they support the hypothesis that ARFs are a crucial component of the auxin signaling pathway, which regulates a wide range of physiological processes. PMID:26442055

Pure MW Data for v=0-6 of PbI Give Vibrational Spacings and a Full Analytic Potential Energy Function

NASA Astrophysics Data System (ADS)

Yoo, Ji Ho (Chris); Evans, Corey; Walker, Nick; Le Roy, Robert J.

2015-06-01

At last year's ISMS meeting, Zaleski et al. reported new broadband MW spectroscopy measurements of pure rotational transitions in the v=0-6 levels of the ^2Π1/2 ground electronic state of PbI. The analysis presented at that time was a conventional v-level by v-level `band-constant' analysis performed using the PGopher program. That level-by-level PGopher analysis yielded values of B_v, D_v and five spin-splitting parameters for each vibrational level of each isotopologue. Ignoring the spin-splitting information, the B_v and D_v values were used to generate a set of synthetic pure R(0) transitions for each level that were taken to represent the ``mechanical'' information about the molecule contained in these spectra. A standard direct-potential-fit (DPF) analysis was then used to fit these data to an ``Expanded Morse Oscillator'' (EMO) potential function form. The well-depth parameter D_e was fixed at the literature value, while values of the equilibrium distance r_e and three EMO exponent-coefficient expansion `potential shape' parameters are determined from the fits. The best fits to the data yield potentials whose fundamental vibrational spacings are in excellent agreement with experiment together with reliable predictions for the first five overtone energies. D.P. Zaleski, H. Köckert, S.L. Stephens, N. Walker, L.-M. Dickens, and C. Evans, paper RE08 at the 69th International Symposium on Molecular Spectroscopy, University of Illinois (2014). PGopher - a Program for Simulating Rotational Structure, C. M. Western, University of Bristol, http://pgopher.chm.bris.ac.uk DPotFit 2.0: A Computer Program for fitting Diatomic Molecule Spectra to Potential Energy Functions, R.J. Le Roy, J. Seto and Y. Huang, University of Waterloo Chemical Physics Research Report CP-667 (2013); see http://leroy.uwaterloo.ca/programs/. K. Ziebarth, R. Breidohr, O. Shestakov and E.H. Fink, Chem. Phys. Lett. 190, 271 (1992).

Effects of digestion, chemical separation, and deposition on Po-210 quantitative analysis

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

Seiner, Brienne N.; Morley, Shannon M.; Beacham, Tere A.

Polonium-210 is a radioactive isotope often used to study sedimentation processes, food chains, aerosol behavior, and atmospheric circulations related to environmental sciences. Materials for the analysis of Po-210 range from tobacco leaves or cotton fibers, to soils and sediments. The purpose of this work was to determine polonium losses from a variety of sample types (soil, cotton fiber, and air filter) due to digestion technique, chemical separation, and deposition method for alpha energy analysis. Results demonstrated that yields from a perchloric acid wet-ash were similar to that from a microwave digestion. Both were greater than the dry-ash procedure. The poloniummore » yield from the perchloric acid wet ash was 87 ± 5%, the microwave digestion had a yield of 100 ± 7%, and the dry ash had a yield of 38 ± 5%. The chemical separation of polonium by an anion exchange resin was used only on the soil samples due to the complex nature of this sample. The yield of Po-209 tracer after chemical separation and deposition for alpha analysis was 83 ± 7% for the soil samples. Spontaneous deposition yields for the cotton and air filters were 87 ± 4% and 92 ± 6%, respectively. Based on the overall process yields for each sample type the amount of Po-210 was quantified using alpha energy analysis. The soil contained 0.18 ± 0.08 Bq/g, the cotton swipe contained 0.7 mBq/g, and the air filter contained 0.04 ± 0.02 mBq/g. High and robust yields of polonium are possible using a suitable digestion, separation, and deposition method.« less

Bark analysis as a guide to cassava nutrition in Sierra Leone

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

Godfrey-Sam-Aggrey, W.; Garber, M.J.

1979-01-01

Cassava main stem barks from two experiments in which similar fertilizers were applied directly in a 2/sup 5/ confounded factorial design were analyzed and the bark nutrients used as a guide to cassava nutrition. The application of multiple regression analysis to the respective root yields and bark nutrient concentrations enable nutrient levels and optimum adjusted root yields to be derived. Differences in bark nutrient concentrations reflected soil fertility levels. Bark analysis and the application of multiple regression analysis to root yields and bark nutrients appear to be useful tools for predicting fertilizer recommendations for cassava production.

Persistency of milk yield in Indonesian Holstein cows

NASA Astrophysics Data System (ADS)

Widyas, N.; Putra, F. Y.; Nugroho, T.; Pramono, A.; Susilowati, A.; Sutarno; Prastowo, S.

2018-03-01

Milk yield is an important trait in dairy industry; thus, information regarding this phenotype is essential to measure the productivity of a farm. Total milk yield in one lactation period was often predicted using information from samples collected within certain time intervals. The rate of change of milk production between two-time intervals is defined as persistency. This article aims to estimate the persistency of milk yield between lactation 1, 2 and 3 in Indonesian Friesian Holstein (IFH) cows. Data was collected from Limpakuwus stable, Baturraden Dairy Cattle Breeding Centre, Central Java Indonesia. Records were obtained from cows which started lactating on 2013 until the end of third lactation around the beginning of 2016. Milk yield from the first (L1), second (L2) and third (L3) lactations of 21 cows were recorded in kilograms. Samples were collected in 30 days basis interval started from the 10th day of lactation up to the 10th month. In this population, the cows first calving was around February – April 2013; while the second and third calving occurred all over the relevant year. The mean of milk yield for L1, L2 and L3 were 17.77±3.70, 16.09±5.17 and 13.73±4.02 Kg respectively. The peak of milk yields was achieved at the second month of the lactation for L1, L2 and L3. The persistency from the second to the tenth test days were 97, 93 and 94% for L1, L2 and L3, respectively. Milk yield persistency is representing ability of cow in maintain milk production after peak during lactation period. The more persistent shows better performance of dairy cattle as well as farm management. For that, persistency value could be used as valuable information in evaluating the management in Indonesian dairy farms.

Farmers Extension Program Effects on Yield Gap in North China Plain

NASA Astrophysics Data System (ADS)

Sum, N.; Zhao, Y.

2015-12-01

Improving crop yield of the lowest yielding smallholder farmers in developing countries is essential to both food security of the country and the farmers' livelihood. Although wheat and maize production in most developed countries have reached 80% or greater of yield potential determined by simulated models, yield gap remains high in the developing world. One of these cases is the yield gap of maize in the North China Plain (NCP), where the average farmer's yield is 41% of his or her potential yield. This large yield gap indicates opportunity to raise yields substantially by improving agronomy, especially in nutrition management, irrigation facility, and mechanization issues such as technical services. Farmers' agronomic knowledge is essential to yield performance. In order to propagate such knowledge to farmers, agricultural extension programs, especially in-the-field guidance with training programs at targeted demonstration fields, have become prevalent in China. Although traditional analyses of the effects of the extension program are done through surveys, they are limited to only one to two years and to a small area. However, the spatial analysis tool Google Earth Engine (GEE) and its extensive satellite imagery data allow for unprecedented spatial temporal analysis of yield variation. We used GEE to analyze maize yield in Quzhou county in the North China Plain from 2007 to 2013. We based our analysis on the distance from a demonstration farm plot, the source of the farmers' agronomic knowledge. Our hypothesis was that the farther the farmers' fields were from the demonstration plot, the less access they would have to the knowledge, and the less increase in yield over time. Testing this hypothesis using GEE helps us determine the effectiveness of the demonstration plot in disseminating optimal agronomic practices in addition to evaluating yield performance of the demonstration field itself. Furthermore, we can easily extend this methodology to analyze the whole NCP and any other parts of the world for any type of crop.

A hierarchical spatial model for well yield in complex aquifers

NASA Astrophysics Data System (ADS)

Montgomery, J.; O'sullivan, F.

2017-12-01

Efficiently siting and managing groundwater wells requires reliable estimates of the amount of water that can be produced, or the well yield. This can be challenging to predict in highly complex, heterogeneous fractured aquifers due to the uncertainty around local hydraulic properties. Promising statistical approaches have been advanced in recent years. For instance, kriging and multivariate regression analysis have been applied to well test data with limited but encouraging levels of prediction accuracy. Additionally, some analytical solutions to diffusion in homogeneous porous media have been used to infer "effective" properties consistent with observed flow rates or drawdown. However, this is an under-specified inverse problem with substantial and irreducible uncertainty. We describe a flexible machine learning approach capable of combining diverse datasets with constraining physical and geostatistical models for improved well yield prediction accuracy and uncertainty quantification. Our approach can be implemented within a hierarchical Bayesian framework using Markov Chain Monte Carlo, which allows for additional sources of information to be incorporated in priors to further constrain and improve predictions and reduce the model order. We demonstrate the usefulness of this approach using data from over 7,000 wells in a fractured bedrock aquifer.

Uncertainty in Simulating Wheat Yields Under Climate Change

NASA Technical Reports Server (NTRS)

Asseng, S.; Ewert, F.; Rosenzweig, Cynthia; Jones, J. W.; Hatfield, J. W.; Ruane, A. C.; Boote, K. J.; Thornburn, P. J.; Rotter, R. P.; Cammarano, D.;

Bayesian networks and information theory for audio-visual perception modeling.

PubMed

Besson, Patricia; Richiardi, Jonas; Bourdin, Christophe; Bringoux, Lionel; Mestre, Daniel R; Vercher, Jean-Louis

2010-09-01

Thanks to their different senses, human observers acquire multiple information coming from their environment. Complex cross-modal interactions occur during this perceptual process. This article proposes a framework to analyze and model these interactions through a rigorous and systematic data-driven process. This requires considering the general relationships between the physical events or factors involved in the process, not only in quantitative terms, but also in term of the influence of one factor on another. We use tools from information theory and probabilistic reasoning to derive relationships between the random variables of interest, where the central notion is that of conditional independence. Using mutual information analysis to guide the model elicitation process, a probabilistic causal model encoded as a Bayesian network is obtained. We exemplify the method by using data collected in an audio-visual localization task for human subjects, and we show that it yields a well-motivated model with good predictive ability. The model elicitation process offers new prospects for the investigation of the cognitive mechanisms of multisensory perception.

Fault diagnosis model for power transformers based on information fusion

NASA Astrophysics Data System (ADS)

Dong, Ming; Yan, Zhang; Yang, Li; Judd, Martin D.

2005-07-01

Methods used to assess the insulation status of power transformers before they deteriorate to a critical state include dissolved gas analysis (DGA), partial discharge (PD) detection and transfer function techniques, etc. All of these approaches require experience in order to correctly interpret the observations. Artificial intelligence (AI) is increasingly used to improve interpretation of the individual datasets. However, a satisfactory diagnosis may not be obtained if only one technique is used. For example, the exact location of PD cannot be predicted if only DGA is performed. However, using diverse methods may result in different diagnosis solutions, a problem that is addressed in this paper through the introduction of a fuzzy information infusion model. An inference scheme is proposed that yields consistent conclusions and manages the inherent uncertainty in the various methods. With the aid of information fusion, a framework is established that allows different diagnostic tools to be combined in a systematic way. The application of information fusion technique for insulation diagnostics of transformers is proved promising by means of examples.

A mathematical framework for yield (vs. rate) optimization in constraint-based modeling and applications in metabolic engineering.

