A COMPARATIVE STUDY OF FORECASTING MODELS FOR TREND AND SEASONAL TIME SERIES DOES COMPLEX MODEL ALWAYS YIELD BETTER FORECAST THAN SIMPLE MODELS

Directory of Open Access Journals (Sweden)

Suhartono Suhartono

2005-01-01

Full Text Available Many business and economic time series are non-stationary time series that contain trend and seasonal variations. Seasonality is a periodic and recurrent pattern caused by factors such as weather, holidays, or repeating promotions. A stochastic trend is often accompanied with the seasonal variations and can have a significant impact on various forecasting methods. In this paper, we will investigate and compare some forecasting methods for modeling time series with both trend and seasonal patterns. These methods are Winter's, Decomposition, Time Series Regression, ARIMA and Neural Networks models. In this empirical research, we study on the effectiveness of the forecasting performance, particularly to answer whether a complex method always give a better forecast than a simpler method. We use a real data, that is airline passenger data. The result shows that the more complex model does not always yield a better result than a simpler one. Additionally, we also find the possibility to do further research especially the use of hybrid model by combining some forecasting method to get better forecast, for example combination between decomposition (as data preprocessing and neural network model.

A Remote Sensing-Derived Corn Yield Assessment Model

Science.gov (United States)

Shrestha, Ranjay Man

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

Forecasting olive crop yields based on long-term aero biological data series and bio climatic conditions for the southern Iberian Peninsula

Energy Technology Data Exchange (ETDEWEB)

Aguilera, F.; Ruiz-Valenzuela, L.

2014-06-01

In the present study, bio-meteorological models for predicting olive-crop production in the southern Iberian Peninsula were developed. These covered a 16-year period: 1994-2009. The forecasting models were constructed using the partial least-squares regression method, taking the annual olive yield as the dependent variable, and both aero biological and meteorological parameters as the independent variables. Two regression models were built for the prediction of crop production prior to the final harvest at two different times of the year: July and November. The percentage variance explained by the models was between 83% and 93%. Through these forecasting models, the main factors that influence olive-crop yield were identified. Pollen index and accumulated precipitation, especially as rain recorded during the pre-flowering months, were the most important parameters for providing an explanation of fluctuations in fruit production. The temperature recorded during the two months preceding budburst was another important variable, which showed positive effects on the final yield. The July model that provides accurate predictions of fruit production eight months prior to the final harvest is proposed as an optimal model to forecast fruit produced by olive trees in western Mediterranean areas. (Author)

Rice yield estimation with multi-temporal Radarsat-2 data

Science.gov (United States)

Chen, Chi-Farn; Son, Nguyen-Thanh; Chen, Cheng-Ru

2015-04-01

Rice is the most important food crop in Taiwan. Monitoring rice crop yield is thus crucial for agronomic planners to formulate successful strategies to address national food security and rice grain export issues. However, there is a real challenge for this monitoring purpose because the size of rice fields in Taiwan was generally small and fragmented, and the cropping calendar was also different from region to region. Thus, satellite-based estimation of rice crop yield requires the data that have sufficient spatial and temporal resolutions. This study aimed to develop models to estimate rice crop yield from multi-temporal Radarsat-2 data (5 m resolution). Data processing were carried out for the first rice cropping season from February to July in 2014 in the western part of Taiwan, consisting of four main steps: (1) constructing time-series backscattering coefficient data, (2) spatiotemporal noise filtering of the time-series data, (3) establishment of crop yield models using the time-series backscattering coefficients and in-situ measured yield data, and (4) model validation using field data and government's yield statistics. The results indicated that backscattering behavior varied from region to region due to changes in cultural practices and cropping calendars. The highest correlation coefficient (R2 > 0.8) was obtained at the ripening period. The robustness of the established models was evaluated by comparisons between the estimated yields and in-situ measured yield data showed satisfactory results, with the root mean squared error (RMSE) smaller than 10%. Such results were reaffirmed by the correlation analysis between the estimated yields and government's rice yield statistics (R2 > 0.8). This study demonstrates advantages of using multi-temporal Radarsat-2 backscattering data for estimating rice crop yields in Taiwan prior to the harvesting period, and thus the methods were proposed for rice yield monitoring in other regions.

An experimental assessment of proposed universal yield curves for secondary electron emission

International Nuclear Information System (INIS)

Salehi, M.; Flinn, E.A.

1980-01-01

A variety of 'Universal Yield Curves' for the secondary emission process have been proposed. A series of precise measurements of the secondary emission properties of a range of related amorphous semiconducting materials, made under UHV on freshly vacuum-cleaved surfaces, and covering a wide range of primary energies, have recently made possible an accurate assessment of the validity of the various UYC's suggested. It is found that no truly universal curve exists; the atomic number of the target material plays an important part in determining the secondary emission properties. Agarwal's (Proc. Phys. Soc.; 71: 851 (1958)) semi-empirical expression, which takes account of the atomic number and weight, is found to give good agreement for all the materials studied. Further theoretical investigation is required. (author)

Performance of a procedure for yield estimation in fruit orchards

DEFF Research Database (Denmark)

Aravena Zamora, Felipe; Potin, Camila; Wulfsohn, Dvora-Laio

Early estimation of expected fruit tree yield is important for the market planning and for growers and exporters to plan for labour and boxes. Large variations in tree yield may be found, posing a challenge for accurate yield estimation. We evaluated a multilevel systematic sampling procedure...

Computing exact Fourier series coefficients of IC rectilinear polygons from low-resolution fast Fourier coefficients

Science.gov (United States)

Scheibler, Robin; Hurley, Paul

2012-03-01

We present a novel, accurate and fast algorithm to obtain Fourier series coefficients from an IC layer whose description consists of rectilinear polygons on a plane, and how to implement it using off-the-shelf hardware components. Based on properties of Fourier calculus, we derive a relationship between the Discrete Fourier Transforms of the sampled mask transmission function and its continuous Fourier series coefficients. The relationship leads to a straightforward algorithm for computing the continuous Fourier series coefficients where one samples the mask transmission function, compute its discrete Fourier transform and applies a frequency-dependent multiplicative factor. The algorithm is guaranteed to yield the exact continuous Fourier series coefficients for any sampling representing the mask function exactly. Computationally, this leads to significant saving by allowing to choose the maximal such pixel size and reducing the fast Fourier transform size by as much, without compromising accuracy. In addition, the continuous Fourier series is free from aliasing and follows closely the physical model of Fourier optics. We show that in some cases this can make a significant difference, especially in modern very low pitch technology nodes.

An accurate optical design method for synchrotron radiation beamlines with wave-front aberration theory

Energy Technology Data Exchange (ETDEWEB)

Yu, Xiaojiang, E-mail: slsyxj@nus.edu.sg; Diao, Caozheng; Breese, Mark B. H. [Singapore Synchrotron Light Source, National University of Singapore, Singapore 117603 (Singapore)

2016-07-27

An aberration calculation method which was developed by Lu [1] can treat individual aberration term precisely. Spectral aberration is the linear sum of these aberration terms, and the aberrations of multi-element systems also can be calculated correctly when the stretching ratio, defined herein, is unity. Evaluation of focusing mirror-grating systems which are optimized according to Lu’s method, along with the Light Path Function (LPF) and the Spot Diagram method (SD) are discussed to confirm the advantage of Lu’s methodology. Lu’s aberration terms are derived from a precise wave-front treatment, whereas the terms of the power series expansion of the light path function do not yield an accurate sum of the aberrations. Moreover, Lu’s aberration terms can be individually optimized. This is not possible with the analytical spot diagram formulae.

Accurate control testing for clay liner permeability

Energy Technology Data Exchange (ETDEWEB)

Mitchell, R J

1991-08-01

Two series of centrifuge tests were carried out to evaluate the use of centrifuge modelling as a method of accurate control testing of clay liner permeability. The first series used a large 3 m radius geotechnical centrifuge and the second series a small 0.5 m radius machine built specifically for research on clay liners. Two permeability cells were fabricated in order to provide direct data comparisons between the two methods of permeability testing. In both cases, the centrifuge method proved to be effective and efficient, and was found to be free of both the technical difficulties and leakage risks normally associated with laboratory permeability testing of fine grained soils. Two materials were tested, a consolidated kaolin clay having an average permeability coefficient of 1.2{times}10{sup -9} m/s and a compacted illite clay having a permeability coefficient of 2.0{times}10{sup -11} m/s. Four additional tests were carried out to demonstrate that the 0.5 m radius centrifuge could be used for linear performance modelling to evaluate factors such as volumetric water content, compaction method and density, leachate compatibility and other construction effects on liner leakage. The main advantages of centrifuge testing of clay liners are rapid and accurate evaluation of hydraulic properties and realistic stress modelling for performance evaluations. 8 refs., 12 figs., 7 tabs.

Real-time yield estimation based on deep learning

Science.gov (United States)

Rahnemoonfar, Maryam; Sheppard, Clay

2017-05-01

Crop yield estimation is an important task in product management and marketing. Accurate yield prediction helps farmers to make better decision on cultivation practices, plant disease prevention, and the size of harvest labor force. The current practice of yield estimation based on the manual counting of fruits is very time consuming and expensive process and it is not practical for big fields. Robotic systems including Unmanned Aerial Vehicles (UAV) and Unmanned Ground Vehicles (UGV), provide an efficient, cost-effective, flexible, and scalable solution for product management and yield prediction. Recently huge data has been gathered from agricultural field, however efficient analysis of those data is still a challenging task. Computer vision approaches currently face diffident challenges in automatic counting of fruits or flowers including occlusion caused by leaves, branches or other fruits, variance in natural illumination, and scale. In this paper a novel deep convolutional network algorithm was developed to facilitate the accurate yield prediction and automatic counting of fruits and vegetables on the images. Our method is robust to occlusion, shadow, uneven illumination and scale. Experimental results in comparison to the state-of-the art show the effectiveness of our algorithm.

Accurate anisotropic material modelling using only tensile tests for hot and cold forming

Science.gov (United States)

Abspoel, M.; Scholting, M. E.; Lansbergen, M.; Neelis, B. M.

2017-09-01

Accurate material data for simulations require a lot of effort. Advanced yield loci require many different kinds of tests and a Forming Limit Curve (FLC) needs a large amount of samples. Many people use simple material models to reduce the effort of testing, however some models are either not accurate enough (i.e. Hill’48), or do not describe new types of materials (i.e. Keeler). Advanced yield loci describe the anisotropic materials behaviour accurately, but are not widely adopted because of the specialized tests, and data post-processing is a hurdle for many. To overcome these issues, correlations between the advanced yield locus points (biaxial, plane strain and shear) and mechanical properties have been investigated. This resulted in accurate prediction of the advanced stress points using only Rm, Ag and r-values in three directions from which a Vegter yield locus can be constructed with low effort. FLC’s can be predicted with the equations of Abspoel & Scholting depending on total elongation A80, r-value and thickness. Both predictive methods are initially developed for steel, aluminium and stainless steel (BCC and FCC materials). The validity of the predicted Vegter yield locus is investigated with simulation and measurements on both hot and cold formed parts and compared with Hill’48. An adapted specimen geometry, to ensure a homogeneous temperature distribution in the Gleeble hot tensile test, was used to measure the mechanical properties needed to predict a hot Vegter yield locus. Since for hot material, testing of stress states other than uniaxial is really challenging, the prediction for the yield locus adds a lot of value. For the hot FLC an A80 sample with a homogeneous temperature distribution is needed which is due to size limitations not possible in the Gleeble tensile tester. Heating the sample in an industrial type furnace and tensile testing it in a dedicated device is a good alternative to determine the necessary parameters for the FLC

Accurate expansion of cylindrical paraxial waves for its straightforward implementation in electromagnetic scattering

Science.gov (United States)

Naserpour, Mahin; Zapata-Rodríguez, Carlos J.

2018-01-01

The evaluation of vector wave fields can be accurately performed by means of diffraction integrals, differential equations and also series expansions. In this paper, a Bessel series expansion which basis relies on the exact solution of the Helmholtz equation in cylindrical coordinates is theoretically developed for the straightforward yet accurate description of low-numerical-aperture focal waves. The validity of this approach is confirmed by explicit application to Gaussian beams and apertured focused fields in the paraxial regime. Finally we discuss how our procedure can be favorably implemented in scattering problems.