PubMed

Klamt, Steffen; Müller, Stefan; Regensburger, Georg; Zanghellini, Jürgen

2018-05-01

The optimization of metabolic rates (as linear objective functions) represents the methodical core of flux-balance analysis techniques which have become a standard tool for the study of genome-scale metabolic models. Besides (growth and synthesis) rates, metabolic yields are key parameters for the characterization of biochemical transformation processes, especially in the context of biotechnological applications. However, yields are ratios of rates, and hence the optimization of yields (as nonlinear objective functions) under arbitrary linear constraints is not possible with current flux-balance analysis techniques. Despite the fundamental importance of yields in constraint-based modeling, a comprehensive mathematical framework for yield optimization is still missing. We present a mathematical theory that allows one to systematically compute and analyze yield-optimal solutions of metabolic models under arbitrary linear constraints. In particular, we formulate yield optimization as a linear-fractional program. For practical computations, we transform the linear-fractional yield optimization problem to a (higher-dimensional) linear problem. Its solutions determine the solutions of the original problem and can be used to predict yield-optimal flux distributions in genome-scale metabolic models. For the theoretical analysis, we consider the linear-fractional problem directly. Most importantly, we show that the yield-optimal solution set (like the rate-optimal solution set) is determined by (yield-optimal) elementary flux vectors of the underlying metabolic model. However, yield- and rate-optimal solutions may differ from each other, and hence optimal (biomass or product) yields are not necessarily obtained at solutions with optimal (growth or synthesis) rates. Moreover, we discuss phase planes/production envelopes and yield spaces, in particular, we prove that yield spaces are convex and provide algorithms for their computation. We illustrate our findings by a small example and demonstrate their relevance for metabolic engineering with realistic models of E. coli. We develop a comprehensive mathematical framework for yield optimization in metabolic models. Our theory is particularly useful for the study and rational modification of cell factories designed under given yield and/or rate requirements. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Famine Early Warning Systems and Their Use of Satellite Remote Sensing Data

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Essam, Timothy; Leonard, Kenneth

2011-01-01

Famine early warning organizations have experience that has much to contribute to efforts to incorporate climate and weather information into economic and political systems. Food security crises are now caused almost exclusively by problems of food access, not absolute food availability, but the role of monitoring agricultural production both locally and globally remains central. The price of food important to the understanding of food security in any region, but it needs to be understood in the context of local production. Thus remote sensing is still at the center of much food security analysis, along with an examination of markets, trade and economic policies during food security analyses. Technology including satellite remote sensing, earth science models, databases of food production and yield, and modem telecommunication systems contributed to improved food production information. Here we present an econometric approach focused on bringing together satellite remote sensing and market analysis into food security assessment in the context of early warning.

Formation Pathways of Carbon Allotropes in Detonation Condensates

NASA Astrophysics Data System (ADS)

Nielsen, Michael; Bagge-Hansen, Michael; Hammons, Josh; Lauderbach, Lisa; Hodgin, Ralph; Bastea, Sorin; Fried, Larry; Lee, Jonathan; van Buuren, Tony; Pagoria, Phil; May, Chadd; Aloni, Shaul; Willey, Trevor

2017-06-01

Time-resolved small-angle scattering (TR-SAXS) data reveal evolution in the size and morphology of nano-carbon particles that form during the first microsecond during the detonation of high explosive (HE) materials, but do not provide chemical or phase information. Herein, we present analysis of complementary post-detonation soots collected with minimal environmental carbon or other contamination: HE samples are detonated whithin clean ice capture layers to yield aqueous dispersions of the carbonaceous soot. We report substantial variation in soots formed through the detonation of HE materials that attain a variety of temperatures and pressures during detonation. Transmission electron microscopy analysis of these recovered soots provides physical and chemical information that we compare directly to TR-SAXS data and SAXS measurements from recovered soots. We observe various structures including graphitic and amorphous carbon, nanodiamond, and spherical carbon onions. These experimental data correlate to models of how products from HE materials traverse the carbon phase diagram during detonation. Prepared by LLNL under Contract DE-AC52-07NA27344.

High-content screening for the discovery of pharmacological compounds: advantages, challenges and potential benefits of recent technological developments.

PubMed

Soleilhac, Emmanuelle; Nadon, Robert; Lafanechere, Laurence

2010-02-01

Screening compounds with cell-based assays and microscopy image-based analysis is an approach currently favored for drug discovery. Because of its high information yield, the strategy is called high-content screening (HCS). This review covers the application of HCS in drug discovery and also in basic research of potential new pathways that can be targeted for treatment of pathophysiological diseases. HCS faces several challenges, however, including the extraction of pertinent information from the massive amount of data generated from images. Several proposed approaches to HCS data acquisition and analysis are reviewed. Different solutions from the fields of mathematics, bioinformatics and biotechnology are presented. Potential applications and limits of these recent technical developments are also discussed. HCS is a multidisciplinary and multistep approach for understanding the effects of compounds on biological processes at the cellular level. Reliable results depend on the quality of the overall process and require strong interdisciplinary collaborations.

Multivariate statistical analysis of the polyphenolic constituents in kiwifruit juices to trace fruit varieties and geographical origins.

PubMed

Guo, Jing; Yuan, Yahong; Dou, Pei; Yue, Tianli

2017-10-01

Fifty-one kiwifruit juice samples of seven kiwifruit varieties from five regions in China were analyzed to determine their polyphenols contents and to trace fruit varieties and geographical origins by multivariate statistical analysis. Twenty-one polyphenols belonging to four compound classes were determined by ultra-high-performance liquid chromatography coupled with ultra-high-resolution TOF mass spectrometry. (-)-Epicatechin, (+)-catechin, procyanidin B1 and caffeic acid derivatives were the predominant phenolic compounds in the juices. Principal component analysis (PCA) allowed a clear separation of the juices according to kiwifruit varieties. Stepwise linear discriminant analysis (SLDA) yielded satisfactory categorization of samples, provided 100% success rate according to kiwifruit varieties and 92.2% success rate according to geographical origins. The result showed that polyphenolic profiles of kiwifruit juices contain enough information to trace fruit varieties and geographical origins. Copyright © 2017 Elsevier Ltd. All rights reserved.

Systematic Analysis Of Ocean Colour Uncertainties

NASA Astrophysics Data System (ADS)

Lavender, Samantha

2013-12-01

This paper reviews current research into the estimation of uncertainties as a pixel-based measure to aid non- specialist users of remote sensing products. An example MERIS image, captured on the 28 March 2012, was processed with above-water atmospheric correction code. This was initially based on both the Antoine & Morel Standard Atmospheric Correction, with Bright Pixel correction component, and Doerffer Neural Network coastal water's approach. It's showed that analysis of the atmospheric by-products yield important information about the separation of the atmospheric and in-water signals, helping to sign-post possible uncertainties in the atmospheric correction results. Further analysis has concentrated on implementing a ‘simplistic' atmospheric correction so that the impact of changing the input auxiliary data can be analysed; the influence of changing surface pressure is demonstrated. Future work will focus on automating the analysis, so that the methodology can be implemented within an operational system.

Estimating hazard ratios in cohort data with missing disease information due to death.

PubMed

Binder, Nadine; Herrnböck, Anne-Sophie; Schumacher, Martin

2017-03-01

In clinical and epidemiological studies information on the primary outcome of interest, that is, the disease status, is usually collected at a limited number of follow-up visits. The disease status can often only be retrieved retrospectively in individuals who are alive at follow-up, but will be missing for those who died before. Right-censoring the death cases at the last visit (ad-hoc analysis) yields biased hazard ratio estimates of a potential risk factor, and the bias can be substantial and occur in either direction. In this work, we investigate three different approaches that use the same likelihood contributions derived from an illness-death multistate model in order to more adequately estimate the hazard ratio by including the death cases into the analysis: a parametric approach, a penalized likelihood approach, and an imputation-based approach. We investigate to which extent these approaches allow for an unbiased regression analysis by evaluating their performance in simulation studies and on a real data example. In doing so, we use the full cohort with complete illness-death data as reference and artificially induce missing information due to death by setting discrete follow-up visits. Compared to an ad-hoc analysis, all considered approaches provide less biased or even unbiased results, depending on the situation studied. In the real data example, the parametric approach is seen to be too restrictive, whereas the imputation-based approach could almost reconstruct the original event history information. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Characterizing of tissue microstructure with single-detector polarization-sensitive optical coherence tomography

NASA Astrophysics Data System (ADS)

Liu, Bin; Harman, Michelle; Giattina, Susanne; Stamper, Debra L.; Demakis, Charles; Chilek, Mark; Raby, Stephanie; Brezinski, Mark E.

2006-06-01

Assessing tissue birefringence with imaging modality polarization-sensitive optical coherence tomography (PS-OCT) could improve the characterization of in vivo tissue pathology. Among the birefringent components, collagen may provide invaluable clinical information because of its alteration in disorders ranging from myocardial infarction to arthritis. But the features required of clinical imaging modality in these areas usually include the ability to assess the parameter of interest rapidly and without extensive data analysis, the characteristics that single-detector PS-OCT demonstrates. But beyond detecting organized collagen, which has been previously demonstrated and confirmed with the appropriate histological techniques, additional information can potentially be gained with PS-OCT, including collagen type, form versus intrinsic birefringence, the collagen angle, and the presence of multiple birefringence materials. In part I, we apply the simple but powerful fast-Fourier transform (FFT) to both PS-OCT mathematical modeling and in vitro bovine meniscus for improved PS-OCT data analysis. The FFT analysis yields, in a rapid, straightforward, and easily interpreted manner, information on the presence of multiple birefringent materials, distinguishing the true anatomical structure from patterns in image resulting from alterations in the polarization state and identifying the tissue/phantom optical axes. Therefore the use of the FFT analysis of PS-OCT data provides information on tissue composition beyond identifying the presence of organized collagen in real time and directly from the image without extensive mathematical manipulation or data analysis. In part II, Helistat phantoms (collagen type I) are analyzed with the ultimate goal of improved tissue characterization. This study, along with the data in part I, advance the insights gained from PS-OCT images beyond simply determining the presence or absence of birefringence.

Searching the Footprints of Pioneers on Neurology: A Bibliometric Analysis.

PubMed

Park, Kang Min; Kim, Jee-Eun; Kim, Yerim; Kim, Si Eun; Yoon, Dae Young; Bae, Jong Seok

2017-01-01

We identify the most cited articles that have influenced the clinical practices of neurologists. We first analyzed the top 100 cited articles published in 50 neurology journals with high impact factors. We collected all of the original articles on clinical neurology published in all 554 medical journals. The Institute for Scientific Information Web of Science search tools were used to identify the top 100 cited articles in the database of Journal Citation Reports since 1950, which were then manually reviewed to discover their contents. In the first part of analysis, the top 100 cited articles were all published in 17 journals, with 26 articles published in Neurology. The most frequent topic subject of neurodegeneration appeared in 40 articles. The second part of the analysis revealed that the top 100 cited articles were also all published in 17 journals, with 30 articles published in New England Journal of Medicine. In contrast to the first part of the analysis, stroke was the most frequent topic subject (in 38 articles). Our bibliometric analysis has yielded 2 detailed lists of the top 100 cited articles that were listed separately using different methods. This approach can provide information about the trends and academic achievements in the field of clinical neurology. © 2017 S. Karger AG, Basel.

Mind the Roots: Phenotyping Below-Ground Crop Diversity and Its Influence on Final Yield

NASA Astrophysics Data System (ADS)

Nieters, C.; Guadagno, C. R.; Lemli, S.; Hosseini, A.; Ewers, B. E.

2017-12-01

Changes in global climate patterns and water regimes are having profound impacts on worldwide crop production. An ever-growing population paired with increasing temperatures and unpredictable periods of severe drought call for accurate modeling of future crop yield. Although novel approaches are being developed in high-throughput, above-ground image phenotyping, the below-ground plant system is still poorly phenotyped. Collection of plant root morphology and hydraulics are needed to inform mathematical models to reliably estimate yields of crops grown in sub-optimal conditions. We used Brassica rapa to inform our model as it is a globally cultivated crop with several functionally diverse cultivars. Specifically, we use 7 different accessions from oilseed (R500 and Yellow Sarson), leafy type (Pac choi and Chinese cabbage), a vegetable turnip, and two Wisconsin Fast Plants (Imb211 and Fast Plant self-compatible), which have shorter life cycles and potentially large differences in allocation to roots. Bi-weekly, we harvested above and below-ground biomass to compare the varieties in terms of carbon allocation throughout their life cycle. Using WinRhizo software, we analyzed root system length and surface area to compare and contrast root morphology among cultivars. Our results confirm that root structural characteristics are crucial to explain plant water use and carbon allocation. The root:shoot ratio reveals a significant (p < 0.01) difference among crop accession. To validate the procedure across different varieties and life stages we also compared surface area results from the image-based technology to dry biomass finding a strong linear relationship (R2= 0.85). To assess the influence of a diverse above-ground morphology on the root system we also measured above-ground anatomical and physiological traits such as gas exchange, chlorophyll content, and chlorophyll a fluorescence. A thorough analysis of the root system will clarify carbon dynamics and hydraulics at the whole-plant level, improving final yield predictions.

The effect of shear strength on isentropic compression experiments

NASA Astrophysics Data System (ADS)

Thomson, Stuart; Howell, Peter; Ockendon, John; Ockendon, Hilary

2015-06-01

Isentropic compression experiments (ICE) are a novel way of obtaining equation of state information for metals undergoing violent plastic deformation. In a typical experiment, millimetre thick metal samples are subjected to pressures on the order of 10 -102 GPa, while the yield strength of the material can be as low as 10-1GPa. The analysis of such experiments has so far neglected the effect of shear strength, instead treating the highly plasticised metal as an inviscid compressible fluid. However making this approximation belies the basic elastic nature of a solid object. A more accurate method should strive to incorporate the small but measurable effects of shear strength. Here we present a one-dimensional mathematical model for elastoplasticity at high stress which allows for both compressibility and the shear strength of the material. In the limit of zero yield stress this model reproduces the hydrodynamic models currently used to analyse ICEs. We will also show using a systematic asymptotic analysis that entropy changes are universally negligible in the absence of shocks. Numerical solutions of the governing equations will then be presented for problems relevant to ICEs in order to investigate the effects of shear strength over a model based purely on hydrodynamics.

Unravelling molecular mechanisms from floral initiation to lipid biosynthesis in a promising biofuel tree species, Pongamia pinnata using transcriptome analysis

PubMed Central

Sreeharsha, Rachapudi V.; Mudalkar, Shalini; Singha, Kambam T.; Reddy, Attipalli R.

2016-01-01

Pongamia pinnata (L.) (Fabaceae) is a promising biofuel tree species which is underexploited in the areas of both fundamental and applied research, due to the lack of information either on transcriptome or genomic data. To investigate the possible metabolic pathways, we performed whole transcriptome analysis of Pongamia through Illumina NextSeq platform and generated 2.8 GB of paired end sequence reads. The de novo assembly of raw reads generated 40,000 contigs and 35,000 transcripts, representing leaf, flower and seed unigenes. Spatial and temporal expression profiles of photoperiod and floral homeotic genes in Pongamia, identified GIGANTEA (GI) - CONSTANS (CO) - FLOWERING LOCUS T (FT) as active signal cascade for floral initiation. Four prominent stages of seed development were selected in a high yielding Pongamia accession (TOIL 1) to follow the temporal expression patterns of key fatty acid biosynthetic genes involved in lipid biosynthesis and accumulation. Our results provide insights into an array of molecular events from flowering to seed maturity in Pongamia which will provide substantial basis for modulation of fatty acid composition and enhancing oil yields which should serve as a potential feedstock for biofuel production. PMID:27677333

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could be further associated with the actual yield. Utilizing satellite remote sensing products, such as daily NDVI derived from Moderate Resolution Imaging Spectroradiometer (MODIS) at 250 m pixel size, the crop yield estimation can be performed at a very fine spatial resolution. Therefore, this study examined the potential of these daily NDVI products within agricultural studies and crop yield assessments. In this study, a regression-based approach was proposed to estimate the annual corn yield through changes in MODIS daily NDVI time series. The relationship between daily NDVI and corn yield was well defined and established, and as changes in corn phenology and yield were directly reflected by the changes in NDVI within the growing season, these two entities were combined to develop a relational model. The model was trained using 15 years (2000-2014) of historical NDVI and county-level corn yield data for four major corn producing states: Kansas, Nebraska, Iowa, and Indiana, representing four climatic regions as South, West North Central, East North Central, and Central, respectively, within the U.S. Corn Belt area. The model's goodness of fit was well defined with a high coefficient of determination (R2>0.81). Similarly, using 2015 yield data for validation, 92% of average accuracy signified the performance of the model in estimating corn yield at county level. Besides providing the county-level corn yield estimations, the derived model was also accurate enough to estimate the yield at finer spatial resolution (field level). The model's assessment accuracy was evaluated using the randomly selected field level corn yield within the study area for 2014, 2015, and 2016. A total of over 120 plot level corn yield were used for validation, and the overall average accuracy was 87%, which statistically justified the model's capability to estimate plot-level corn yield. Additionally, the proposed model was applied to the impact estimation by examining the changes in corn yield due to flood events during the growing season. Using a 2011 Missouri River flood event as a case study, field-level flood impact map on corn yield throughout the flooded regions was produced and an overall agreement of over 82.2% was achieved when compared with the reference impact map. The future research direction of this dissertation research would be to examine other major crops outside the Corn Belt region of the U.S.

Kinetically accessible yield (KAY) for redirection of metabolism to produce exo-metabolites

DOE PAGES

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei; ...

2017-04-05

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

InfoDROUGHT: Technical reliability assessment using crop yield data at the Spanish-national level

NASA Astrophysics Data System (ADS)

Contreras, Sergio; Garcia-León, David; Hunink, Johannes E.

2017-04-01

Drought monitoring (DM) is a key component of risk-centered drought preparedness plans and drought policies. InfoDROUGHT (www.infosequia.es) is a a site- and user-tailored and fully-integrated DM system which combines functionalities for: a) the operational satellite-based weekly-1km tracking of severity and spatial extent of drought impacts, b) the interactive and faster query and delivery of drought information through a web-mapping service. InfoDROUGHT has a flexible and modular structure. The calibration (threshold definitions) and validation of the system is performed by combining expert knowledge and auxiliary impact assessments and datasets. Different technical solutions (basic or advanced versions) or deployment options (open-standard or restricted-authenticated) can be purchased by end-users and customers according to their needs. In this analysis, the technical reliability of InfoDROUGHT and its performance for detecting drought impacts on agriculture has been evaluated in the 2003-2014 period by exploring and quantifying the relationships among the drought severity indices reported by InfoDROUGHT and the annual yield anomalies observed for different rainfed crops (maize, wheat, barley) at Spain. We hypothesize a positive relationship between the crop anomalies and the drought severity level detected by InfoDROUGHT. Annual yield anomalies were computed at the province administrative level as the difference between the annual yield reported by the Spanish Annual Survey of Crop Acreages and Yields (ESYRCE database) and the mean annual yield estimated during the study period. Yield anomalies were finally compared against drought greenness-based and thermal-based drought indices (VCI and TCI, respectively) to check the coherence of the outputs and the hypothesis stated. InfoDROUGHT has been partly funded by the Spanish Ministry of Economy and Competiveness through a Torres-Quevedo grant, and by the H2020-EU project "Bridging the Gap for Innovations in Disaster Resilience" (www.brigaid.eu).

[Winter wheat yield gap between field blocks based on comparative performance analysis].

PubMed

Chen, Jian; Wang, Zhong-Yi; Li, Liang-Tao; Zhang, Ke-Feng; Yu, Zhen-Rong

2008-09-01

Based on a two-year household survey data, the yield gap of winter wheat in Quzhou County of Hebei Province, China in 2003-2004 was studied through comparative performance analysis (CPA). The results showed that there was a greater yield gap (from 4.2 to 7.9 t x hm(-2)) between field blocks, with a variation coefficient of 0.14. Through stepwise forward linear multiple regression, it was found that the yield model with 8 selected variables could explain 63% variability of winter wheat yield. Among the variables selected, soil salinity, soil fertility, and irrigation water quality were the most important limiting factors, accounting for 52% of the total yield gap. Crop variety was another important limiting factor, accounting for 14%; while planting date, fertilizer type, disease and pest, and water press accounted for 7%, 14%, 10%, and 3%, respectively. Therefore, besides soil and climate conditions, management practices occupied the majority of yield variability in Quzhou County, suggesting that the yield gap could be reduced significantly through optimum field management.

Electric-Field Instrument With Ac-Biased Corona Point

NASA Technical Reports Server (NTRS)

Markson, R.; Anderson, B.; Govaert, J.

1993-01-01

Measurements indicative of incipient lightning yield additional information. New instrument gives reliable readings. High-voltage ac bias applied to needle point through high-resistance capacitance network provides corona discharge at all times, enabling more-slowly-varying component of electrostatic potential of needle to come to equilibrium with surrounding air. High resistance of high-voltage coupling makes instrument insensitive to wind. Improved corona-point instrument expected to yield additional information assisting in safety-oriented forecasting of lighting.

Growth and yield predictions for upland oak stands. 10 years after initial thinning

Treesearch

Martin E. Dale; Martin E. Dale

1972-01-01

The purpose of this paper is to furnish part of the needed information, that is, quantitative estimates of growth and yield 10 years after initial thinning of upland oak stands. All estimates are computed from a system of equations. These predictions are presented here in tabular form for convenient visual inspection of growth and yield trends. The tables show growth...

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

Lafontaine Rivera, Jimmy G.; Theisen, Matthew K.; Chen, Po-Wei

The product formation yield (product formed per unit substrate consumed) is often the most important performance indicator in metabolic engineering. Until now, the actual yield cannot be predicted, but it can be bounded by its maximum theoretical value. The maximum theoretical yield is calculated by considering the stoichiometry of the pathways and cofactor regeneration involved. Here in this paper we found that in many cases, dynamic stability becomes an issue when excessive pathway flux is drawn to a product. This constraint reduces the yield and renders the maximal theoretical yield too loose to be predictive. We propose a more realisticmore » quantity, defined as the kinetically accessible yield (KAY) to predict the maximum accessible yield for a given flux alteration. KAY is either determined by the point of instability, beyond which steady states become unstable and disappear, or a local maximum before becoming unstable. Thus, KAY is the maximum flux that can be redirected for a given metabolic engineering strategy without losing stability. Strictly speaking, calculation of KAY requires complete kinetic information. With limited or no kinetic information, an Ensemble Modeling strategy can be used to determine a range of likely values for KAY, including an average prediction. We first apply the KAY concept with a toy model to demonstrate the principle of kinetic limitations on yield. We then used a full-scale E. coli model (193 reactions, 153 metabolites) and this approach was successful in E. coli for predicting production of isobutanol: the calculated KAY values are consistent with experimental data for three genotypes previously published.« less

Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States.