ZNJPrice/Earnings Ratio Model through Dividend Yield and Required Yield Above Expected Inflation

Directory of Open Access Journals (Sweden)

Emil Mihalina

2010-07-01

Full Text Available Price/earnings ratio is the most popular and most widespread evaluation model used to assess relative capital asset value on financial markets. In functional terms, company earnings in the very long term can be described with high significance. Empirically, it is visible from long-term statistics that the demanded (required yield on capital markets has certain regularity. Thus, investors first require a yield above the stable inflation rate and then a dividend yield and a capital increase caused by the growth of earnings that influence the price, with the assumption that the P/E ratio is stable. By combining the Gordon model for current dividend value, the model of market capitalization of earnings (price/earnings ratio and bearing in mind the influence of the general price levels on company earnings, it is possible to adjust the price/earnings ratio by deriving a function of the required yield on capital markets measured by a market index through dividend yield and inflation rate above the stable inflation rate increased by profit growth. The S&P 500 index for example, has in the last 100 years grown by exactly the inflation rate above the stable inflation rate increased by profit growth. The comparison of two series of price/earnings ratios, a modelled one and an average 7-year ratio, shows a notable correlation in the movement of two series of variables, with a three year deviation. Therefore, it could be hypothesized that three years of the expected inflation level, dividend yield and profit growth rate of the market index are discounted in the current market prices. The conclusion is that, at the present time, the relationship between the adjusted average price/earnings ratio and its effect on the market index on one hand and the modelled price/earnings ratio on the other can clearly show the expected dynamics and course in the following period.

Accurate determination of light elements by charged particle activation analysis

International Nuclear Information System (INIS)

Shikano, K.; Shigematsu, T.

1989-01-01

To develop accurate determination of light elements by CPAA, accurate and practical standardization methods and uniform chemical etching are studied based on determination of carbon in gallium arsenide using the 12 C(d,n) 13 N reaction and the following results are obtained: (1)Average stopping power method with thick target yield is useful as an accurate and practical standardization method. (2)Front surface of sample has to be etched for accurate estimate of incident energy. (3)CPAA is utilized for calibration of light element analysis by physical method. (4)Calibration factor of carbon analysis in gallium arsenide using the IR method is determined to be (9.2±0.3) x 10 15 cm -1 . (author)

Adjusting slash pine growth and yield for silvicultural treatments

Science.gov (United States)

Stephen R. Logan; Barry D. Shiver

2006-01-01

With intensive silvicultural treatments such as fertilization and competition control now commonplace in today's slash pine (Pinus elliottii Engelm.) plantations, a method to adjust current growth and yield models is required to accurately account for yield increases due to these practices. Some commonly used ad-hoc methods, such as raising site...

Determination of fission gas yields from isotope ratios

DEFF Research Database (Denmark)

Mogensen, Mogens Bjerg

1983-01-01

This paper describes a method of calculating the actual fission yield of Kr and Xe in nuclear fuel including the effect of neutron capture reactions and decay. The bases for this calculation are the cumulative yields (ref. 1) of Kr and Xe isotopes (or pairs of isotopes) which are unaffected...... by neutron capture reactions, and measured Kr and Xe isotope ratios. Also the burnup contribution from the different fissile heavy isotopes must be known in order to get accurate fission gas yields....

Accurate expansion of cylindrical paraxial waves for its straightforward implementation in electromagnetic scattering

International Nuclear Information System (INIS)

Naserpour, Mahin; Zapata-Rodríguez, Carlos J.

2018-01-01

Highlights: • Paraxial beams are represented in a series expansion in terms of Bessel wave functions. • The coefficients of the series expansion can be analytically determined by using the pattern in the focal plane. • In particular, Gaussian beams and apertured wave fields have been critically examined. • This representation of the wave field is adequate for scattering problems with shaped beams. - Abstract: The evaluation of vector wave fields can be accurately performed by means of diffraction integrals, differential equations and also series expansions. In this paper, a Bessel series expansion which basis relies on the exact solution of the Helmholtz equation in cylindrical coordinates is theoretically developed for the straightforward yet accurate description of low-numerical-aperture focal waves. The validity of this approach is confirmed by explicit application to Gaussian beams and apertured focused fields in the paraxial regime. Finally we discuss how our procedure can be favorably implemented in scattering problems.

MISSE 2 PEACE Polymers Experiment Atomic Oxygen Erosion Yield Error Analysis

Science.gov (United States)

McCarthy, Catherine E.; Banks, Bruce A.; deGroh, Kim, K.

2010-01-01

Atomic oxygen erosion of polymers in low Earth orbit (LEO) poses a serious threat to spacecraft performance and durability. To address this, 40 different polymer samples and a sample of pyrolytic graphite, collectively called the PEACE (Polymer Erosion and Contamination Experiment) Polymers, were exposed to the LEO space environment on the exterior of the International Space Station (ISS) for nearly 4 years as part of the Materials International Space Station Experiment 1 & 2 (MISSE 1 & 2). The purpose of the PEACE Polymers experiment was to obtain accurate mass loss measurements in space to combine with ground measurements in order to accurately calculate the atomic oxygen erosion yields of a wide variety of polymeric materials exposed to the LEO space environment for a long period of time. Error calculations were performed in order to determine the accuracy of the mass measurements and therefore of the erosion yield values. The standard deviation, or error, of each factor was incorporated into the fractional uncertainty of the erosion yield for each of three different situations, depending on the post-flight weighing procedure. The resulting error calculations showed the erosion yield values to be very accurate, with an average error of 3.30 percent.

Accurate determination of rates from non-uniformly sampled relaxation data

Energy Technology Data Exchange (ETDEWEB)

Stetz, Matthew A.; Wand, A. Joshua, E-mail: wand@upenn.edu [University of Pennsylvania Perelman School of Medicine, Johnson Research Foundation and Department of Biochemistry and Biophysics (United States)

2016-08-15

The application of non-uniform sampling (NUS) to relaxation experiments traditionally used to characterize the fast internal motion of proteins is quantitatively examined. Experimentally acquired Poisson-gap sampled data reconstructed with iterative soft thresholding are compared to regular sequentially sampled (RSS) data. Using ubiquitin as a model system, it is shown that 25 % sampling is sufficient for the determination of quantitatively accurate relaxation rates. When the sampling density is fixed at 25 %, the accuracy of rates is shown to increase sharply with the total number of sampled points until eventually converging near the inherent reproducibility of the experiment. Perhaps contrary to some expectations, it is found that accurate peak height reconstruction is not required for the determination of accurate rates. Instead, inaccuracies in rates arise from inconsistencies in reconstruction across the relaxation series that primarily manifest as a non-linearity in the recovered peak height. This indicates that the performance of an NUS relaxation experiment cannot be predicted from comparison of peak heights using a single RSS reference spectrum. The generality of these findings was assessed using three alternative reconstruction algorithms, eight different relaxation measurements, and three additional proteins that exhibit varying degrees of spectral complexity. From these data, it is revealed that non-linearity in peak height reconstruction across the relaxation series is strongly correlated with errors in NUS-derived relaxation rates. Importantly, it is shown that this correlation can be exploited to reliably predict the performance of an NUS-relaxation experiment by using three or more RSS reference planes from the relaxation series. The RSS reference time points can also serve to provide estimates of the uncertainty of the sampled intensity, which for a typical relaxation times series incurs no penalty in total acquisition time.

Yield surface evolution for columnar ice

Science.gov (United States)

Zhou, Zhiwei; Ma, Wei; Zhang, Shujuan; Mu, Yanhu; Zhao, Shunpin; Li, Guoyu

A series of triaxial compression tests, which has capable of measuring the volumetric strain of the sample, were conducted on columnar ice. A new testing approach of probing the experimental yield surface was performed from a single sample in order to investigate yield and hardening behaviors of the columnar ice under complex stress states. Based on the characteristic of the volumetric strain, a new method of defined the multiaxial yield strengths of the columnar ice is proposed. The experimental yield surface remains elliptical shape in the stress space of effective stress versus mean stress. The effect of temperature, loading rate and loading path in the initial yield surface and deformation properties of the columnar ice were also studied. Subsequent yield surfaces of the columnar ice have been explored by using uniaxial and hydrostatic paths. The evolution of the subsequent yield surface exhibits significant path-dependent characteristics. The multiaxial hardening law of the columnar ice was established experimentally. A phenomenological yield criterion was presented for multiaxial yield and hardening behaviors of the columnar ice. The comparisons between the theoretical and measured results indicate that this current model is capable of giving a reasonable prediction for the multiaxial yield and post-yield properties of the columnar ice subjected to different temperature, loading rate and path conditions.

Solutions of diffusion equations in two-dimensional cylindrical geometry by series expansions

International Nuclear Information System (INIS)

Ohtani, Nobuo

1976-01-01

A solution of the multi-group multi-regional diffusion equation in two-dimensional cylindrical (rho-z) geometry is obtained in the form of a regionwise double series composed of Bessel and trigonometrical functions. The diffusion equation is multiplied by weighting functions, which satisfy the homogeneous part of the diffusion equation, and the products are integrated over the region for obtaining the equations to determine the fluxes and their normal derivatives at the region boundaries. Multiplying the diffusion equation by each function of the set used for the flux expansion, then integrating the products, the coefficients of the double series of the flux inside each region are calculated using the boundary values obtained above. Since the convergence of the series thus obtained is slow especially near the region boundaries, a method for improving the convergence has been developed. The double series of the flux is separated into two parts. The normal derivative at the region boundary of the first part is zero, and that of the second part takes the value which is obtained in the first stage of this method. The second part is replaced by a continuous function, and the flux is represented by the sum of the continuous function and the double series. A sample critical problem of a two-group two-region system is numerically studied. The results show that the present method yields very accurately the flux integrals in each region with only a small number of expansion terms. (auth.)

Data-driven machine control : a feasibility study on YieldStar

NARCIS (Netherlands)

Mehrafrouz, M.

2014-01-01

Traditionally machine control software focusses on the control flow; this is also the situation within ASML and YieldStar. With the increased complexity of the machine control software more and more data is needed to accurately control a tool like YieldStar. In other software application areas, like

Variability in yield of faba beans (Vicia faba L.)

NARCIS (Netherlands)

Grashoff, C.

1992-01-01

Yield variability is one of the major problems in growing faba beans. In this thesis, the effect of water supply pattern on yield variability of the crop is studied with experiments in the field and under controlled conditions, and with a simulation model. In a series of field experiments,

Simple and Accurate Analytical Solutions of the Electrostatically Actuated Curled Beam Problem

KAUST Repository

Younis, Mohammad I.

2014-08-17

We present analytical solutions of the electrostatically actuated initially deformed cantilever beam problem. We use a continuous Euler-Bernoulli beam model combined with a single-mode Galerkin approximation. We derive simple analytical expressions for two commonly observed deformed beams configurations: the curled and tilted configurations. The derived analytical formulas are validated by comparing their results to experimental data in the literature and numerical results of a multi-mode reduced order model. The derived expressions do not involve any complicated integrals or complex terms and can be conveniently used by designers for quick, yet accurate, estimations. The formulas are found to yield accurate results for most commonly encountered microbeams of initial tip deflections of few microns. For largely deformed beams, we found that these formulas yield less accurate results due to the limitations of the single-mode approximations they are based on. In such cases, multi-mode reduced order models need to be utilized.

4-H Science Inquiry Video Series

Science.gov (United States)

Green, Jeremy W.; Black, Lynette; Willis, Patrick

2013-01-01

Studies support science inquiry as a positive method and approach for 4-H professionals and volunteers to use for teaching science-based practices to youth. The development of a science inquiry video series has yielded positive results as it relates to youth development education and science. The video series highlights how to conduct science-rich…

Review of current GPS methodologies for producing accurate time series and their error sources

Science.gov (United States)

He, Xiaoxing; Montillet, Jean-Philippe; Fernandes, Rui; Bos, Machiel; Yu, Kegen; Hua, Xianghong; Jiang, Weiping

2017-05-01

The Global Positioning System (GPS) is an important tool to observe and model geodynamic processes such as plate tectonics and post-glacial rebound. In the last three decades, GPS has seen tremendous advances in the precision of the measurements, which allow researchers to study geophysical signals through a careful analysis of daily time series of GPS receiver coordinates. However, the GPS observations contain errors and the time series can be described as the sum of a real signal and noise. The signal itself can again be divided into station displacements due to geophysical causes and to disturbing factors. Examples of the latter are errors in the realization and stability of the reference frame and corrections due to ionospheric and tropospheric delays and GPS satellite orbit errors. There is an increasing demand on detecting millimeter to sub-millimeter level ground displacement signals in order to further understand regional scale geodetic phenomena hence requiring further improvements in the sensitivity of the GPS solutions. This paper provides a review spanning over 25 years of advances in processing strategies, error mitigation methods and noise modeling for the processing and analysis of GPS daily position time series. The processing of the observations is described step-by-step and mainly with three different strategies in order to explain the weaknesses and strengths of the existing methodologies. In particular, we focus on the choice of the stochastic model in the GPS time series, which directly affects the estimation of the functional model including, for example, tectonic rates, seasonal signals and co-seismic offsets. Moreover, the geodetic community continues to develop computational methods to fully automatize all phases from analysis of GPS time series. This idea is greatly motivated by the large number of GPS receivers installed around the world for diverse applications ranging from surveying small deformations of civil engineering structures (e

Series expansion of the modified Einstein Procedure

Science.gov (United States)

Seema Chandrakant Shah-Fairbank

2009-01-01

This study examines calculating total sediment discharge based on the Modified Einstein Procedure (MEP). A new procedure based on the Series Expansion of the Modified Einstein Procedure (SEMEP) has been developed. This procedure contains four main modifications to MEP. First, SEMEP solves the Einstein integrals quickly and accurately based on a series expansion. Next,...

The Impact of Statistical Leakage Models on Design Yield Estimation

Directory of Open Access Journals (Sweden)

Rouwaida Kanj

2011-01-01

Full Text Available Device mismatch and process variation models play a key role in determining the functionality and yield of sub-100 nm design. Average characteristics are often of interest, such as the average leakage current or the average read delay. However, detecting rare functional fails is critical for memory design and designers often seek techniques that enable accurately modeling such events. Extremely leaky devices can inflict functionality fails. The plurality of leaky devices on a bitline increase the dimensionality of the yield estimation problem. Simplified models are possible by adopting approximations to the underlying sum of lognormals. The implications of such approximations on tail probabilities may in turn bias the yield estimate. We review different closed form approximations and compare against the CDF matching method, which is shown to be most effective method for accurate statistical leakage modeling.

Conditional time series forecasting with convolutional neural networks

NARCIS (Netherlands)

A. Borovykh (Anastasia); S.M. Bohte (Sander); C.W. Oosterlee (Cornelis)

2017-01-01

textabstractForecasting financial time series using past observations has been a significant topic of interest. While temporal relationships in the data exist, they are difficult to analyze and predict accurately due to the non-linear trends and noise present in the series. We propose to learn these

Imaging Spectroscopy for On-Farm Measurement of Grassland Yield and Quality

NARCIS (Netherlands)

Schut, A.G.T.; Heijden, van der G.W.A.M.; Hoving, I.E.; Stienezen, M.W.J.; Evert, van F.K.; Meuleman, J.

2006-01-01

Grassland management has a large influence on the operating cost and environmental impact of dairy farms and requires accurate, detailed, and timely information about the yield and quality of grass. Our objective was to evaluate imaging spectroscopy as a means to obtain accurate, detailed, and rapid

Comparative study of ultrasound and ERCP in the diagnosis of hepatic, biliary and pancreatic diseases: A prospective study based on a continuous series of 424 patients

International Nuclear Information System (INIS)

Frederic, N.; D'Hondt, M.; Hermanus, A.; Potvliege, R.; Deltenre, M.; Reuck, M. de

1983-01-01

A prospective study of the diagnostic yield of ultrasound (US) and ERCP was made on a continuous series of 424 patients. Technical failures were slightly more frequent with US (11%) than with ERCP (8%), while US proved more accurate than ERCP in the diagnosis of focal hepatic disease -94% of correct diagnoses versus 41% (n=17). In diffuse hepatic disease (n=63) the accuracy of both methods was the same -87% of correct diagnoses with US, 83% with ERCP. US had better performances (91%), while ERCP was more accurate in the diagnosis of common duct lithiasis or tumor (98% for ERCP, 36% for US). Although ERCP has a better diagnostic yield for pancreatic diseases (92% to 100% of correct diagnoses according to the lesions) associate complications, such as pseudo-cysts, abscess formation and extravasations are better demonstrated by US (95% of correct diagnoses versus 73%). The two methods thus prove to be complementary. (orig.)

Determination of internal series resistance of PV devices: repeatability and uncertainty

International Nuclear Information System (INIS)

Trentadue, Germana; Pavanello, Diego; Salis, Elena; Field, Mike; Müllejans, Harald

2016-01-01

The calibration of photovoltaic devices requires the measurement of their current–voltage characteristics at standard test conditions (STC). As the latter can only be reached approximately, a curve translation is necessary, requiring among others the internal series resistance of the photovoltaic device as an input parameter. Therefore accurate and reliable determination of the series resistance is important in measurement and test laboratories. This work follows standard IEC 60891 ed 2 (2009) for the determination of the internal series resistance and investigates repeatability and uncertainty of the result in three aspects for a number of typical photovoltaic technologies. Firstly the effect of varying device temperature on the determined series resistance is determined experimentally and compared to a theoretical derivation showing agreement. It is found that the series resistance can be determined with an uncertainty of better than 5% if the device temperature is stable within  ±0.1 °C, whereas the temperature range of  ±2 °C allowed by the standard leads to much larger variations. Secondly the repeatability of the series resistance determination with respect to noise in current–voltage measurement is examined yielding typical values of  ±5%. Thirdly the determination of the series resistance using three different experimental set-ups (solar simulators) shows agreement on the level of  ±5% for crystalline Silicon photovoltaic devices and deviations up to 15% for thin-film devices. It is concluded that the internal series resistance of photovoltaic devices could be determined with an uncertainty of better than 10%. The influence of this uncertainty in series resistance on the electrical performance parameters of photovoltaic devices was estimated and showed a contribution of 0.05% for open-circuit voltage and 0.1% for maximum power. Furthermore it is concluded that the range of device temperatures allowed during determination of series

Taylor's series method for solving the nonlinear point kinetics equations

International Nuclear Information System (INIS)

Nahla, Abdallah A.

2011-01-01

Highlights: → Taylor's series method for nonlinear point kinetics equations is applied. → The general order of derivatives are derived for this system. → Stability of Taylor's series method is studied. → Taylor's series method is A-stable for negative reactivity. → Taylor's series method is an accurate computational technique. - Abstract: Taylor's series method for solving the point reactor kinetics equations with multi-group of delayed neutrons in the presence of Newtonian temperature feedback reactivity is applied and programmed by FORTRAN. This system is the couples of the stiff nonlinear ordinary differential equations. This numerical method is based on the different order derivatives of the neutron density, the precursor concentrations of i-group of delayed neutrons and the reactivity. The r th order of derivatives are derived. The stability of Taylor's series method is discussed. Three sets of applications: step, ramp and temperature feedback reactivities are computed. Taylor's series method is an accurate computational technique and stable for negative step, negative ramp and temperature feedback reactivities. This method is useful than the traditional methods for solving the nonlinear point kinetics equations.

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

Science.gov (United States)

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.

Stock vs. Bond Yields, and Demographic Fluctuations

DEFF Research Database (Denmark)

Gozluklu, Arie; Morin, Annaïg

This paper analyzes the strong comovement between real stock and nominal bond yields at generational (low) frequencies. Life-cycle patterns in savings behavior in an overlapping generations model with cash-in-advance constraints explain this persistent comovement between financial yields. We argue...... that the slow-evolving time-series covariation due to changing population age structure accounts for the equilibrium relation between stock and bond markets. As a result, by exploiting the demographic information into distant future, the forecasting performance of evaluation models improves. Finally, using...

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

NARCIS (Netherlands)

Makowski, D.; Asseng, S.; Ewert, F.; Bassu, S.; Durand, J.L.; Martre, P.; Adam, M.; Aggarwal, P.K.; Angulo, C.; Baron, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Brisson, N.; Cammarano, D.; Challinor, A.J.; Conijn, J.G.; Corbeels, M.; Deryng, D.; Sanctis, De G.; Doltra, J.; Gayler, S.; Goldberg, R.; Grassini, P.; Hatfield, J.L.; Heng, L.; Hoek, S.B.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, C.; Jongschaap, R.E.E.; Jones, J.W.; Kemanian, R.A.; Kersebaum, K.C.; Kim, S.H.; Lizaso, J.; Müller, C.; Naresh Kumar, S.; Nendel, C.; O'Leary, G.J.; Olesen, J.E.; Osborne, T.M.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.; Rosenzweig, C.; Ruane, A.C.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Steduto, P.; Stöckle, C.O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Teixeira, E.; Thorburn, P.; Timlin, D.; Travasso, M.; Roetter, R.P.; Waha, K.; Wallach, D.; White, J.W.; Williams, J.R.; Wolf, J.

2015-01-01

Many simulation studies have been carried out to predict the effect of climate change on crop yield. Typically, in such study, one or several crop models are used to simulate series of crop yield values for different climate scenarios corresponding to different hypotheses of temperature, CO2

Home Circadian Phase Assessments with Measures of Compliance Yield Accurate Dim Light Melatonin Onsets.

Science.gov (United States)

Burgess, Helen J; Wyatt, James K; Park, Margaret; Fogg, Louis F

2015-06-01

There is a need for the accurate assessment of circadian phase outside of the clinic/laboratory, particularly with the gold standard dim light melatonin onset (DLMO). We tested a novel kit designed to assist in saliva sampling at home for later determination of the DLMO. The home kit includes objective measures of compliance to the requirements for dim light and half-hourly saliva sampling. Participants were randomized to one of two 10-day protocols. Each protocol consisted of two back-to-back home and laboratory phase assessments in counterbalanced order, separated by a 5-day break. Laboratory or participants' homes. Thirty-five healthy adults, age 21-62 y. N/A. Most participants received at least one 30-sec epoch of light > 50 lux during the home phase assessments (average light intensity 4.5 lux), but on average for light > 50 lux or sampling errors. There was no significant difference between the home and laboratory DLMOs (P > 0.05); on average the home DLMOs occurred 9.6 min before the laboratory DLMOs. The home DLMOs were highly correlated with the laboratory DLMOs (r = 0.91, P dim light melatonin onsets (DLMOs) demonstrates that including objective measures of light exposure and sample timing during home saliva sampling can lead to accurate home DLMOs. Circadian Phase Assessments at Home, http://clinicaltrials.gov/show/NCT01487252, NCT01487252. © 2015 Associated Professional Sleep Societies, LLC.

Robust and Accurate Anomaly Detection in ECG Artifacts Using Time Series Motif Discovery

Science.gov (United States)

Sivaraks, Haemwaan

2015-01-01

Electrocardiogram (ECG) anomaly detection is an important technique for detecting dissimilar heartbeats which helps identify abnormal ECGs before the diagnosis process. Currently available ECG anomaly detection methods, ranging from academic research to commercial ECG machines, still suffer from a high false alarm rate because these methods are not able to differentiate ECG artifacts from real ECG signal, especially, in ECG artifacts that are similar to ECG signals in terms of shape and/or frequency. The problem leads to high vigilance for physicians and misinterpretation risk for nonspecialists. Therefore, this work proposes a novel anomaly detection technique that is highly robust and accurate in the presence of ECG artifacts which can effectively reduce the false alarm rate. Expert knowledge from cardiologists and motif discovery technique is utilized in our design. In addition, every step of the algorithm conforms to the interpretation of cardiologists. Our method can be utilized to both single-lead ECGs and multilead ECGs. Our experiment results on real ECG datasets are interpreted and evaluated by cardiologists. Our proposed algorithm can mostly achieve 100% of accuracy on detection (AoD), sensitivity, specificity, and positive predictive value with 0% false alarm rate. The results demonstrate that our proposed method is highly accurate and robust to artifacts, compared with competitive anomaly detection methods. PMID:25688284

Determining the best phenological state for accurate mapping of Phragmites australis in wetlands using time series multispectral satellite data

Science.gov (United States)

Rupasinghe, P. A.; Markle, C. E.; Marcaccio, J. V.; Chow-Fraser, P.