PubMed

Kniss, Andrew R; Savage, Steven D; Jabbour, Randa

2016-01-01

Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 67% of conventional yield [corrected]. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (Glycine max) and potato (Solanum tuberosum), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (Hordeum vulgare), wheat (Triticum aestevum), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap.

Commercial Crop Yields Reveal Strengths and Weaknesses for Organic Agriculture in the United States

PubMed Central

Savage, Steven D.; Jabbour, Randa

2016-01-01

Land area devoted to organic agriculture has increased steadily over the last 20 years in the United States, and elsewhere around the world. A primary criticism of organic agriculture is lower yield compared to non-organic systems. Previous analyses documenting the yield deficiency in organic production have relied mostly on data generated under experimental conditions, but these studies do not necessarily reflect the full range of innovation or practical limitations that are part of commercial agriculture. The analysis we present here offers a new perspective, based on organic yield data collected from over 10,000 organic farmers representing nearly 800,000 hectares of organic farmland. We used publicly available data from the United States Department of Agriculture to estimate yield differences between organic and conventional production methods for the 2014 production year. Similar to previous work, organic crop yields in our analysis were lower than conventional crop yields for most crops. Averaged across all crops, organic yield averaged 80% of conventional yield. However, several crops had no significant difference in yields between organic and conventional production, and organic yields surpassed conventional yields for some hay crops. The organic to conventional yield ratio varied widely among crops, and in some cases, among locations within a crop. For soybean (Glycine max) and potato (Solanum tuberosum), organic yield was more similar to conventional yield in states where conventional yield was greatest. The opposite trend was observed for barley (Hordeum vulgare), wheat (Triticum aestevum), and hay crops, however, suggesting the geographical yield potential has an inconsistent effect on the organic yield gap. PMID:27552217

Synthetic Aperture Radar (SAR)-based paddy rice monitoring system: Development and application in key rice producing areas in Tropical Asia

NASA Astrophysics Data System (ADS)

Setiyono, T. D.; Holecz, F.; Khan, N. I.; Barbieri, M.; Quicho, E.; Collivignarelli, F.; Maunahan, A.; Gatti, L.; Romuga, G. C.

2017-01-01

Reliable and regular rice information is essential part of many countries’ national accounting process but the existing system may not be sufficient to meet the information demand in the context of food security and policy. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland paddy rice, especially in tropical region where pervasive cloud cover in the rainy seasons limits the use of optical imagery. This study uses multi-temporal X-band and C-band SAR imagery, automated image processing, rule-based classification and field observations to classify rice in multiple locations across Tropical Asia and assimilate the information into ORYZA Crop Growth Simulation model (CGSM) to generate high resolution yield maps. The resulting cultivated rice area maps had classification accuracies above 85% and yield estimates were within 81-93% agreement against district level reported yields. The study sites capture much of the diversity in water management, crop establishment and rice maturity durations and the study demonstrates the feasibility of rice detection, yield monitoring, and damage assessment in case of climate disaster at national and supra-national scales using multi-temporal SAR imagery combined with CGSM and automated methods.

Development of a sensitivity analysis technique for multiloop flight control systems

NASA Technical Reports Server (NTRS)

Vaillard, A. H.; Paduano, J.; Downing, D. R.

1985-01-01

This report presents the development and application of a sensitivity analysis technique for multiloop flight control systems. This analysis yields very useful information on the sensitivity of the relative-stability criteria of the control system, with variations or uncertainties in the system and controller elements. The sensitivity analysis technique developed is based on the computation of the singular values and singular-value gradients of a feedback-control system. The method is applicable to single-input/single-output as well as multiloop continuous-control systems. Application to sampled-data systems is also explored. The sensitivity analysis technique was applied to a continuous yaw/roll damper stability augmentation system of a typical business jet, and the results show that the analysis is very useful in determining the system elements which have the largest effect on the relative stability of the closed-loop system. As a secondary product of the research reported here, the relative stability criteria based on the concept of singular values were explored.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

PubMed

Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Analysis of pumping tests of partially penetrating wells in an unconfined aquifer using inverse numerical optimization

NASA Astrophysics Data System (ADS)

Hvilshøj, S.; Jensen, K. H.; Barlebo, H. C.; Madsen, B.

1999-08-01

Inverse numerical modeling was applied to analyze pumping tests of partially penetrating wells carried out in three wells established in an unconfined aquifer in Vejen, Denmark, where extensive field investigations had previously been carried out, including tracer tests, mini-slug tests, and other hydraulic tests. Drawdown data from multiple piezometers located at various horizontal and vertical distances from the pumping well were included in the optimization. Horizontal and vertical hydraulic conductivities, specific storage, and specific yield were estimated, assuming that the aquifer was either a homogeneous system with vertical anisotropy or composed of two or three layers of different hydraulic properties. In two out of three cases, a more accurate interpretation was obtained for a multi-layer model defined on the basis of lithostratigraphic information obtained from geological descriptions of sediment samples, gammalogs, and flow-meter tests. Analysis of the pumping tests resulted in values for horizontal hydraulic conductivities that are in good accordance with those obtained from slug tests and mini-slug tests. Besides the horizontal hydraulic conductivity, it is possible to determine the vertical hydraulic conductivity, specific yield, and specific storage based on a pumping test of a partially penetrating well. The study demonstrates that pumping tests of partially penetrating wells can be analyzed using inverse numerical models. The model used in the study was a finite-element flow model combined with a non-linear regression model. Such a model can accommodate more geological information and complex boundary conditions, and the parameter-estimation procedure can be formalized to obtain optimum estimates of hydraulic parameters and their standard deviations.

77 FR 67816 - Proposed Agency Information Collection Activities; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-14

... information collection on respondents, including through the use of automated collection techniques or other... trades driven by retail investors versus those that are wholesale driven. This would yield information... FEDERAL RESERVE SYSTEM Proposed Agency Information Collection Activities; Comment Request AGENCY...

Application of isotope labeling experiments and (13)C flux analysis to enable rational pathway engineering.

PubMed

McAtee, Allison G; Jazmin, Lara J; Young, Jamey D

2015-12-01

Isotope labeling experiments (ILEs) and (13)C flux analysis provide actionable information for metabolic engineers to identify knockout, overexpression, and/or media optimization targets. ILEs have been used in both academic and industrial labs to increase product formation, discover novel metabolic functions in previously uncharacterized organisms, and enhance the metabolic efficiency of host cell factories. This review highlights specific examples of how ILEs have been used in conjunction with enzyme or metabolic engineering to elucidate host cell metabolism and improve product titer, rate, or yield in a directed manner. We discuss recent progress and future opportunities involving the use of ILEs and (13)C flux analysis to characterize non-model host organisms and to identify and subsequently eliminate wasteful byproduct pathways or metabolic bottlenecks. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Impacts of Information-Sharing Mechanisms on Spatial Market Formation Based on Agent-Based Modeling

PubMed Central

Li, Qianqian; Yang, Tao; Zhao, Erbo; Xia, Xing’ang; Han, Zhangang

2013-01-01

There has been an increasing interest in the geographic aspects of economic development, exemplified by P. Krugman’s logical analysis. We show in this paper that the geographic aspects of economic development can be modeled using multi-agent systems that incorporate multiple underlying factors. The extent of information sharing is assumed to be a driving force that leads to economic geographic heterogeneity across locations without geographic advantages or disadvantages. We propose an agent-based market model that considers a spectrum of different information-sharing mechanisms: no information sharing, information sharing among friends and pheromone-like information sharing. Finally, we build a unified model that accommodates all three of these information-sharing mechanisms based on the number of friends who can share information. We find that the no information-sharing model does not yield large economic zones, and more information sharing can give rise to a power-law distribution of market size that corresponds to the stylized fact of city size and firm size distributions. The simulations show that this model is robust. This paper provides an alternative approach to studying economic geographic development, and this model could be used as a test bed to validate the detailed assumptions that regulate real economic agglomeration. PMID:23484007

Behavioral economics and empirical public policy.

PubMed

Hursh, Steven R; Roma, Peter G

2013-01-01

The application of economics principles to the analysis of behavior has yielded novel insights on value and choice across contexts ranging from laboratory animal research to clinical populations to national trends of global impact. Recent innovations in demand curve methods provide a credible means of quantitatively comparing qualitatively different reinforcers as well as quantifying the choice relations between concurrently available reinforcers. The potential of the behavioral economic approach to inform public policy is illustrated with examples from basic research, pre-clinical behavioral pharmacology, and clinical drug abuse research as well as emerging applications to public transportation and social behavior. Behavioral Economics can serve as a broadly applicable conceptual, methodological, and analytical framework for the development and evaluation of empirical public policy. © Society for the Experimental Analysis of Behavior.

Optimized "detectors" for dynamics analysis in solid-state NMR

NASA Astrophysics Data System (ADS)

Smith, Albert A.; Ernst, Matthias; Meier, Beat H.

2018-01-01

Relaxation in nuclear magnetic resonance (NMR) results from stochastic motions that modulate anisotropic NMR interactions. Therefore, measurement of relaxation-rate constants can be used to characterize molecular-dynamic processes. The motion is often characterized by Markov processes using an auto-correlation function, which is assumed to be a sum of multiple decaying exponentials. We have recently shown that such a model can lead to severe misrepresentation of the real motion, when the real correlation function is more complex than the model. Furthermore, multiple distributions of motion may yield the same set of dynamics data. Therefore, we introduce optimized dynamics "detectors" to characterize motions which are linear combinations of relaxation-rate constants. A detector estimates the average or total amplitude of motion for a range of motional correlation times. The information obtained through the detectors is less specific than information obtained using an explicit model, but this is necessary because the information contained in the relaxation data is ambiguous, if one does not know the correct motional model. On the other hand, if one has a molecular dynamics trajectory, one may calculate the corresponding detector responses, allowing direct comparison to experimental NMR dynamics analysis. We describe how to construct a set of optimized detectors for a given set of relaxation measurements. We then investigate the properties of detectors for a number of different data sets, thus gaining an insight into the actual information content of the NMR data. Finally, we show an example analysis of ubiquitin dynamics data using detectors, using the DIFRATE software.

Assessing the impacts of current and future concentrations of surface ozone on crop yield with meta-analysis

NASA Astrophysics Data System (ADS)

Feng, Zhaozhong; Kobayashi, Kazuhiko

Meta-analysis was conducted to quantitatively assess the effects of rising ozone concentrations ([O 3]) on yield and yield components of major food crops: potato, barley, wheat, rice, bean and soybean in 406 experimental observations. Yield loss of the crops under current and future [O 3] was expressed relative to the yield under base [O 3] (≤26 ppb). With potato, current [O 3] (31-50 ppb) reduced the yield by 5.3%, and it reduced the yield of barley, wheat and rice by 8.9%, 9.7% and 17.5%, respectively. In bean and soybean, the yield losses were 19.0% and 7.7%, respectively. Compared with yield loss at current [O 3], future [O 3] (51-75 ppb) drove a further 10% loss in yield of soybean, wheat and rice, and 20% loss in bean. Mass of individual grain, seed, or tuber was often the major cause of the yield loss at current and future [O 3], whereas other yield components also contributed to the yield loss in some cases. No significant difference was found between the responses in crops grown in pots and those in the ground for any yield parameters. The ameliorating effect of elevated [CO 2] was significant in the yields of wheat and potato, and the individual grain weight in wheat exposed to future [O 3]. These findings confirm the rising [O 3] as a threat to food security for the growing global population in this century.

CT contrast predicts pancreatic cancer treatment response to verteporfin-based photodynamic therapy

NASA Astrophysics Data System (ADS)

Jermyn, Michael; Davis, Scott C.; Dehghani, Hamid; Huggett, Matthew T.; Hasan, Tayyaba; Pereira, Stephen P.; Bown, Stephen G.; Pogue, Brian W.

2014-04-01

The goal of this study was to determine dominant factors affecting treatment response in pancreatic cancer photodynamic therapy (PDT), based on clinically available information in the VERTPAC-01 trial. This trial investigated the safety and efficacy of verteporfin PDT in 15 patients with locally advanced pancreatic adenocarcinoma. CT scans before and after contrast enhancement from the 15 patients in the VERTPAC-01 trial were used to determine venous-phase blood contrast enhancement and this was correlated with necrotic volume determined from post-treatment CT scans, along with estimation of optical absorption in the pancreas for use in light modeling of the PDT treatment. Energy threshold contours yielded estimates for necrotic volume based on this light modeling. Both contrast-derived venous blood content and necrotic volume from light modeling yielded strong correlations with observed necrotic volume (R2 = 0.85 and 0.91, respectively). These correlations were much stronger than those obtained by correlating energy delivered versus necrotic volume in the VERTPAC-01 study and in retrospective analysis from a prior clinical study. This demonstrates that contrast CT can provide key surrogate dosimetry information to assess treatment response. It also implies that light attenuation is likely the dominant factor in the VERTPAC treatment response, as opposed to other factors such as drug distribution. This study is the first to show that contrast CT provides needed surrogate dosimetry information to predict treatment response in a manner which uses standard-of-care clinical images, rather than invasive dosimetry methods.

GIDEP Batching Tool

NASA Technical Reports Server (NTRS)

Fong, Danny; Odell,Dorice; Barry, Peter; Abrahamian, Tomik

2008-01-01

This software provides internal, automated search mechanics of GIDEP (Government- Industry Data Exchange Program) Alert data imported from the GIDEP government Web site. The batching tool allows the import of a single parts list in tab-delimited text format into the local JPL GIDEP database. Delimiters from every part number are removed. The original part numbers with delimiters are compared, as well as the newly generated list without the delimiters. The two lists run against the GIDEP imports, and output any matches. This feature only works with Netscape 2.0 or greater, or Internet Explorer 4.0 or greater. The user selects the browser button to choose a text file to import. When the submit button is pressed, this script will import alerts from the text file into the local JPL GIDEP database. This batch tool provides complete in-house control over exported material and data for automated batch match abilities. The batching tool has the ability to match capabilities of the parts list to tables, and yields results that aid further research and analysis. This provides more control over GIDEP information for metrics and reports information not provided by the government site. This software yields results quickly and gives more control over external data from the government site in order to generate other reports not available from the external source. There is enough space to store years of data. The program relates to risk identification and management with regard to projects and GIDEP alert information encompassing flight parts for space exploration.

Data presentation techniques for rotating machinery malfunction diagnosis

NASA Technical Reports Server (NTRS)

Spettel, T.

1985-01-01

Baseline steady state data is excellent for documentation of vibration signals at normal operating conditions. Assuming that a set of initial data was acquired with the machinery in a good state of repair, any future changes or deterioration in mechanical condition can be easily compared to the baseline information. Often this type of comparison will yield sufficient information for evaluation of the problem. However, many malfunctions require the analysis of transient data in order to identify the malfunction. Steady-state data formats consist of: Time Base Waveform, Orbit, Spectrum. Transient data formats consist of: Polar, Bode, Cascade. Our objective is to demonstrate the use of the above formats to diagnose a machine malfunction. A turbine-driven compressor train is chosen as an example. The machine train outline drawing is shown.

Low-dimensional approximation searching strategy for transfer entropy from non-uniform embedding

PubMed Central

2018-01-01

Transfer entropy from non-uniform embedding is a popular tool for the inference of causal relationships among dynamical subsystems. In this study we present an approach that makes use of low-dimensional conditional mutual information quantities to decompose the original high-dimensional conditional mutual information in the searching procedure of non-uniform embedding for significant variables at different lags. We perform a series of simulation experiments to assess the sensitivity and specificity of our proposed method to demonstrate its advantage compared to previous algorithms. The results provide concrete evidence that low-dimensional approximations can help to improve the statistical accuracy of transfer entropy in multivariate causality analysis and yield a better performance over other methods. The proposed method is especially efficient as the data length grows. PMID:29547669

Civil Affairs Language for Informing Cultural Operations (CALICO)

DTIC Science & Technology

2011-10-01

occasionally outline the results of their efforts.   Most of the first results of the search query  yielded  one or two page articles.  While the information...conducting a  GAP  analysis of the Civil Affairs organizational capability or simply serve as a validity check  for the existing Civil Affairs doctrine...the  gaps  in water and sanitation activities  needs assessment  evaluate sri methodology’s application on other crops  case management    General

United Nations High Commissioner for Refugees feeding program performance in Kenya and Tanzania: a retrospective analysis of routine Health Information System data.

PubMed

Tappis, Hannah; Doocy, Shannon; Haskew, Christopher; Wilkinson, Caroline; Oman, Allison; Spiegel, Paul

2012-06-01

The United Nations High Commissioner for Refugees (UNHCR) Health Information System is a primary source of routine nutrition program data and provides a comprehensive assessment of UNHCR selective feeding programs in more than 90 refugee camps in 18 countries worldwide. To evaluate the coverage and effectiveness of UNHCR supplementary and therapeutic feeding programs for malnourished children under 5 years of age in Kenya and Tanzania refugee camps. Analysis of Kenya and Tanzania refugee camp population, growth monitoring and nutrition program data from the UNHCR Health Information System. UNHCR-supported implementing partners in Kenya and Tanzania admitted nearly 45,000 malnourished refugee children in selective feeding programs between January 2006 and May 2009. Average recovery rates of 77.1% and 84.6% in the therapeutic and supplementary programs, respectively, mortality rates of less than 1%, and average readmission below 5% suggest that feeding programs had a beneficial effect on enrolled children. Increasing admission and enrollment in supplementary feeding programs was successful in preventing cases of severe malnutrition in some camps. Further attention to these camps would be likely to yield sizeable benefits in terms of absolute reductions in malnutrition prevalence and mortality rates.

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

PubMed

Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

2015-01-01

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

Detection of Cell Wall Chemical Variation in Zea Mays Mutants Using Near-Infrared Spectroscopy

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

Buyck, N.; Thomas, S.

Corn stover is regarded as the prime candidate feedstock material for commercial biomass conversion in the United States. Variations in chemical composition of Zea mays cell walls can affect biomass conversion process yields and economics. Mutant lines were constructed by activating a Mu transposon system. The cell wall chemical composition of 48 mutant families was characterized using near-infrared (NIR) spectroscopy. NIR data were analyzed using a multivariate statistical analysis technique called Principal Component Analysis (PCA). PCA of the NIR data from 349 maize leaf samples reveals 57 individuals as outliers on one or more of six Principal Components (PCs) atmore » the 95% confidence interval. Of these, 19 individuals from 16 families are outliers on either PC3 (9% of the variation) or PC6 (1% of the variation), the two PCs that contain information about cell wall polymers. Those individuals for which altered cell wall chemistry is confirmed with wet chemical analysis will then be subjected to fermentation analysis to determine whether or not biomass conversion process kinetics, yields and/or economics are significantly affected. Those mutants that provide indications for a decrease in process cost will be pursued further to identify the gene(s) responsible for the observed changes in cell wall composition and associated changes in process economics. These genes will eventually be incorporated into maize breeding programs directed at the development of a truly dual use crop.« less

Does technology acceleration equate to mask cost acceleration?

NASA Astrophysics Data System (ADS)

Trybula, Walter J.; Grenon, Brian J.

2003-06-01

The technology acceleration of the ITRS Roadmap has many implications on both the semiconductor sup-plier community and the manufacturers. INTERNATIONAL SEMATECH has revaluated the projected cost of advanced technology masks. Building on the methodology developed in 1996 for mask costs, this work provided a critical review of mask yields and factors relating to the manufacture of photolithography masks. The impact of the yields provided insight into the learning curve for leading edge mask manufac-turing. The projected mask set cost was surprising, and the ability to provide first and second year cost estimates provided additional information on technology introduction. From this information, the impact of technology acceleration can be added to the projected yields to evaluate the impact on mask costs.

Information yield: a comparison of Kodak T-Mat G, Ortho L and RP X-Omat films.

PubMed

Miles, D A; Van Dis, M L; Peterson, M G

1989-02-01

The information yield from two rare-earth screen-film combinations, Lanex Regular/T-Mat G (TMG) and Lanex regular/Ortho L (OL) has been compared with that from a conventional calcium-tungstate combination, X-Omatic regular/RP X-Omat (XRP), by means of perceptibility curves generated from an aluminum test object. The TMG and OL systems were faster than the XRP and the OL had the widest latitude. The maximum number of details perceived was similar for all three systems. The results support the suggestion that the TMG and OL systems permit more information to be perceived than XRP and that the newer imaging systems do not lose information despite their increased speed.

Comparison of methods of extracting information for meta-analysis of observational studies in nutritional epidemiology.

PubMed

Bae, Jong-Myon

2016-01-01

A common method for conducting a quantitative systematic review (QSR) for observational studies related to nutritional epidemiology is the "highest versus lowest intake" method (HLM), in which only the information concerning the effect size (ES) of the highest category of a food item is collected on the basis of its lowest category. However, in the interval collapsing method (ICM), a method suggested to enable a maximum utilization of all available information, the ES information is collected by collapsing all categories into a single category. This study aimed to compare the ES and summary effect size (SES) between the HLM and ICM. A QSR for evaluating the citrus fruit intake and risk of pancreatic cancer and calculating the SES by using the HLM was selected. The ES and SES were estimated by performing a meta-analysis using the fixed-effect model. The directionality and statistical significance of the ES and SES were used as criteria for determining the concordance between the HLM and ICM outcomes. No significant differences were observed in the directionality of SES extracted by using the HLM or ICM. The application of the ICM, which uses a broader information base, yielded more-consistent ES and SES, and narrower confidence intervals than the HLM. The ICM is advantageous over the HLM owing to its higher statistical accuracy in extracting information for QSR on nutritional epidemiology. The application of the ICM should hence be recommended for future studies.

Spatial variability effects on precision and power of forage yield estimation

USDA-ARS?s Scientific Manuscript database

Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...