2017-12-01

Phragmites australis (European common reed), is a relatively recent invader of wetlands and beaches in Ontario. It can establish large homogenous stands within wetlands and disperse widely throughout the landscape by wind and vehicular traffic. A first step in managing this invasive species includes accurate mapping and quantification of its distribution. This is challenging because Phragimtes is distributed in a large spatial extent, which makes the mapping more costly and time consuming. Here, we used freely available multispectral satellite images taken monthly (cloud free images as available) for the calendar year to determine the optimum phenological state of Phragmites that would allow it to be accurately identified using remote sensing data. We analyzed time series, Landsat-8 OLI and Sentinel-2 images for Big Creek Wildlife Area, ON using image classification (Support Vector Machines), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI). We used field sampling data and high resolution image collected using Unmanned Aerial Vehicle (UAV; 8 cm spatial resolution) as training data and for the validation of the classified images. The accuracy for all land cover classes and for Phragmites alone were low at both the start and end of the calendar year, but reached overall accuracy >85% by mid to late summer. The highest classification accuracies for Landsat-8 OLI were associated with late July and early August imagery. We observed similar trends using the Sentinel-2 images, with higher overall accuracy for all land cover classes and for Phragmites alone from late July to late September. During this period, we found the greatest difference between Phragmites and Typha, commonly confused classes, with respect to near-infrared and shortwave infrared reflectance. Therefore, the unique spectral signature of Phragmites can be attributed to both the level of greenness and factors related to water content in the leaves during late

Computational Error Estimate for the Power Series Solution of Odes ...

African Journals Online (AJOL)

This paper compares the error estimation of power series solution with recursive Tau method for solving ordinary differential equations. From the computational viewpoint, the power series using zeros of Chebyshevpolunomial is effective, accurate and easy to use. Keywords: Lanczos Tau method, Chebyshev polynomial, ...

Forecasting Long Memory Series Subject to Structural Change

DEFF Research Database (Denmark)

Dias, Gustavo Fruet; Papailias, Fotis

A two-stage forecasting approach for long memory time series is introduced. In the first step we estimate the fractional exponent and, applying the fractional differencing operator, we obtain the underlying weakly dependent series. In the second step, we perform the multi-step ahead forecasts...... for the weakly dependent series and obtain their long memory counterparts by applying the fractional cumulation operator. The methodology applies to stationary and nonstationary cases. Simulations and an application to seven time series provide evidence that the new methodology is more robust to structural...... change and yields good forecasting results....

Atomic Oxygen Erosion Yield Prediction for Spacecraft Polymers in Low Earth Orbit

Science.gov (United States)

Banks, Bruce A.; Backus, Jane A.; Manno, Michael V.; Waters, Deborah L.; Cameron, Kevin C.; deGroh, Kim K.

2009-01-01

The ability to predict the atomic oxygen erosion yield of polymers based on their chemistry and physical properties has been only partially successful because of a lack of reliable low Earth orbit (LEO) erosion yield data. Unfortunately, many of the early experiments did not utilize dehydrated mass loss measurements for erosion yield determination, and the resulting mass loss due to atomic oxygen exposure may have been compromised because samples were often not in consistent states of dehydration during the pre-flight and post-flight mass measurements. This is a particular problem for short duration mission exposures or low erosion yield materials. However, as a result of the retrieval of the Polymer Erosion and Contamination Experiment (PEACE) flown as part of the Materials International Space Station Experiment 2 (MISSE 2), the erosion yields of 38 polymers and pyrolytic graphite were accurately measured. The experiment was exposed to the LEO environment for 3.95 years from August 16, 2001 to July 30, 2005 and was successfully retrieved during a space walk on July 30, 2005 during Discovery s STS-114 Return to Flight mission. The 40 different materials tested (including Kapton H fluence witness samples) were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The MISSE 2 PEACE Polymers experiment used carefully dehydrated mass measurements, as well as accurate density measurements to obtain accurate erosion yield data for high-fluence (8.43 1021 atoms/sq cm). The resulting data was used to develop an erosion yield predictive tool with a correlation coefficient of 0.895 and uncertainty of +/-6.3 10(exp -25)cu cm/atom. The predictive tool utilizes the chemical structures and physical properties of polymers to predict in-space atomic oxygen erosion yields. A predictive tool concept (September 2009 version) is presented which represents an improvement over an earlier (December 2008) version.

Microscopic predictions of fission yields based on the time dependent GCM formalism

International Nuclear Information System (INIS)

Regnier, D.; Dubray, N.; Verriere, M.; Schunck, N.

2016-01-01

Accurate knowledge of fission fragment yields is an essential ingredient of numerous applications ranging from the formation of elements in the r-process to fuel cycle optimization in nuclear energy. The need for a predictive theory applicable where no data is available, together with the variety of potential applications, is an incentive to develop a fully microscopic approach to fission dynamics. One of the most promising theoretical frameworks is the time-dependent generator coordinate method (TDGCM) applied under the Gaussian overlap approximation (GOA). Previous studies reported promising results by numerically solving the TDGCM+GOA equation with a finite difference technique. However, the computational cost of this method makes it difficult to properly control numerical errors. In addition, it prevents one from performing calculations with more than two collective variables. To overcome these limitations, we have developed the new code FELIX-1.0 that solves the TDGCM+GOA equation based on the Galerkin finite element method. In this article, we briefly illustrate the capabilities of the solver FELIX-1.0, in particular its validation for n+ 239 Pu low energy induced fission. FELIX-1.0 gives full control on the numerical precision of fission product yields in neutron-induced fission, and its scalability also enables series of dynamical calculations on several potential energy surfaces. Preliminary results suggest an important sensitivity of our two-dimensional approach to the input potential energy surface

Can Measured Synergy Excitations Accurately Construct Unmeasured Muscle Excitations?

Science.gov (United States)

Bianco, Nicholas A; Patten, Carolynn; Fregly, Benjamin J

2018-01-01

Accurate prediction of muscle and joint contact forces during human movement could improve treatment planning for disorders such as osteoarthritis, stroke, Parkinson's disease, and cerebral palsy. Recent studies suggest that muscle synergies, a low-dimensional representation of a large set of muscle electromyographic (EMG) signals (henceforth called "muscle excitations"), may reduce the redundancy of muscle excitation solutions predicted by optimization methods. This study explores the feasibility of using muscle synergy information extracted from eight muscle EMG signals (henceforth called "included" muscle excitations) to accurately construct muscle excitations from up to 16 additional EMG signals (henceforth called "excluded" muscle excitations). Using treadmill walking data collected at multiple speeds from two subjects (one healthy, one poststroke), we performed muscle synergy analysis on all possible subsets of eight included muscle excitations and evaluated how well the calculated time-varying synergy excitations could construct the remaining excluded muscle excitations (henceforth called "synergy extrapolation"). We found that some, but not all, eight-muscle subsets yielded synergy excitations that achieved >90% extrapolation variance accounted for (VAF). Using the top 10% of subsets, we developed muscle selection heuristics to identify included muscle combinations whose synergy excitations achieved high extrapolation accuracy. For 3, 4, and 5 synergies, these heuristics yielded extrapolation VAF values approximately 5% lower than corresponding reconstruction VAF values for each associated eight-muscle subset. These results suggest that synergy excitations obtained from experimentally measured muscle excitations can accurately construct unmeasured muscle excitations, which could help limit muscle excitations predicted by muscle force optimizations.

Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

Directory of Open Access Journals (Sweden)

Oscar Rojas

2013-04-01

Full Text Available Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regional scales. Several qualitative and quantitative approaches can be clearly distinguished, going from the use of low resolution satellite imagery as the main predictor of final crop yield to complex crop growth models where remote sensing-derived indicators play different roles, depending on the nature of the model and on the availability of data measured on the ground. Vegetation performance anomaly detection with low resolution images continues to be a fundamental component of early warning and drought monitoring systems at the regional scale. For applications at more detailed scales, the limitations created by the mixed nature of low resolution pixels are being progressively reduced by the higher resolution offered by new sensors, while the continuity of existing systems remains crucial for ensuring the availability of long time series as needed by the majority of the yield prediction methods used today.

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

Science.gov (United States)

Skakun, Sergii; Vermote, Eric; Roger, Jean-Claude; Franch, Belen

2017-01-01

Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of an image every 3-5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10-30 m). This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI) from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

Combined Use of Landsat-8 and Sentinel-2A Images for Winter Crop Mapping and Winter Wheat Yield Assessment at Regional Scale

Directory of Open Access Journals (Sweden)

Sergii Skakun

2017-05-01

Full Text Available Timely and accurate information on crop yield and production is critical to many applications within agriculture monitoring. Thanks to its coverage and temporal resolution, coarse spatial resolution satellite imagery has always been a source of valuable information for yield forecasting and assessment at national and regional scales. With availability of free images acquired by Landsat-8 and Sentinel-2 remote sensing satellites, it becomes possible to provide temporal resolution of 3–5 days, and therefore, to develop next generation agriculture products at higher spatial resolution (10–30 m. This paper explores the combined use of Landsat-8 and Sentinel-2A for winter crop mapping and winter wheat yield assessment at regional scale. For the former, we adapt a previously developed approach for the Moderate Resolution Imaging Spectroradiometer (MODIS instrument at 250 m resolution that allows automatic mapping of winter crops taking into account a priori knowledge on crop calendar. For the latter, we use a generalized winter wheat yield forecasting model that is based on estimation of the peak Normalized Difference Vegetation Index (NDVI from MODIS image time-series, and further downscaled to be applicable at 30 m resolution. We show that integration of Landsat-8 and Sentinel-2A improves both winter crop mapping and winter wheat yield assessment. In particular, the error of winter wheat yield estimates can be reduced up to 1.8 times compared to using a single satellite.

Accurate argon cluster-ion sputter yields: Measured yields and effect of the sputter threshold in practical depth-profiling by x-ray photoelectron spectroscopy and secondary ion mass spectrometry

Energy Technology Data Exchange (ETDEWEB)

Cumpson, Peter J.; Portoles, Jose F.; Barlow, Anders J.; Sano, Naoko [National EPSRC XPS User' s Service (NEXUS), School of Mechanical and Systems Engineering, Newcastle University, Newcastle upon Tyne, NE1 7RU (United Kingdom)

2013-09-28

Argon Gas Cluster-Ion Beam sources are likely to become widely used on x-ray photoelectron spectroscopy and secondary ion mass spectrometry instruments in the next few years. At typical energies used for sputter depth profiling the average argon atom in the cluster has a kinetic energy comparable with the sputter threshold, meaning that for the first time in practical surface analysis a quantitative model of sputter yields near threshold is needed. We develop a simple equation based on a very simple model. Though greatly simplified it is likely to have realistic limiting behaviour and can be made useful for estimating sputter yields by fitting its three parameters to experimental data. We measure argon cluster-ion sputter yield using a quartz crystal microbalance close to the sputter threshold, for silicon dioxide, poly(methyl methacrylate), and polystyrene and (along with data for gold from the existing literature) perform least-squares fits of our new sputter yield equation to this data. The equation performs well, with smaller residuals than for earlier empirical models, but more importantly it is very easy to use in the design and quantification of sputter depth-profiling experiments.

On clustering fMRI time series

DEFF Research Database (Denmark)

Goutte, Cyril; Toft, Peter Aundal; Rostrup, E.

1999-01-01

Analysis of fMRI time series is often performed by extracting one or more parameters for the individual voxels. Methods based, e.g., on various statistical tests are then used to yield parameters corresponding to probability of activation or activation strength. However, these methods do...