Network meta-analysis: a technique to gather evidence from direct and indirect comparisons

PubMed Central

2017-01-01

Systematic reviews and pairwise meta-analyses of randomized controlled trials, at the intersection of clinical medicine, epidemiology and statistics, are positioned at the top of evidence-based practice hierarchy. These are important tools to base drugs approval, clinical protocols and guidelines formulation and for decision-making. However, this traditional technique only partially yield information that clinicians, patients and policy-makers need to make informed decisions, since it usually compares only two interventions at the time. In the market, regardless the clinical condition under evaluation, usually many interventions are available and few of them have been studied in head-to-head studies. This scenario precludes conclusions to be drawn from comparisons of all interventions profile (e.g. efficacy and safety). The recent development and introduction of a new technique – usually referred as network meta-analysis, indirect meta-analysis, multiple or mixed treatment comparisons – has allowed the estimation of metrics for all possible comparisons in the same model, simultaneously gathering direct and indirect evidence. Over the last years this statistical tool has matured as technique with models available for all types of raw data, producing different pooled effect measures, using both Frequentist and Bayesian frameworks, with different software packages. However, the conduction, report and interpretation of network meta-analysis still poses multiple challenges that should be carefully considered, especially because this technique inherits all assumptions from pairwise meta-analysis but with increased complexity. Thus, we aim to provide a basic explanation of network meta-analysis conduction, highlighting its risks and benefits for evidence-based practice, including information on statistical methods evolution, assumptions and steps for performing the analysis. PMID:28503228

Antipsychotic-induced weight gain: a comprehensive research synthesis.

PubMed

Allison, D B; Mentore, J L; Heo, M; Chandler, L P; Cappelleri, J C; Infante, M C; Weiden, P J

1999-11-01

The purpose of this study was to estimate and compare the effects of antipsychotics-both the newer ones and the conventional ones-on body weight. A comprehensive literature search identified 81 English- and non-English-language articles that included data on weight change in antipsychotic-treated patients. For each agent, a meta-analysis and random effects metaregression estimated the weight change after 10 weeks of treatment at a standard dose. A comprehensive narrative review was also conducted on all articles that did not yield quantitative information but did yield important qualitative information. Placebo was associated with a mean weight reduction of 0.74 kg. Among conventional agents, mean weight change ranged from a reduction of 0.39 kg with molindone to an increase of 3.19 kg with thioridazine. Among newer antipsychotic agents, mean increases were as follows: clozapine, 4.45 kg; olanzapine, 4.15 kg; sertindole, 2.92 kg; risperidone, 2.10 kg; and ziprasidone, 0.04 kg. Insufficient data were available to evaluate quetiapine at 10 weeks. Both conventional and newer antipsychotics are associated with weight gain. Among the newer agents, clozapine appears to have the greatest potential to induce weight gain, and ziprasidone the least. The differences among newer agents may affect compliance with medication and health risk.

ANALYSIS OF CLINICAL AND DERMOSCOPIC FEATURES FOR BASAL CELL CARCINOMA NEURAL NETWORK CLASSIFICATION

PubMed Central

Cheng, Beibei; Stanley, R. Joe; Stoecker, William V; Stricklin, Sherea M.; Hinton, Kristen A.; Nguyen, Thanh K.; Rader, Ryan K.; Rabinovitz, Harold S.; Oliviero, Margaret; Moss, Randy H.

2012-01-01

Background Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the United States. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features. Methods Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural network-based techniques, including Evolving Artificial Neural Networks and Evolving Artificial Neural Network Ensembles. Results Experiment results based on ten-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories. Conclusions Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process. PMID:22724561

Deep-space navigation with differenced data types. Part 3: An expanded information content and sensitivity analysis

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Thurman, S. W.

1992-01-01

An approximate six-parameter analytic model for Earth-based differential range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, Deep Space Network station oscillator (clock/frequency) offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Quantitative results indicate that a few differenced Doppler plus ranging passes yield angular position estimates with a precision on the order of 0.1 to 0.4 micro-rad, and angular rate precision on the order of 10 to 25 x 10(exp -12) rad/sec, assuming no a priori information on the coordinate parameters. Sensitivity analyses suggest that troposphere zenith delay calibration error is the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to troposphere calibration errors than differenced range. By comparison, results computed using wideband and narrowband (delta) VLBI under similar circumstances yielded angular precisions of 0.07 to 0.4 micro-rad, and angular rate precisions of 0.5 to 1.0 x 10(exp -12) rad/sec.

Deep-space navigation with differenced data types. Part 3: An expanded information content and sensitivity analysis

NASA Technical Reports Server (NTRS)

Estefan, J. A.; Thurman, S. W.

1992-01-01

An approximate six-parameter analytic model for Earth-based differenced range measurements is presented and is used to derive a representative analytic approximation for differenced Doppler measurements. The analytical models are tasked to investigate the ability of these data types to estimate spacecraft geocentric angular motion, Deep Space Network station oscillator (clock/frequency) offsets, and signal-path calibration errors over a period of a few days, in the presence of systematic station location and transmission media calibration errors. Quantitative results indicate that a few differenced Doppler plus ranging passes yield angular position estimates with a precision on the order of 0.1 to 0.4 microrad, and angular rate precision on the order of 10 to 25(10)(exp -12) rad/sec, assuming no a priori information on the coordinate parameters. Sensitivity analyses suggest that troposphere zenith delay calibration error is the dominant systematic error source in most of the tracking scenarios investigated; as expected, the differenced Doppler data were found to be much more sensitive to troposphere calibration errors than differenced range. By comparison, results computed using wide band and narrow band (delta)VLBI under similar circumstances yielded angular precisions of 0.07 to 0.4 /microrad, and angular rate precisions of 0.5 to 1.0(10)(exp -12) rad/sec.

Simultaneous extraction of proteins and metabolites from cells in culture

PubMed Central

Sapcariu, Sean C.; Kanashova, Tamara; Weindl, Daniel; Ghelfi, Jenny; Dittmar, Gunnar; Hiller, Karsten

2014-01-01

Proper sample preparation is an integral part of all omics approaches, and can drastically impact the results of a wide number of analyses. As metabolomics and proteomics research approaches often yield complementary information, it is desirable to have a sample preparation procedure which can yield information for both types of analyses from the same cell population. This protocol explains a method for the separation and isolation of metabolites and proteins from the same biological sample, in order for downstream use in metabolomics and proteomics analyses simultaneously. In this way, two different levels of biological regulation can be studied in a single sample, minimizing the variance that would result from multiple experiments. This protocol can be used with both adherent and suspension cell cultures, and the extraction of metabolites from cellular medium is also detailed, so that cellular uptake and secretion of metabolites can be quantified. Advantages of this technique includes:1.Inexpensive and quick to perform; this method does not require any kits.2.Can be used on any cells in culture, including cell lines and primary cells extracted from living organisms.3.A wide variety of different analysis techniques can be used, adding additional value to metabolomics data analyzed from a sample; this is of high value in experimental systems biology. PMID:26150938

A review of the global relationship among freshwater fish, autotrophic activity, and regional climate

USGS Publications Warehouse

Deines, Andrew M.; Bunnell, David B.; Rogers, Mark W.; Beard, T. Douglas; Taylor, William W.

2015-01-01

The relationship between autotrophic activity and freshwater fish populations is an important consideration for ecologists describing trophic structure in aquatic communities, fisheries managers tasked with increasing sustainable fisheries development, and fish farmers seeking to maximize production. Previous studies of the empirical relationships of autotrophic activity and freshwater fish yield have found positive relationships but were limited by small sample sizes, small geographic scopes, and the inability to compare patterns among many types of measurement techniques. Individual studies and reviews have also lacked consistent consideration of regional climate factors which may inform relationships between fisheries and autotrophic activity. We compiled data from over 700 freshwater systems worldwide and used meta-analysis and linear models to develop a comprehensive global synthesis between multiple metrics of autotrophic activity, fisheries, and climate indicators. Our results demonstrate that multiple metrics of fish (i.e., catch per unit effort, yield, and production) increase with autotrophic activity across a variety of fisheries. At the global scale additional variation in this positive relationship can be ascribed to regional climate differences (i.e., temperature and precipitation) across systems. Our results provide a method and proof-of-concept for assessing inland fisheries production at the global scale, where current estimates are highly uncertain, and may therefore inform the continued sustainable use of global inland fishery resources.

What did Erwin mean? The physics of information from the materials genomics of aperiodic crystals and water to molecular information catalysts and life.

PubMed

Varn, D P; Crutchfield, J P

2016-03-13

Erwin Schrödinger famously and presciently ascribed the vehicle transmitting the hereditary information underlying life to an 'aperiodic crystal'. We compare and contrast this, only later discovered to be stored in the linear biomolecule DNA, with the information-bearing, layered quasi-one-dimensional materials investigated by the emerging field of chaotic crystallography. Despite differences in functionality, the same information measures capture structure and novelty in both, suggesting an intimate coherence between the information character of biotic and abiotic matter-a broadly applicable physics of information. We review layered solids and consider three examples of how information- and computation-theoretic techniques are being applied to understand their structure. In particular, (i) we review recent efforts to apply new kinds of information measures to quantify disordered crystals; (ii) we discuss the structure of ice I in information-theoretic terms; and (iii) we recount recent investigations into the structure of tris(bicyclo[2.1.1]hexeno)benzene, showing how an information-theoretic analysis yields additional insight into its structure. We then illustrate a new Second Law of Thermodynamics that describes information processing in active low-dimensional materials, reviewing Maxwell's Demon and a new class of molecular devices that act as information catalysts. Lastly, we conclude by speculating on how these ideas from informational materials science may impact biology. © 2016 The Author(s).

Some Notes on Information Theory and Its Applications

EPA Science Inventory

Information is in the purest sense one of the most fundamental quantities in nature, and the study of information can often yield fundamental insights that cannot otherwise be obtained. For example, starting from a form of information arising from the work of the statistician R....

77 FR 36489 - Agency Information Collection Activities: Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-19

... collection methods, including interviews and research, to inform the design, development, and implementation.... For example, information collected from consumers will help the CFPB to design model forms... used for quantitative information collections that are designed to yield statistically significant...

Reduced product yield in chemical processes by second law effects

NASA Technical Reports Server (NTRS)

England, C.; Funk, J. E.

1980-01-01

An analysis of second law effects in chemical processes, where product yield is explicitly related to the individual irreversibilities within the process to indicate a maximum theoretical yield, is presented. Examples are given that indicate differences between first and second law approaches toward process efficiency and process yield. This analysis also expresses production capacity in terms of the heating value of a product. As a result, it is particularly convenient in analyzing fuel conversion plants and their potential for improvement. Relationships are also given for the effects of irreversibilities on requirements for process heat and for feedstocks.

Protons in head-and-neck cancer: bridging the gap of evidence.

PubMed

Ramaekers, Bram L T; Grutters, Janneke P C; Pijls-Johannesma, Madelon; Lambin, Philippe; Joore, Manuela A; Langendijk, Johannes A

2013-04-01

To use Normal Tissue Complication Probability (NTCP) models and comparative planning studies to explore the (cost-)effectiveness of swallowing sparing intensity modulated proton radiotherapy (IMPT) compared with swallowing sparing intensity modulated radiotherapy with photons (IMRT) in head and neck cancer (HNC). A Markov model was constructed to examine and compare the costs and quality-adjusted life years (QALYs) of the following strategies: (1) IMPT for all patients; (2) IMRT for all patients; and (3) IMPT if efficient. The assumption of equal survival for IMPT and IMRT in the base case analysis was relaxed in a sensitivity analysis. Intensity modulated proton radiation therapy and IMRT for all patients yielded 6.620 and 6.520 QALYs and cost €50,989 and €41,038, respectively. Intensity modulated proton radiation therapy if efficient yielded 6.563 QALYs and cost €43,650. The incremental cost-effectiveness ratio of IMPT if efficient versus IMRT for all patients was €60,278 per QALY gained. In the sensitivity analysis, IMRT was more effective (0.967 QALYs) and less expensive (€8218) and thus dominated IMPT for all patients. Cost-effectiveness analysis based on normal tissue complication probability models and planning studies proved feasible and informative and enables the analysis of individualized strategies. The increased effectiveness of IMPT does not seem to outweigh the higher costs for all head-and-neck cancer patients. However, when assuming equal survival among both modalities, there seems to be value in identifying those patients for whom IMPT is cost-effective. Copyright © 2013 Elsevier Inc. All rights reserved.