Primary yield and multitranche structure in securitization issues: Explicative factors. A review

Directory of Open Access Journals (Sweden)

Miguel Á. Peña-Cerezo

2016-09-01

Full Text Available The reasons for the strong rise in the securitization phenomenon up until the start of the “subprime crisis” need to be analysed. According to many authors, they mainly stem from its offering the possibility of generating fixed yield securities with the highest rating and a low risk premium, thanks to the issues being structured in differentiated bond series, so that certain series absorb most of the risk, thus facilitating the safer or “senior” tranches having a higher rating. Accordingly, this paper reviews the literature on the factors underlying the generation of differentiated tranches in this type of issues and regarding the determining factors of the yield offered by securitization issues. It concludes that the search for more complete markets, along with the reducing of problems associated to the moral hazard, are the main reasons for the multi-tranche structuring. And given the strong influence of the number of tranches on the yield offered by the issues, the paper likewise concludes that the multitranche structures has been an efficient tool to place securitization issues with more competitive yields.

Crop Yield Predictions - High Resolution Statistical Model for Intra-season Forecasts Applied to Corn in the US

Science.gov (United States)

Cai, Y.

2017-12-01

Accurately forecasting crop yields has broad implications for economic trading, food production monitoring, and global food security. However, the variation of environmental variables presents challenges to model yields accurately, especially when the lack of highly accurate measurements creates difficulties in creating models that can succeed across space and time. In 2016, we developed a sequence of machine-learning based models forecasting end-of-season corn yields for the US at both the county and national levels. We combined machine learning algorithms in a hierarchical way, and used an understanding of physiological processes in temporal feature selection, to achieve high precision in our intra-season forecasts, including in very anomalous seasons. During the live run, we predicted the national corn yield within 1.40% of the final USDA number as early as August. In the backtesting of the 2000-2015 period, our model predicts national yield within 2.69% of the actual yield on average already by mid-August. At the county level, our model predicts 77% of the variation in final yield using data through the beginning of August and improves to 80% by the beginning of October, with the percentage of counties predicted within 10% of the average yield increasing from 68% to 73%. Further, the lowest errors are in the most significant producing regions, resulting in very high precision national-level forecasts. In addition, we identify the changes of important variables throughout the season, specifically early-season land surface temperature, and mid-season land surface temperature and vegetation index. For the 2017 season, we feed 2016 data to the training set, together with additional geospatial data sources, aiming to make the current model even more precise. We will show how our 2017 US corn yield forecasts converges in time, which factors affect the yield the most, as well as present our plans for 2018 model adjustments.

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

Science.gov (United States)

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

Satellite-based assessment of grassland yields

Science.gov (United States)

Grant, K.; Siegmund, R.; Wagner, M.; Hartmann, S.

2015-04-01

Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available, cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.

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

Science.gov (United States)

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...

A globally accurate theory for a class of binary mixture models

Science.gov (United States)

Dickman, Adriana G.; Stell, G.

The self-consistent Ornstein-Zernike approximation results for the 3D Ising model are used to obtain phase diagrams for binary mixtures described by decorated models, yielding the plait point, binodals, and closed-loop coexistence curves for the models proposed by Widom, Clark, Neece, and Wheeler. The results are in good agreement with series expansions and experiments.

Absolute measurement of the DT primary neutron yield on the National Ignition Facility

Directory of Open Access Journals (Sweden)

Leeper R.J.

2013-11-01

Full Text Available The measurement of the absolute neutron yield produced in inertial confinement fusion target experiments conducted on the National Ignition Facility (NIF is essential in benchmarking progress towards the goal of achieving ignition on this facility. This paper describes three independent diagnostic techniques that have been developed to make accurate and precise DT neutron yield measurements on the NIF.

Gridding artifacts on ENVISAT/MERIS temporal series

NARCIS (Netherlands)

Gómez Chova, L.; Zurita-Milla, R.; Alonso, L.; Guanter, L.; Amoros-Lopez, J.; Camps-Valls, G.; Moreno, J.; Lacoste-Francis, H.

2010-01-01

Earth observation satellites are a valuable source of data that can be used to better understand the Earth system dynamics. However, analysis of satellite image time series requires an accurate spatial co-registration so that the multi-temporal pixel entities offer a true temporal view of the study

MÉTODOS DISCRETOS Y CONTINUOS PARA MODELAR LA DENSIDAD DE PROBABILIDAD DE LA VOLATILIDAD ESTOCÁSTICA DE LOS RENDIMIENTOS DE SERIES FINANCIERAS DISCRETE AND CONTINUOUS METHODS FOR MODELING FINANCIAL SERIES YIELDING STOCHASTIC VOLATILITY PROBABILITY DENSITY

Directory of Open Access Journals (Sweden)

Carlos Alexánder Grajales Correa

2007-07-01

Full Text Available En este trabajo se consideran los rendimientos diarios de un activo financiero con el propósito de modelar y comparar la densidad de probabilidad de la volatilidad estocástica de los retornos. Para tal fin, se proponen los modelos ARCH y sus extensiones, que son en tiempo discreto, así como un modelo empírico de volatilidad estocástica, desarrollado por Paul Wilmott. Para el caso discreto se muestran los modelos que permiten estimar la volatilidad condicional heterocedástica en un instante t del tiempo, t∈[1,T]. En el caso continuo se asocia un proceso de difusión de Itô a la volatilidad estocástica de la serie financiera, lo cual posibilita discretizar dicho proceso y simularlo para obtener densidades de probabilidad empíricas de la volatilidad. Finalmente se ilustran y se comparan los resultados obtenidos con las metodologías expuestas para el caso de las series financieras S&P 500 de EEUU, el Índice de Precios y Cotizaciones de la Bolsa Mexicana de Valores (IPC y el IGBC de Colombia.This work considers daily yields of financial assets in order to model and compare returns stochastic volatility probability density. For such aim, ARCH models and its extensions are proposed - they are in discrete time- as well as an Empirical Stochastic Volatility Model, developed by Paul Wilmott. For the discrete case, models that allow to estimate heteroscedasticity conditional volatility in a time, t, t,t∈[1,T], are shown. In the continuous case, there is an association of an Itô diffusion process to stochastic volatility of the financial series, which allows to write a discretization of this process and to simulate it to obtain empirical probabilistic densities from the volatility. Finally the results are illustrated and compared with methodologies exposed by the case of the financial series S&P 500 of the U.S.A., Index of Prices and Quotations of stock-market Mexican of Values (IPC and IGBC of Colombia.

Scale-dependent intrinsic entropies of complex time series.

Science.gov (United States)

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

An Algorithm for the Convolution of Legendre Series

KAUST Repository

Hale, Nicholas; Townsend, Alex

2014-01-01

An O(N2) algorithm for the convolution of compactly supported Legendre series is described. The algorithm is derived from the convolution theorem for Legendre polynomials and the recurrence relation satisfied by spherical Bessel functions. Combining with previous work yields an O(N 2) algorithm for the convolution of Chebyshev series. Numerical results are presented to demonstrate the improved efficiency over the existing algorithm. © 2014 Society for Industrial and Applied Mathematics.

Explosive Yield Estimation using Fourier Amplitude Spectra of Velocity Histories

Science.gov (United States)

Steedman, D. W.; Bradley, C. R.

2016-12-01

The Source Physics Experiment (SPE) is a series of explosive shots of various size detonated at varying depths in a borehole in jointed granite. The testbed includes an extensive array of accelerometers for measuring the shock environment close-in to the explosive source. One goal of SPE is to develop greater understanding of the explosion phenomenology in all regimes: from near-source, non-linear response to the far-field linear elastic region, and connecting the analyses from the respective regimes. For example, near-field analysis typically involves review of kinematic response (i.e., acceleration, velocity and displacement) in the time domain and looks at various indicators (e.g., peaks, pulse duration) to facilitate comparison among events. Review of far-field data more often is based on study of response in the frequency domain to facilitate comparison of event magnitudes. To try to "bridge the gap" between approaches, we have developed a scaling law for Fourier amplitude spectra of near-field velocity histories that successfully collapses data from a wide range of yields (100 kg to 5000 kg) and range to sensors in jointed granite. Moreover, we show that we can apply this scaling law to data from a new event to accurately estimate the explosive yield of that event. This approach presents a new way of working with near-field data that will be more compatible with traditional methods of analysis of seismic data and should serve to facilitate end-to-end event analysis. The goal is that this new approach to data analysis will eventually result in improved methods for discrimination of event type (i.e., nuclear or chemical explosion, or earthquake) and magnitude.

Accurate Synthesis of Polybrominated Diphenyl Ethers%精确合成多溴代二苯醚类化合物

Institute of Scientific and Technical Information of China (English)

沈宏; 崔凯

2017-01-01

用间氯过氧苯甲酸和三氟甲磺酸作为酸性氧化体系,以多种溴代碘苯及溴代苯合成了溴代二苯基碘盐.再以其与溴代苯酚在碱性条件下反应,精确合成各种多溴代二苯醚.该方法简便、反应条件温和、后处理简单、产品纯度好、收率高.%A series of polybrominated diphenyliodonium trifluoromethanesulfonic salt were synthesized from brominated iodobenzene and brominated benzene catalyzed by m-chloroperoxybenzoic acid and trifluoromethanesulfonic acid.Then corresponding polybrominateddiphenyl ethers were accurately synthesized with them and brominated phenol in alkaline condition.The advantages of the procedure is mild reaction condition,easy operation,simple after-treatment,high yield and purity of products.

Predictive ability of machine learning methods for massive crop yield prediction

Directory of Open Access Journals (Sweden)

Alberto Gonzalez-Sanchez

2014-04-01

Full Text Available An important issue for agricultural planning purposes is the accurate yield estimation for the numerous crops involved in the planning. Machine learning (ML is an essential approach for achieving practical and effective solutions for this problem. Many comparisons of ML methods for yield prediction have been made, seeking for the most accurate technique. Generally, the number of evaluated crops and techniques is too low and does not provide enough information for agricultural planning purposes. This paper compares the predictive accuracy of ML and linear regression techniques for crop yield prediction in ten crop datasets. Multiple linear regression, M5-Prime regression trees, perceptron multilayer neural networks, support vector regression and k-nearest neighbor methods were ranked. Four accuracy metrics were used to validate the models: the root mean square error (RMS, root relative square error (RRSE, normalized mean absolute error (MAE, and correlation factor (R. Real data of an irrigation zone of Mexico were used for building the models. Models were tested with samples of two consecutive years. The results show that M5-Prime and k-nearest neighbor techniques obtain the lowest average RMSE errors (5.14 and 4.91, the lowest RRSE errors (79.46% and 79.78%, the lowest average MAE errors (18.12% and 19.42%, and the highest average correlation factors (0.41 and 0.42. Since M5-Prime achieves the largest number of crop yield models with the lowest errors, it is a very suitable tool for massive crop yield prediction in agricultural planning.

Accurate shear measurement with faint sources

International Nuclear Information System (INIS)

Zhang, Jun; Foucaud, Sebastien; Luo, Wentao

2015-01-01

For cosmic shear to become an accurate cosmological probe, systematic errors in the shear measurement method must be unambiguously identified and corrected for. Previous work of this series has demonstrated that cosmic shears can be measured accurately in Fourier space in the presence of background noise and finite pixel size, without assumptions on the morphologies of galaxy and PSF. The remaining major source of error is source Poisson noise, due to the finiteness of source photon number. This problem is particularly important for faint galaxies in space-based weak lensing measurements, and for ground-based images of short exposure times. In this work, we propose a simple and rigorous way of removing the shear bias from the source Poisson noise. Our noise treatment can be generalized for images made of multiple exposures through MultiDrizzle. This is demonstrated with the SDSS and COSMOS/ACS data. With a large ensemble of mock galaxy images of unrestricted morphologies, we show that our shear measurement method can achieve sub-percent level accuracy even for images of signal-to-noise ratio less than 5 in general, making it the most promising technique for cosmic shear measurement in the ongoing and upcoming large scale galaxy surveys

Accurate Quantitative Sensing of Intracellular pH based on Self-ratiometric Upconversion Luminescent Nanoprobe

NARCIS (Netherlands)

Li, C.; Zuo, J.; Zhang, L.; Chang, Y.; Zhang, Y.; Tu, L.; Liu, X.; Xue, B.; Li, Q.; Zhao, H.; Zhang, H.; Kong, X.

2016-01-01

Accurate quantitation of intracellular pH (pHi) is of great importance in revealing the cellular activities and early warning of diseases. A series of fluorescence-based nano-bioprobes composed of different nanoparticles or/and dye pairs have already been developed for pHi sensing. Till now,

High Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration

Science.gov (United States)

Scott, James R.; Martini, Michael C.

2008-01-01

Taylor series integration is implemented in a spacecraft trajectory analysis code-the Spacecraft N-body Analysis Program (SNAP) - and compared with the code s existing eighth-order Runge-Kutta Fehlberg time integration scheme. Nine trajectory problems, including near Earth, lunar, Mars and Europa missions, are analyzed. Head-to-head comparison at five different error tolerances shows that, on average, Taylor series is faster than Runge-Kutta Fehlberg by a factor of 15.8. Results further show that Taylor series has superior convergence properties. Taylor series integration proves that it can provide rapid, highly accurate solutions to spacecraft trajectory problems.

Yield and competition in barley variety mixtures

Directory of Open Access Journals (Sweden)

Kari Jokinen

1991-09-01

Full Text Available Competition between spring barley varieties and yield performance of two-, three and four-variety mixtures were studied in two replacement series field experiments. In the first experiment, repeated in three successive years (1983 —85 the components were the six-row varieties Agneta, Arra, Hja-673 and Porno. In the second experiment (1984, including two nitrogen doses (50 and 100 kgN/ha, both six-row (Agneta, Pomo and two-row (Ida, Kustaa varieties were used. Arra in the first and Agneta in the second experiment were the most competitive varieties. The results suggested that the fast growth of Arra at the beginning promoted its competitive ability. Increase in available nitrogen usually strengthened the competitiveness of Agneta. The observed competitive differences between varieties were not related to the earliness of a variety, neither to the morphological characters (two- and six-row varieties nor to the grain yield of a variety grown alone. The competitive ability was not always a stable character, the dominant suppression relationship varying from one environment to another (e.g. growing season, nitrogen dose. The observed overyielding was not statistically significant. The ratio of actual to expected yield and the relative yield total of several mixtures exceeded slightly one. As a conclusion, the yield advantage of mixtures was marginal. As a rule, the mixtures were not more stable than monocultures as determined by the coefficient of variation. However, the yield of some mixtures varied less than the yield of the most stable monoculture.

Automated Feature Design for Time Series Classification by Genetic Programming

OpenAIRE

Harvey, Dustin Yewell

2014-01-01

Time series classification (TSC) methods discover and exploit patterns in time series and other one-dimensional signals. Although many accurate, robust classifiers exist for multivariate feature sets, general approaches are needed to extend machine learning techniques to make use of signal inputs. Numerous applications of TSC can be found in structural engineering, especially in the areas of structural health monitoring and non-destructive evaluation. Additionally, the fields of process contr...

Quality metric for accurate overlay control in <20nm nodes

Science.gov (United States)

Klein, Dana; Amit, Eran; Cohen, Guy; Amir, Nuriel; Har-Zvi, Michael; Huang, Chin-Chou Kevin; Karur-Shanmugam, Ramkumar; Pierson, Bill; Kato, Cindy; Kurita, Hiroyuki

2013-04-01

The semiconductor industry is moving toward 20nm nodes and below. As the Overlay (OVL) budget is getting tighter at these advanced nodes, the importance in the accuracy in each nanometer of OVL error is critical. When process owners select OVL targets and methods for their process, they must do it wisely; otherwise the reported OVL could be inaccurate, resulting in yield loss. The same problem can occur when the target sampling map is chosen incorrectly, consisting of asymmetric targets that will cause biased correctable terms and a corrupted wafer. Total measurement uncertainty (TMU) is the main parameter that process owners use when choosing an OVL target per layer. Going towards the 20nm nodes and below, TMU will not be enough for accurate OVL control. KLA-Tencor has introduced a quality score named `Qmerit' for its imaging based OVL (IBO) targets, which is obtained on the-fly for each OVL measurement point in X & Y. This Qmerit score will enable the process owners to select compatible targets which provide accurate OVL values for their process and thereby improve their yield. Together with K-T Analyzer's ability to detect the symmetric targets across the wafer and within the field, the Archer tools will continue to provide an independent, reliable measurement of OVL error into the next advanced nodes, enabling fabs to manufacture devices that meet their tight OVL error budgets.

A global water supply reservoir yield model with uncertainty analysis

International Nuclear Information System (INIS)

Kuria, Faith W; Vogel, Richard M

2014-01-01

Understanding the reliability and uncertainty associated with water supply yields derived from surface water reservoirs is central for planning purposes. Using a global dataset of monthly river discharge, we introduce a generalized model for estimating the mean and variance of water supply yield, Y, expected from a reservoir for a prespecified reliability, R, and storage capacity, S assuming a flow record of length n. The generalized storage–reliability–yield (SRY) relationships reported here have numerous water resource applications ranging from preliminary water supply investigations, to economic and climate change impact assessments. An example indicates how our generalized SRY relationship can be combined with a hydroclimatic model to determine the impact of climate change on surface reservoir water supply yields. We also document that the variability of estimates of water supply yield are invariant to characteristics of the reservoir system, including its storage capacity and reliability. Standardized metrics of the variability of water supply yields are shown to depend only on the sample size of the inflows and the statistical characteristics of the inflow series. (paper)

Enriched Meshfree Method for an Accurate Numerical Solution of the Motz Problem

Directory of Open Access Journals (Sweden)

Won-Tak Hong

2016-01-01

Full Text Available We present an enriched meshfree solution of the Motz problem. The Motz problem has been known as a benchmark problem to verify the efficiency of numerical methods in the presence of a jump boundary data singularity at a point, where an abrupt change occurs for the boundary condition. We propose a singular basis function enrichment technique in the context of partition of unity based meshfree method. We take the leading terms of the local series expansion at the point singularity and use them as enrichment functions for the local approximation space. As a result, we obtain highly accurate leading coefficients of the Motz problem that are comparable to the most accurate numerical solution. The proposed singular enrichment technique is highly effective in the case of the local series expansion of the solution being known. The enrichment technique that is used in this study can be applied to monotone singularities (of type rα with α<1 as well as oscillating singularities (of type rαsin⁡(ϵlog⁡r. It is the first attempt to apply singular meshfree enrichment technique to the Motz problem.

Automatic yield-line analysis of slabs using discontinuity layout optimization.

Science.gov (United States)

Gilbert, Matthew; He, Linwei; Smith, Colin C; Le, Canh V

2014-08-08

The yield-line method of analysis is a long established and extremely effective means of estimating the maximum load sustainable by a slab or plate. However, although numerous attempts to automate the process of directly identifying the critical pattern of yield-lines have been made over the past few decades, to date none has proved capable of reliably analysing slabs of arbitrary geometry. Here, it is demonstrated that the discontinuity layout optimization (DLO) procedure can successfully be applied to such problems. The procedure involves discretization of the problem using nodes inter-connected by potential yield-line discontinuities, with the critical layout of these then identified using linear programming. The procedure is applied to various benchmark problems, demonstrating that highly accurate solutions can be obtained, and showing that DLO provides a truly systematic means of directly and reliably automatically identifying yield-line patterns. Finally, since the critical yield-line patterns for many problems are found to be quite complex in form, a means of automatically simplifying these is presented.

Comparison of (alpha, n) thick-target neutron yields and spectra from ORIGEN-S and SOURCES

International Nuclear Information System (INIS)

Brown, T.H.; Wilson, W.B.; Perry, R.T.; Charlton, W.S.

1998-01-01

Both ORIGEN-S and SOURCES generate thick-target neutron yields and energy spectra from (α,n) reactions in homogeneous materials. SOURCES calculates yield and spectra for any material containing α-emitting and (α,n) target elements by simulating reaction physics, using α-emission energy spectra, elemental stopping cross sections, (α,n) cross sections for target nuclei, and branching fractions to produce-nuclide energy levels. This methodology results in accurate yield and spectra. ORIGEN-S has two options for calculating yields and spectra. The UO 2 option (default) estimates yields and spectra assuming the input α-emitters to be infinitely dilute in UO 2 . The borosilicate-glass option estimates yields from the total input material composition and generates spectra purportedly representative of spectra generated by 238 Pu, 241 Am, 242 Cm, and 244 Cm infinitely dilute in borosilicate glass, even if none of these four α-emitters are present in the input material composition. Because yields from the borosilicate-glass option in ORIGEN-S are based on entire input material composition and are reasonably accurate, the same is often assumed to be true for spectra. The input/output functionality of the borosilicate-glass option, along with ambiguity in ORIGEN-S documentation, gives the incorrect impression that spectra representative of input compositions are generated. This impression is reinforced by wide usage of the SCALE code system and its ORIGEN-S module and their sponsorship by the US Nuclear Regulatory Commission

PARAMETRIZATION OF INNER STRUCTURE OF AGRICULTURAL SYSTEMS ON THE BASIS OF MAXIMAL YIELDS ISOLINES (ISOCARPS

Directory of Open Access Journals (Sweden)

K KUDRNA

2004-07-01

Full Text Available On the basis of analysis of yield time series from a ten-year period, isolines of maximal yields of crops (isocarps have been constructed, homogenized yield zones have been determined, and inner structures of the agricultural system have been calculated. The algorithm of a normal and an optimal structure calculation have been used, and differences in the structure of the agricultural system have been determined for every defi ned zone.

Neural network versus classical time series forecasting models

Science.gov (United States)

Nor, Maria Elena; Safuan, Hamizah Mohd; Shab, Noorzehan Fazahiyah Md; Asrul, Mohd; Abdullah, Affendi; Mohamad, Nurul Asmaa Izzati; Lee, Muhammad Hisyam

2017-05-01

Artificial neural network (ANN) has advantage in time series forecasting as it has potential to solve complex forecasting problems. This is because ANN is data driven approach which able to be trained to map past values of a time series. In this study the forecast performance between neural network and classical time series forecasting method namely seasonal autoregressive integrated moving average models was being compared by utilizing gold price data. Moreover, the effect of different data preprocessing on the forecast performance of neural network being examined. The forecast accuracy was evaluated using mean absolute deviation, root mean square error and mean absolute percentage error. It was found that ANN produced the most accurate forecast when Box-Cox transformation was used as data preprocessing.