Protein Inference from the Integration of Tandem MS Data and Interactome Networks.

PubMed

Zhong, Jiancheng; Wang, Jianxing; Ding, Xiaojun; Zhang, Zhen; Li, Min; Wu, Fang-Xiang; Pan, Yi

2017-01-01

Since proteins are digested into a mixture of peptides in the preprocessing step of tandem mass spectrometry (MS), it is difficult to determine which specific protein a shared peptide belongs to. In recent studies, besides tandem MS data and peptide identification information, some other information is exploited to infer proteins. Different from the methods which first use only tandem MS data to infer proteins and then use network information to refine them, this study proposes a protein inference method named TMSIN, which uses interactome networks directly. As two interacting proteins should co-exist, it is reasonable to assume that if one of the interacting proteins is confidently inferred in a sample, its interacting partners should have a high probability in the same sample, too. Therefore, we can use the neighborhood information of a protein in an interactome network to adjust the probability that the shared peptide belongs to the protein. In TMSIN, a multi-weighted graph is constructed by incorporating the bipartite graph with interactome network information, where the bipartite graph is built with the peptide identification information. Based on multi-weighted graphs, TMSIN adopts an iterative workflow to infer proteins. At each iterative step, the probability that a shared peptide belongs to a specific protein is calculated by using the Bayes' law based on the neighbor protein support scores of each protein which are mapped by the shared peptides. We carried out experiments on yeast data and human data to evaluate the performance of TMSIN in terms of ROC, q-value, and accuracy. The experimental results show that AUC scores yielded by TMSIN are 0.742 and 0.874 in yeast dataset and human dataset, respectively, and TMSIN yields the maximum number of true positives when q-value less than or equal to 0.05. The overlap analysis shows that TMSIN is an effective complementary approach for protein inference.

Analysis of a large dataset of mycorrhiza inoculation field trials on potato shows highly significant increases in yield.

PubMed

Hijri, Mohamed

2016-04-01

An increasing human population requires more food production in nutrient-efficient systems in order to simultaneously meet global food needs while reducing the environmental footprint of agriculture. Arbuscular mycorrhizal fungi (AMF) have the potential to enhance crop yield, but their efficiency has yet to be demonstrated in large-scale crop production systems. This study reports an analysis of a dataset consisting of 231 field trials in which the same AMF inoculant (Rhizophagus irregularis DAOM 197198) was applied to potato over a 4-year period in North America and Europe under authentic field conditions. The inoculation was performed using a liquid suspension of AMF spores that was sprayed onto potato seed pieces, yielding a calculated 71 spores per seed piece. Statistical analysis showed a highly significant increase in marketable potato yield (ANOVA, P < 0.0001) for inoculated fields (42.2 tons/ha) compared with non-inoculated controls (38.3 tons/ha), irrespective of trial year. The average yield increase was 3.9 tons/ha, representing 9.5 % of total crop yield. Inoculation was profitable with a 0.67-tons/ha increase in yield, a threshold reached in almost 79 % of all trials. This finding clearly demonstrates the benefits of mycorrhizal-based inoculation on crop yield, using potato as a case study. Further improvements of these beneficial inoculants will help compensate for crop production deficits, both now and in the future.

Molecular Basis for Cyclooxygenase Inhibition by the Non-steroidal Anti-inflammatory Drug Naproxen

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

Duggan, Kelsey C.; Walters, Matthew J.; Musee, Joel

Naproxen ((S)-6-methoxy-{alpha}-methyl-2-naphthaleneacetic acid) is a powerful non-selective non-steroidal anti-inflammatory drug that is extensively used as a prescription and over-the-counter medication. Naproxen exhibits gastrointestinal toxicity, but its cardiovascular toxicity may be reduced compared with other drugs in its class. Despite the fact that naproxen has been marketed for many years, the molecular basis of its interaction with cyclooxygenase (COX) enzymes is unknown. We performed a detailed study of naproxen-COX-2 interactions using site-directed mutagenesis, structure-activity analysis, and x-ray crystallography. The results indicate that each of the pendant groups of the naphthyl scaffold are essential for COX inhibition, and only minimal substitutions aremore » tolerated. Mutation of Trp-387 to Phe significantly reduced inhibition by naproxen, a result that appears unique to this inhibitor. Substitution of S or CH2 for the O atom of the p-methoxy group yielded analogs that were not affected by the W387F substitution and that exhibited increased COX-2 selectivity relative to naproxen. Crystallization and x-ray analysis yielded structures of COX-2 complexed to naproxen and its methylthio analog at 1.7 and 2.3 {angstrom} resolution, respectively. The combination of mutagenesis, structure analysis, and x-ray crystallography provided comprehensive information on the unique interactions responsible for naproxen binding to COX-2.« less

Seismic attribute analysis for reservoir and fluid prediction, Malay Basin

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

Mansor, M.N.; Rudolph, K.W.; Richards, F.B.

1994-07-01

The Malay Basin is characterized by excellent seismic data quality, but complex clastic reservoir architecture. With these characteristics, seismic attribute analysis is a very important tool in exploration and development geoscience and is routinely used for mapping fluids and reservoir, recognizing and risking traps, assessment, depth conversion, well placement, and field development planning. Attribute analysis can be successfully applied to both 2-D and 3-D data as demonstrated by comparisons of 2-D and 3-D amplitude maps of the same area. There are many different methods of extracting amplitude information from seismic data, including amplitude mapping, horizon slice, summed horizon slice, isochronmore » slice, and horizon slice from AVO (amplitude versus offset) cube. Within the Malay Basin, horizon/isochron slice techniques have several advantages over simply extracting amplitudes from a picked horizon: they are much faster, permit examination of the amplitude structure of the entire cube, yield better results for weak/variable signatures, and aid summation of amplitudes. Summation in itself often yields improved results because it incorporates the signature from the entire reservoir interval, reducing any effects due to noise, mispicking, or waveform variations. Dip and azimuth attributes have been widely applied by industry for fault identification. In addition, these attributes can also be used to map signature variations associated with hydrocarbon contacts or stratigraphic changes, and this must be considered when using these attributes for structural interpretation.« less

Batch culture characterization and metabolic flux analysis of succinate-producing Escherichia coli strains.

PubMed

Sánchez, Ailen M; Bennett, George N; San, Ka-Yiu

2006-05-01

This study presents an in-depth analysis of the anaerobic metabolic fluxes of various mutant strains of Escherichia coli overexpressing the Lactococcus lactis pyruvate carboxylase (PYC) for the production of succinate. Previously, a metabolic network design that includes an active glyoxylate pathway implemented in vivo increased succinate yield from glucose in an E. coli mutant to 1.6 mol/mol under fully anaerobic conditions. The design consists of a dual succinate synthesis route, which diverts required quantities of NADH through the traditional fermentative pathway and maximizes the carbon converted to succinate by balancing the carbon flux through the fermentative pathway and the glyoxylate pathway (which has a lower NADH requirement). Mutant strains previously constructed during the development of high-yield succinate-producing strains were selected for further characterization to understand their metabolic response as a result of several genetic manipulations and to determine the significance of the fermentative and the glyoxylate pathways in the production of succinate. Measured fluxes obtained under batch cultivation conditions were used to estimate intracellular fluxes and identify critical branch point flux split ratios. The comparison of changes in branch point flux split ratios to the glyoxylate pathway and the fermentative pathway at the oxaloacetate (OAA) node as a result of different mutations revealed the sensitivity of succinate yield to these manipulations. The most favorable split ratio to obtain the highest succinate yield was the fractional partition of OAA to glyoxylate of 0.32 and 0.68 to the fermentative pathway obtained in strains SBS550MG (pHL413) and SBS990MG (pHL413). The succinate yields achieved in these two strains were 1.6 and 1.7 mol/mol, respectively. In addition, an active glyoxylate pathway in an ldhA, adhE, ack-pta mutant strain is shown to be responsible for the high succinate yields achieved anaerobically. Furthermore, in vitro activity measurements of seven crucial enzymes involved in the pathways studied and intracellular measurements of key intermediate metabolite pools provided additional insights on the physiological perturbations caused by these mutations. The characterization of these recombinant mutant strains in terms of flux distribution pattern, in vitro enzyme activity and intracellular metabolite pools provides useful information for the rational modification of metabolic fluxes to improve succinate production.

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

NASA Technical Reports Server (NTRS)

Bassu, Simona; Brisson, Nadine; Grassini, Patricio; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W.; Rosenzweig, Cynthia; Ruane, Alex C.; Adam, Myriam;

How do various maize crop models vary in their responses to climate change factors?

PubMed

Bassu, Simona; Brisson, Nadine; Durand, Jean-Louis; Boote, Kenneth; Lizaso, Jon; Jones, James W; Rosenzweig, Cynthia; Ruane, Alex C; Adam, Myriam; Baron, Christian; Basso, Bruno; Biernath, Christian; Boogaard, Hendrik; Conijn, Sjaak; Corbeels, Marc; Deryng, Delphine; De Sanctis, Giacomo; Gayler, Sebastian; Grassini, Patricio; Hatfield, Jerry; Hoek, Steven; Izaurralde, Cesar; Jongschaap, Raymond; Kemanian, Armen R; Kersebaum, K Christian; Kim, Soo-Hyung; Kumar, Naresh S; Makowski, David; Müller, Christoph; Nendel, Claas; Priesack, Eckart; Pravia, Maria Virginia; Sau, Federico; Shcherbak, Iurii; Tao, Fulu; Teixeira, Edmar; Timlin, Dennis; Waha, Katharina

2014-07-01

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2 ], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(-1) per °C. Doubling [CO2 ] from 360 to 720 μmol mol(-1) increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2 ] among models. Model responses to temperature and [CO2 ] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information. © 2014 John Wiley & Sons Ltd.

The application of drug dose equivalence in the quantitative analysis of receptor occupation and drug combinations

PubMed Central

Tallarida, Ronald J.; Raffa, Robert B.

2014-01-01

In this review we show that the concept of dose equivalence for two drugs, the theoretical basis of the isobologram, has a wider use in the analysis of pharmacological data derived from single and combination drug use. In both its application to drug combination analysis with isoboles and certain other actions, listed below, the determination of doses, or receptor occupancies, that yield equal effects provide useful metrics that can be used to obtain quantitative information on drug actions without postulating any intimate mechanism of action. These other drug actions discussed here include (1) combinations of agonists that produce opposite effects, (2) analysis of inverted U-shaped dose effect curves of single agents, (3) analysis on the effect scale as an alternative to isoboles and (4) the use of occupation isoboles to examine competitive antagonism in the dual receptor case. New formulas derived to assess the statistical variance for additive combinations are included, and the more detailed mathematical topics are included in the appendix. PMID:20546783

Correlation analysis of targeted proteins and metabolites to assess and engineer microbial isopentenol production.