The solution of the point kinetics equations via converged accelerated Taylor series (CATS)

Energy Technology Data Exchange (ETDEWEB)

Ganapol, B.; Picca, P. [Dept. of Aerospace and Mechanical Engineering, Univ. of Arizona (United States); Previti, A.; Mostacci, D. [Laboratorio di Montecuccolino, Alma Mater Studiorum - Universita di Bologna (Italy)

2012-07-01

This paper deals with finding accurate solutions of the point kinetics equations including non-linear feedback, in a fast, efficient and straightforward way. A truncated Taylor series is coupled to continuous analytical continuation to provide the recurrence relations to solve the ordinary differential equations of point kinetics. Non-linear (Wynn-epsilon) and linear (Romberg) convergence accelerations are employed to provide highly accurate results for the evaluation of Taylor series expansions and extrapolated values of neutron and precursor densities at desired edits. The proposed Converged Accelerated Taylor Series, or CATS, algorithm automatically performs successive mesh refinements until the desired accuracy is obtained, making use of the intermediate results for converged initial values at each interval. Numerical performance is evaluated using case studies available from the literature. Nearly perfect agreement is found with the literature results generally considered most accurate. Benchmark quality results are reported for several cases of interest including step, ramp, zigzag and sinusoidal prescribed insertions and insertions with adiabatic Doppler feedback. A larger than usual (9) number of digits is included to encourage honest benchmarking. The benchmark is then applied to the enhanced piecewise constant algorithm (EPCA) currently being developed by the second author. (authors)

Assimilation of LAI time-series in crop production models

Science.gov (United States)

Kooistra, Lammert; Rijk, Bert; Nannes, Louis

2014-05-01

Agriculture is worldwide a large consumer of freshwater, nutrients and land. Spatial explicit agricultural management activities (e.g., fertilization, irrigation) could significantly improve efficiency in resource use. In previous studies and operational applications, remote sensing has shown to be a powerful method for spatio-temporal monitoring of actual crop status. As a next step, yield forecasting by assimilating remote sensing based plant variables in crop production models would improve agricultural decision support both at the farm and field level. In this study we investigated the potential of remote sensing based Leaf Area Index (LAI) time-series assimilated in the crop production model LINTUL to improve yield forecasting at field level. The effect of assimilation method and amount of assimilated observations was evaluated. The LINTUL-3 crop production model was calibrated and validated for a potato crop on two experimental fields in the south of the Netherlands. A range of data sources (e.g., in-situ soil moisture and weather sensors, destructive crop measurements) was used for calibration of the model for the experimental field in 2010. LAI from cropscan field radiometer measurements and actual LAI measured with the LAI-2000 instrument were used as input for the LAI time-series. The LAI time-series were assimilated in the LINTUL model and validated for a second experimental field on which potatoes were grown in 2011. Yield in 2011 was simulated with an R2 of 0.82 when compared with field measured yield. Furthermore, we analysed the potential of assimilation of LAI into the LINTUL-3 model through the 'updating' assimilation technique. The deviation between measured and simulated yield decreased from 9371 kg/ha to 8729 kg/ha when assimilating weekly LAI measurements in the LINTUL model over the season of 2011. LINTUL-3 furthermore shows the main growth reducing factors, which are useful for farm decision support. The combination of crop models and sensor

Increasing the temporal resolution of direct normal solar irradiance forecasted series

Science.gov (United States)

Fernández-Peruchena, Carlos M.; Gastón, Martin; Schroedter-Homscheidt, Marion; Marco, Isabel Martínez; Casado-Rubio, José L.; García-Moya, José Antonio

2017-06-01

A detailed knowledge of the solar resource is a critical point in the design and control of Concentrating Solar Power (CSP) plants. In particular, accurate forecasting of solar irradiance is essential for the efficient operation of solar thermal power plants, the management of energy markets, and the widespread implementation of this technology. Numerical weather prediction (NWP) models are commonly used for solar radiation forecasting. In the ECMWF deterministic forecasting system, all forecast parameters are commercially available worldwide at 3-hourly intervals. Unfortunately, as Direct Normal solar Irradiance (DNI) exhibits a great variability due to the dynamic effects of passing clouds, 3-h time resolution is insufficient for accurate simulations of CSP plants due to their nonlinear response to DNI, governed by various thermal inertias due to their complex response characteristics. DNI series of hourly or sub-hourly frequency resolution are normally used for an accurate modeling and analysis of transient processes in CSP technologies. In this context, the objective of this study is to propose a methodology for generating synthetic DNI time series at 1-h (or higher) temporal resolution from 3-h DNI series. The methodology is based upon patterns as being defined with help of the clear-sky envelope approach together with a forecast of maximum DNI value, and it has been validated with high quality measured DNI data.

The effect of sowing date and plant density on yield and yield components of safflower (Carthamus tinctorious L. in Rokh plateau .

Directory of Open Access Journals (Sweden)

seyd fazel fazeli kakhaki

2009-06-01

Full Text Available To investigate the effect of sowing date and plant density on yield and yield components of safflower ( Carthamus tinctorious as well as evaluating the possibility of the second sowing of the plant in Torbat Heidariyeh , a field experiment was conducted in Rokh, Cold Season Cereal Research Station 2005 . The experiment was conducted in split plot arrangement in complete randomized block design with four replications . Main plots were sowing date in five levels including 9 April, 10 May, 31 May, 20 June, 11 July and sub plots were plant density in three levels including 300000, 400000, 500000 plants per hectar. Some charactristics such as the number of capitulum per square meter, seed number in capitulum, seed weight, harvest index and seed yeild was evaluated.The highest seed yield was obtained in first sowing date in 3347 kg/ha and a delay in sowing date resulted a decrease in yield. The cold weather in (05/11/2005 caused flower fertility not accured, consequently, sowing was not successful . Results showed that the effect of sowing date on yield depends on the number of capitulum per unit area and the number of grains per capitulum. These two characteristics in th first sowing date in respect of the other dates were higher. The effect of density on yield was significant resulted on yield increase due to capitulum increase in unit area. As a result, the first sowing date with the highest density is recommended. However, The third and fourth sowing date can be considered as the second planting in a sequeational cropping system .

Comparison of thick-target (alpha,n yield calculation codes

Directory of Open Access Journals (Sweden)

Fernandes Ana C.

2017-01-01

Full Text Available Neutron production yields and energy distributions from (α,n reactions in light elements were calculated using three different codes (SOURCES, NEDIS and USD and compared with the existing experimental data in the 3.5-10 MeV alpha energy range. SOURCES and NEDIS display an agreement between calculated and measured yields in the decay series of 235U, 238U and 232Th within ±10% for most materials. The discrepancy increases with alpha energy but still an agreement of ±20% applies to all materials with reliable elemental production yields (the few exceptions are identified. The calculated neutron energy distributions describe the experimental data, with NEDIS retrieving very well the detailed features. USD generally underestimates the measured yields, in particular for compounds with heavy elements and/or at high alpha energies. The energy distributions exhibit sharp peaks that do not match the observations. These findings may be caused by a poor accounting of the alpha particle energy loss by the code. A big variability was found among the calculated neutron production yields for alphas from Sm decay; the lack of yield measurements for low (~2 MeV alphas does not allow to conclude on the codes’ accuracy in this energy region.

Study of calculated and measured time dependent delayed neutron yields

International Nuclear Information System (INIS)

Waldo, R.W.

1980-05-01

Time-dependent delayed neutron emission is of interest in reactor design, reactor dynamics, and nuclear physics studies. The delayed neutrons from neutron-induced fission of 232 U, 237 Np, 238 Pu, 241 Am, /sup 242m/Am, 245 Cm, and 249 Cf were studied for the first time. The delayed neutron emission from 232 Th, 233 U, 235 U, 238 U, 239 Pu, 241 Pu, and 242 Pu were measured as well. The data were used to develop an empirical expression for the total delayed neutron yield. The expression gives accurate results for a large variety of nuclides from 232 Th to 252 Cf. The data measuring the decay of delayed neutrons with time were used to derive another empirical expression predicting the delayed neutron emission with time. It was found that nuclides with similar mass-to-charge ratios have similar decay patterns. Thus the relative decay pattern of one nuclide can be established by any measured nuclide with a similar mass-to-charge ratio. A simple fission product yield model was developed and applied to delayed neutron precursors. It accurately predicts observed yield and decay characteristics. In conclusion, it is possible to not only estimate the total delayed neutron yield for a given nuclide but the time-dependent nature of the delayed neutrons as well. Reactors utilizing recycled fuel or burning actinides are likely to have inventories of fissioning nuclides that have not been studied until now. The delayed neutrons from these nuclides can now be incorporated so that their influence on the stability and control of reactors can be delineated. 8 figures, 39 tables

Muon reactivation in muon-catalyzed d-t fusion from accurate p-He+ stripping and excitation cross sections

International Nuclear Information System (INIS)

Stodden, C.D.; Monkhorst, H.J.; Szalewicz, K.

1990-01-01

Accurate cross sections are obtained for the excitation and stripping of a muon from αμ in collisions with hydrogen atoms. This is done by calculating the excitation, ionization, and charge-transfer cross sections for the p-He + collision and scaling the results. An impact-parameter coupled-state method with a basis set of up to 51 Sturmian wave functions is used to obtain cross sections at center-of-mass energies ranging from 20 to 600 keV. Along with Stark, Auger, radiative, and stopping rates these cross sections are used to calculate the probability of stripping a muon from αμ by numerically solving a set of coupled differential equations that describe the kinetics of αμ as it travels through a mixture of D 2 and T 2 . An effort has been made to minimize the uncertainty in the value of the stripping probability resulting in error bars of 9% and 11% at densities of 1.2 and 0.05 times liquid-hydrogen density, respectively. X-ray yields belonging to K and L series transitions among αμ states have also been computed. The present results are compared with recent theoretical and experimental data

Invited review: A commentary on predictive cheese yield formulas.

Science.gov (United States)

Emmons, D B; Modler, H W

2010-12-01

Predictive cheese yield formulas have evolved from one based only on casein and fat in 1895. Refinements have included moisture and salt in cheese and whey solids as separate factors, paracasein instead of casein, and exclusion of whey solids from moisture associated with cheese protein. The General, Barbano, and Van Slyke formulas were tested critically using yield and composition of milk, whey, and cheese from 22 vats of Cheddar cheese. The General formula is based on the sum of cheese components: fat, protein, moisture, salt, whey solids free of fat and protein, as well as milk salts associated with paracasein. The testing yielded unexpected revelations. It was startling that the sum of components in cheese was SofC) in cheese. The apparent low estimation of SofC led to the idea of adjusting upwards, for each vat, the 5 measured components in the formula by the observed SofC, as a fraction. The mean of the adjusted predicted yields as percentages of actual yields was 99.99%. The adjusted forms of the General, Barbano, and Van Slyke formulas gave predicted yields equal to the actual yields. It was apparent that unadjusted yield formulas did not accurately predict yield; however, unadjusted PY%AY can be useful as a control tool for analyses of cheese and milk. It was unexpected that total milk protein in the adjusted General formula gave the same predicted yields as casein and paracasein, indicating that casein or paracasein may not always be necessary for successful yield prediction. The use of constants for recovery of fat and protein in the adjusted General formula gave adjusted predicted yields equal to actual yields, indicating that analyses of cheese for protein and fat may not always be necessary for yield prediction. Composition of cheese was estimated using a predictive formula; actual yield was needed for estimation of composition. Adjusted formulas are recommended for estimating target yields and cheese yield efficiency. Constants for solute exclusion

Time-series modeling of long-term weight self-monitoring data.

Science.gov (United States)

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

Sensor-Generated Time Series Events: A Definition Language

Science.gov (United States)

Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

2012-01-01

There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

Parametric Identification of Solar Series based on an Adaptive ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

Department of Computer Science, University of Extremadura, Campus ... els, applying it to the case of sunspot series. .... inspired on the concept of artificial evolution (Goldberg 1989) (Rechenberg 1973) and ... benchmark when na = 5. ... clusion is that an accurate tuning for general purposes could be from na = 5, although.

Yield Estimation for Semipalatinsk Underground Nuclear Explosions Using Seismic Surface-wave Observations at Near-regional Distances

Science.gov (United States)

Adushkin, V. V.

- A statistical procedure is described for estimating the yields of underground nuclear tests at the former Soviet Semipalatinsk test site using the peak amplitudes of short-period surface waves observed at near-regional distances (Δ Semipalatinsk explosions, including the Soviet JVE explosion of September 14, 1988, and it is demonstrated that it provides seismic estimates of explosion yield which are typically within 20% of the yields determined for these same explosions using more accurate, non-seismic techniques based on near-source observations.

Dual-component video image analysis system (VIASCAN) as a predictor of beef carcass red meat yield percentage and for augmenting application of USDA yield grades.

Science.gov (United States)

Cannell, R C; Tatum, J D; Belk, K E; Wise, J W; Clayton, R P; Smith, G C

1999-11-01

An improved ability to quantify differences in the fabrication yields of beef carcasses would facilitate the application of value-based marketing. This study was conducted to evaluate the ability of the Dual-Component Australian VIASCAN to 1) predict fabricated beef subprimal yields as a percentage of carcass weight at each of three fat-trim levels and 2) augment USDA yield grading, thereby improving accuracy of grade placement. Steer and heifer carcasses (n = 240) were evaluated using VIASCAN, as well as by USDA expert and online graders, before fabrication of carcasses to each of three fat-trim levels. Expert yield grade (YG), online YG, VIASCAN estimates, and VIASCAN estimated ribeye area used to augment actual and expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, and hot carcass weight), respectively, 1) accounted for 51, 37, 46, and 55% of the variation in fabricated yields of commodity-trimmed subprimals, 2) accounted for 74, 54, 66, and 75% of the variation in fabricated yields of closely trimmed subprimals, and 3) accounted for 74, 54, 71, and 75% of the variation in fabricated yields of very closely trimmed subprimals. The VIASCAN system predicted fabrication yields more accurately than current online yield grading and, when certain VIASCAN-measured traits were combined with some USDA yield grade factors in an augmentation system, the accuracy of cutability prediction was improved, at packing plant line speeds, to a level matching that of expert graders applying grades at a comfortable rate.