PubMed

George, Kevin W; Chen, Amy; Jain, Aakriti; Batth, Tanveer S; Baidoo, Edward E K; Wang, George; Adams, Paul D; Petzold, Christopher J; Keasling, Jay D; Lee, Taek Soon

2014-08-01

The ability to rapidly assess and optimize heterologous pathway function is critical for effective metabolic engineering. Here, we develop a systematic approach to pathway analysis based on correlations between targeted proteins and metabolites and apply it to the microbial production of isopentenol, a promising biofuel. Starting with a seven-gene pathway, we performed a correlation analysis to reduce pathway complexity and identified two pathway proteins as the primary determinants of efficient isopentenol production. Aided by the targeted quantification of relevant pathway intermediates, we constructed and subsequently validated a conceptual model of isopentenol pathway function. Informed by our analysis, we assembled a strain which produced isopentenol at a titer 1.5 g/L, or 46% of theoretical yield. Our engineering approach allowed us to accurately identify bottlenecks and determine appropriate pathway balance. Paired with high-throughput cloning techniques and analytics, this strategy should prove useful for the analysis and optimization of increasingly complex heterologous pathways. © 2014 Wiley Periodicals, Inc.

Porous Graphitic Carbon Liquid Chromatography-Mass Spectrometry Analysis of Drought Stress-Responsive Raffinose Family Oligosaccharides in Plant Tissues.

PubMed

Jorge, Tiago F; Florêncio, Maria H; António, Carla

2017-01-01

Drought is a major limiting factor in agriculture and responsible for dramatic crop yield losses worldwide. The adjustment of the metabolic status via accumulation of drought stress-responsive osmolytes is one of the many strategies that some plants have developed to cope with water deficit conditions. Osmolytes are highly polar compounds, analysis of whcih is difficult with typical reversed-phase chromatography. Porous graphitic carbon (PGC) has shown to be a suitable alternative to reversed-phase stationary phases for the analysis of highly polar compounds typically found in the plant metabolome. In this chapter, we describe the development and validation of a PGC-based liquid chromatography tandem mass spectrometry (LC-MS n ) method suitable for the target analysis of water-soluble carbohydrates, such as raffinose family oligosaccharides (RFOs). We present detailed information regarding PGC column equilibration, LC-MS n system operation, data analysis, and important notes to be considered during the steps of method development and validation.

Assessment of the SWAT model to simulate a watershed with limited available data in the Pampas region, Argentina.

PubMed

Romagnoli, Martín; Portapila, Margarita; Rigalli, Alfredo; Maydana, Gisela; Burgués, Martín; García, Carlos M

2017-10-15

Argentina has been among the world leaders in the production and export of agricultural products since the 1990s. The Carcarañá River Lower Basin (CRLB), a cropland of the Pampas region supplied by extensive rainfall, is located in an area with few streamgauging and other hydrologic/water-quality stations. Therefore, limited hydrologic data are available resulting in limited water-resources assessment. This work explores the application of Soil and Water Assessment Tool (SWAT) model to the CRLB in the Santa Fe province of the Pampas region. The analysis of field and remote-sensing data characterizing hydrology, water quality, soil types, land use/land cover, management practices, and crop yield, guarantee a comprehensive SWAT modeling approach. A combined manual and automated calibration and validation process incorporating sensitivity and uncertainty analysis is performed using information concerning interior watershed processes. Eleven N/P fertilizer rates are selected to simulate the impact of N fertilizer on crop yield, plant uptake, as well as runoff and leaching losses. Different indices (partial factor productivity, agronomic efficiency, apparent crop recovery efficiency of applied nutrient, internal utilization efficiency, and physiological efficiency) are considered to assess nitrogen-use efficiency. The overall quality of the fit is satisfactory considering the input data limitations. This work provides, for the first time in Argentina, a reliable tool to simulate yield response to soil quality and water availability capable to meet defined environmental targets to support decision making on planning public policies and private activities on the Pampas region. Copyright © 2017 Elsevier B.V. All rights reserved.

Linkages and Interactions Analysis of Major Effect Drought Grain Yield QTLs in Rice.

PubMed

Vikram, Prashant; Swamy, B P Mallikarjuna; Dixit, Shalabh; Trinidad, Jennylyn; Sta Cruz, Ma Teresa; Maturan, Paul C; Amante, Modesto; Kumar, Arvind

2016-01-01

Quantitative trait loci conferring high grain yield under drought in rice are important genomic resources for climate resilient breeding. Major and consistent drought grain yield QTLs usually co-locate with flowering and/or plant height QTLs, which could be due to either linkage or pleiotropy. Five mapping populations used for the identification of major and consistent drought grain yield QTLs underwent multiple-trait, multiple-interval mapping test (MT-MIM) to estimate the significance of pleiotropy effects. Results indicated towards possible linkages between the drought grain yield QTLs with co-locating flowering and/or plant height QTLs. Linkages of days to flowering and plant height were eliminated through a marker-assisted breeding approach. Drought grain yield QTLs also showed interaction effects with flowering QTLs. Drought responsiveness of the flowering locus on chromosome 3 (qDTY3.2) has been revealed through allelic analysis. Considering linkage and interaction effects associated with drought QTLs, a comprehensive marker-assisted breeding strategy was followed to develop rice genotypes with improved grain yield under drought stress.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

NASA Astrophysics Data System (ADS)

He, M.; Kimball, J. S.; Maneta, M. P.; Maxwell, B. D.; Moreno, A.

2017-12-01

Accurate crop yield assessments using satellite-based remote sensing are of interest for the design of regional policies that promote agricultural resiliency and food security. However, the application of current vegetation productivity algorithms derived from global satellite observations are generally too coarse to capture cropland heterogeneity. Merging information from sensors with reciprocal spatial and temporal resolution can improve the accuracy of these retrievals. In this study, we estimate annual crop yields for seven important crop types -alfalfa, barley, corn, durum wheat, peas, spring wheat and winter wheat over Montana, United States (U.S.) from 2008 to 2015. Yields are estimated as the product of gross primary production (GPP) and a crop-specific harvest index (HI) at 30 m spatial resolution. To calculate GPP we used a modified form of the MOD17 LUE algorithm driven by a 30 m 8-day fused NDVI dataset constructed by blending Landsat (5 or 7) and MODIS Terra reflectance data. The fused 30-m NDVI record shows good consistency with the original Landsat and MODIS data, but provides better spatiotemporal information on cropland vegetation growth. The resulting GPP estimates capture characteristic cropland patterns and seasonal variations, while the estimated annual 30 m crop yield results correspond favorably with county-level crop yield data (r=0.96, p<0.05). The estimated crop yield performance was generally lower, but still favorable in relation to field-scale crop yield surveys (r=0.42, p<0.01). Our methods and results are suitable for operational applications at regional scales.

Intelligent systems for the autonomous exploration of Titan and Enceladus

NASA Astrophysics Data System (ADS)

Furfaro, Roberto; Lunine, Jonathan I.; Kargel, Jeffrey S.; Fink, Wolfgang

2008-04-01

Future planetary exploration of the outer satellites of the Solar System will require higher levels of onboard automation, including autonomous determination of sites where the probability of significant scientific findings is highest. Generally, the level of needed automation is heavily influenced by the distance between Earth and the robotic explorer(s) (e.g. spacecraft(s), rover(s), and balloon(s)). Therefore, planning missions to the outer satellites mandates the analysis, design and integration within the mission architecture of semi- and/or completely autonomous intelligence systems. Such systems should (1) include software packages that enable fully automated and comprehensive identification, characterization, and quantification of feature information within an operational region with subsequent target prioritization and selection for close-up reexamination; and (2) integrate existing information with acquired, "in transit" spatial and temporal sensor data to automatically perform intelligent planetary reconnaissance, which includes identification of sites with the highest potential to yield significant geological and astrobiological information. In this paper we review and compare some of the available Artificial Intelligence (AI) schemes and their adaptation to the problem of designing expert systems for onboard-based, autonomous science to be performed in the course of outer satellites exploration. More specifically, the fuzzy-logic framework proposed is analyzed in some details to show the effectiveness of such a scheme when applied to the problem of designing expert systems capable of identifying and further exploring regions on Titan and/or Enceladus that have the highest potential to yield evidence for past or present life. Based on available information (e.g., Cassini data), the current knowledge and understanding of Titan and Enceladus environments is evaluated to define a path for the design of a fuzzy-based system capable of reasoning over collected data and capable of providing the inference required to autonomously optimize future outer satellites explorations.

Minimum number of measurements for evaluating soursop (Annona muricata L.) yield.

PubMed

Sánchez, C F B; Teodoro, P E; Londoño, S; Silva, L A; Peixoto, L A; Bhering, L L

2017-05-31

Repeatability studies on fruit species are of great importance to identify the minimum number of measurements necessary to accurately select superior genotypes. This study aimed to identify the most efficient method to estimate the repeatability coefficient (r) and predict the minimum number of measurements needed for a more accurate evaluation of soursop (Annona muricata L.) genotypes based on fruit yield. Sixteen measurements of fruit yield from 71 soursop genotypes were carried out between 2000 and 2016. In order to estimate r with the best accuracy, four procedures were used: analysis of variance, principal component analysis based on the correlation matrix, principal component analysis based on the phenotypic variance and covariance matrix, and structural analysis based on the correlation matrix. The minimum number of measurements needed to predict the actual value of individuals was estimated. Principal component analysis using the phenotypic variance and covariance matrix provided the most accurate estimates of both r and the number of measurements required for accurate evaluation of fruit yield in soursop. Our results indicate that selection of soursop genotypes with high fruit yield can be performed based on the third and fourth measurements in the early years and/or based on the eighth and ninth measurements at more advanced stages.

The molecular orientation of CO on Pd(1 1 1): a polarization-dependent SFG study

NASA Astrophysics Data System (ADS)

Galletto, Paolo; Unterhalt, Holger; Rupprechter, Günther

2003-01-01

The molecular orientation of carbon monoxide adsorbed on Pd(1 1 1) was examined by sum frequency generation (SFG) vibrational spectroscopy utilizing different polarization combinations of the visible and SFG light. This allows to determine the CO tilt angle with respect to the substrate, provided that a proper optical model for the interface can be defined. It is demonstrated that it is essential to invoke the βaac hyperpolarizability into the analysis and that polarization-dependent SFG of CO/Pd(1 1 1) yields information on βaac/ βccc rather than the tilt angle.

Analysis of pigments in polychromes by use of laser induced breakdown spectroscopy and Raman microscopy

NASA Astrophysics Data System (ADS)

Castillejo, M.; Martín, M.; Silva, D.; Stratoudaki, T.; Anglos, D.; Burgio, L.; Clark, R. J. H.

2000-09-01

Two laser-based analytical techniques, Laser Induced Breakdown Spectroscopy (LIBS) and Raman microscopy, have been used for the identification of pigments on a polychrome from the Rococo period. Detailed spectral data are presented from analyses performed on a fragment of a gilded altarpiece from the church of Escatrón, Zaragoza, Spain. LIBS measurements yielded elemental analytical data which suggest the presence of certain pigments and, in addition, provide information on the stratigraphy of the paint layers. Identification of most pigments and of the materials used in the preparation layer was performed by Raman microscopy.

The suitability of common compressibility equations for characterizing plasticity of diverse powders.

PubMed

Paul, Shubhajit; Sun, Changquan Calvin

2017-10-30

The analysis of powder compressibility data yields useful information for characterizing compaction behavior and mechanical properties of powders, especially plasticity. Among the many compressibility equations proposed in powder compaction research, the Heckel equation and the Kawakita equation are the most commonly used, despite their known limitations. Systematic evaluation of the performance in analyzing compressibility data suggested the Kuentz-Leuenberger equation is superior to both the Heckel equation and the Kawakita equation for characterizing plasticity of powders exhibiting a wide range of mechanical properties. Copyright © 2017 Elsevier B.V. All rights reserved.