Precise measurements of the thick target neutron yields of the 7Li(p,n) reaction

International Nuclear Information System (INIS)

Matysiak, W.; Prestwich, W.V.; Byun, S.H.

2011-01-01

Thick target neutron yield of the 7 Li(p,n) 7 Be reaction was measured in the proton energy range from 1.95 to 2.3 MeV by determining induced activity of the 7 Be. A HPGe detector was used to detect the 478 keV gamma-rays emitted through 7 Be decay. A series of irradiations with nominal proton energies of 1.95, 2.0, 2.1, 2.2, and 2.3 MeV were carried out. In an independent experiment, raw neutron spectra were collected by a 3 He ion chamber for the same series of proton energies. From the raw neutron spectra, it was noted, that the effective proton energies were lower than the nominal by 50-58 keV. After corrections for the proton energy offsets were applied, the measured neutron yields matched the analytically calculated yields within 20%. Long term stability of neutron yield was tested at two nominal proton energies, 2.1 and 1.95 MeV over an experimental period of one year. The results show that the yield at 2.1 MeV was stable within rmse variation coefficient of 4.7% and remained consistent even when the lithium target was replaced, whereas at 1.95 MeV, the maximum fluctuations reached a factor of 10.

Accurate mass measurements on neutron-deficient krypton isotopes

CERN Document Server

Rodríguez, D.; Äystö, J.; Beck, D.; Blaum, K.; Bollen, G.; Herfurth, F.; Jokinen, A.; Kellerbauer, A.; Kluge, H.-J.; Kolhinen, V.S.; Oinonen, M.; Sauvan, E.; Schwarz, S.

2006-01-01

The masses of $^{72–78,80,82,86}$Kr were measured directly with the ISOLTRAP Penning trap mass spectrometer at ISOLDE/CERN. For all these nuclides, the measurements yielded mass uncertainties below 10 keV. The ISOLTRAP mass values for $^{72–75}$Kr being more precise than the previous results obtained by means of other techniques, and thus completely determine the new values in the Atomic-Mass Evaluation. Besides the interest of these masses for nuclear astrophysics, nuclear structure studies, and Standard Model tests, these results constitute a valuable and accurate input to improve mass models. In this paper, we present the mass measurements and discuss the mass evaluation for these Kr isotopes.

Spatiotemporally enhancing time-series DMSP/OLS nighttime light imagery for assessing large-scale urban dynamics

Science.gov (United States)

Xie, Yanhua; Weng, Qihao

2017-06-01

Accurate, up-to-date, and consistent information of urban extents is vital for numerous applications central to urban planning, ecosystem management, and environmental assessment and monitoring. However, current large-scale urban extent products are not uniform with respect to definition, spatial resolution, temporal frequency, and thematic representation. This study aimed to enhance, spatiotemporally, time-series DMSP/OLS nighttime light (NTL) data for detecting large-scale urban changes. The enhanced NTL time series from 1992 to 2013 were firstly generated by implementing global inter-calibration, vegetation-based spatial adjustment, and urban archetype-based temporal modification. The dataset was then used for updating and backdating urban changes for the contiguous U.S.A. (CONUS) and China by using the Object-based Urban Thresholding method (i.e., NTL-OUT method, Xie and Weng, 2016b). The results showed that the updated urban extents were reasonably accurate, with city-scale RMSE (root mean square error) of 27 km2 and Kappa of 0.65 for CONUS, and 55 km2 and 0.59 for China, respectively. The backdated urban extents yielded similar accuracy, with RMSE of 23 km2 and Kappa of 0.63 in CONUS, while 60 km2 and 0.60 in China. The accuracy assessment further revealed that the spatial enhancement greatly improved the accuracy of urban updating and backdating by significantly reducing RMSE and slightly increasing Kappa values. The temporal enhancement also reduced RMSE, and improved the spatial consistency between estimated and reference urban extents. Although the utilization of enhanced NTL data successfully detected urban size change, relatively low locational accuracy of the detected urban changes was observed. It is suggested that the proposed methodology would be more effective for updating and backdating global urban maps if further fusion of NTL data with higher spatial resolution imagery was implemented.

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

Science.gov (United States)

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

Modeling osmotic salinity effects on yield characteristics of substrate-grown greenhouse crops

NARCIS (Netherlands)

Sonneveld, C.; Bos, van den A.L.; Voogt, W.

2004-01-01

In a series of experiments with different osmotic potentials in the root environment, various vegetables, and ornamentals were grown in a substrate system. The osmotic potential was varied by addition of nutrients. Yield characteristics of the crop were related to the osmotic potential of the

Constructing ordinal partition transition networks from multivariate time series.

Science.gov (United States)

Zhang, Jiayang; Zhou, Jie; Tang, Ming; Guo, Heng; Small, Michael; Zou, Yong

2017-08-10

A growing number of algorithms have been proposed to map a scalar time series into ordinal partition transition networks. However, most observable phenomena in the empirical sciences are of a multivariate nature. We construct ordinal partition transition networks for multivariate time series. This approach yields weighted directed networks representing the pattern transition properties of time series in velocity space, which hence provides dynamic insights of the underling system. Furthermore, we propose a measure of entropy to characterize ordinal partition transition dynamics, which is sensitive to capturing the possible local geometric changes of phase space trajectories. We demonstrate the applicability of pattern transition networks to capture phase coherence to non-coherence transitions, and to characterize paths to phase synchronizations. Therefore, we conclude that the ordinal partition transition network approach provides complementary insight to the traditional symbolic analysis of nonlinear multivariate time series.

Modeling Taylor series approximations for prompt neutron kinetics with lab view simulations

International Nuclear Information System (INIS)

Adzri, E. P.

2012-09-01

The reactor point kinetics equations have been subjected to intense research in an effort to find simple yet accurate numerical solutions methods. The equations are very stiff numerically, meaning that there is a wide variation in the decay constants, so that using a particular time step in the numerical solution may provide sufficient accuracy for the group, but not for another. Several solutions techniques have been presented on the point kinetics equations with varying degrees of complexity. These include Power Series Solutions, CORE, PCA, Genapol and Taylor series methods. In this research, algorithms were developed based on the first and second order Taylor series expansion and simulated in LabVIEW to solve the Reactor Point Kinetics equations using block diagram nodes implemented within stacked sequences. The algorithms developed were fast,accurate and simple to code. Several reactivity insertions were used to simulate the change in neutron population with time. The LabVIEW- Taylor series solutions were compared with other solution techniques such as Power Series Solutions, CORE, PCA, Genapol and McMahon and Pierson's Taylor series approximation. The results of LabVIEW-Taylor series technique used by McMahon and Pearson The LabVIEW-implemented techniques were found to agree very well with these other methods. At 1x10 -8 s the neutron population was 1.000220 neutrons / cm 3 , at 1 x 10 -2 s it was 2.007681 neutrons / cm 3 and at 1x10 -1 s it was 2.075317 neutrons / cm 3 ; same results reported by Genapol for a fast reactor, it produced good and accurate results and compared very favorably with other methods found in the literature. Using much smaller time steps to the order or 10 -8 s commensurate with fast reactor parameters also produced very satisfactory results, indicating that the LabVIEW-based Taylor series technique is suitable for simulating the kinetics of fast reactors as well as thermal reactors. Algorithms developed that included second order terms

Analysis of complex time series using refined composite multiscale entropy

International Nuclear Information System (INIS)

Wu, Shuen-De; Wu, Chiu-Wen; Lin, Shiou-Gwo; Lee, Kung-Yen; Peng, Chung-Kang

2014-01-01

Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.

Neural networks and traditional time series methods: a synergistic combination in state economic forecasts.

Science.gov (United States)

Hansen, J V; Nelson, R D

1997-01-01

Ever since the initial planning for the 1997 Utah legislative session, neural-network forecasting techniques have provided valuable insights for analysts forecasting tax revenues. These revenue estimates are critically important since agency budgets, support for education, and improvements to infrastructure all depend on their accuracy. Underforecasting generates windfalls that concern taxpayers, whereas overforecasting produces budget shortfalls that cause inadequately funded commitments. The pattern finding ability of neural networks gives insightful and alternative views of the seasonal and cyclical components commonly found in economic time series data. Two applications of neural networks to revenue forecasting clearly demonstrate how these models complement traditional time series techniques. In the first, preoccupation with a potential downturn in the economy distracts analysis based on traditional time series methods so that it overlooks an emerging new phenomenon in the data. In this case, neural networks identify the new pattern that then allows modification of the time series models and finally gives more accurate forecasts. In the second application, data structure found by traditional statistical tools allows analysts to provide neural networks with important information that the networks then use to create more accurate models. In summary, for the Utah revenue outlook, the insights that result from a portfolio of forecasts that includes neural networks exceeds the understanding generated from strictly statistical forecasting techniques. In this case, the synergy clearly results in the whole of the portfolio of forecasts being more accurate than the sum of the individual parts.

Comparison of annual maximum series and partial duration series methods for modeling extreme hydrologic events

DEFF Research Database (Denmark)

Madsen, Henrik; Rasmussen, Peter F.; Rosbjerg, Dan

1997-01-01

Two different models for analyzing extreme hydrologic events, based on, respectively, partial duration series (PDS) and annual maximum series (AMS), are compared. The PDS model assumes a generalized Pareto distribution for modeling threshold exceedances corresponding to a generalized extreme value......). In the case of ML estimation, the PDS model provides the most efficient T-year event estimator. In the cases of MOM and PWM estimation, the PDS model is generally preferable for negative shape parameters, whereas the AMS model yields the most efficient estimator for positive shape parameters. A comparison...... of the considered methods reveals that in general, one should use the PDS model with MOM estimation for negative shape parameters, the PDS model with exponentially distributed exceedances if the shape parameter is close to zero, the AMS model with MOM estimation for moderately positive shape parameters, and the PDS...

A self-interaction-free local hybrid functional: Accurate binding energies vis-à-vis accurate ionization potentials from Kohn-Sham eigenvalues

International Nuclear Information System (INIS)

Schmidt, Tobias; Kümmel, Stephan; Kraisler, Eli; Makmal, Adi; Kronik, Leeor

2014-01-01

We present and test a new approximation for the exchange-correlation (xc) energy of Kohn-Sham density functional theory. It combines exact exchange with a compatible non-local correlation functional. The functional is by construction free of one-electron self-interaction, respects constraints derived from uniform coordinate scaling, and has the correct asymptotic behavior of the xc energy density. It contains one parameter that is not determined ab initio. We investigate whether it is possible to construct a functional that yields accurate binding energies and affords other advantages, specifically Kohn-Sham eigenvalues that reliably reflect ionization potentials. Tests for a set of atoms and small molecules show that within our local-hybrid form accurate binding energies can be achieved by proper optimization of the free parameter in our functional, along with an improvement in dissociation energy curves and in Kohn-Sham eigenvalues. However, the correspondence of the latter to experimental ionization potentials is not yet satisfactory, and if we choose to optimize their prediction, a rather different value of the functional's parameter is obtained. We put this finding in a larger context by discussing similar observations for other functionals and possible directions for further functional development that our findings suggest

Fuzzy time-series based on Fibonacci sequence for stock price forecasting

Science.gov (United States)

Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

2007-07-01

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

Accurate Modeling Method for Cu Interconnect

Science.gov (United States)

Yamada, Kenta; Kitahara, Hiroshi; Asai, Yoshihiko; Sakamoto, Hideo; Okada, Norio; Yasuda, Makoto; Oda, Noriaki; Sakurai, Michio; Hiroi, Masayuki; Takewaki, Toshiyuki; Ohnishi, Sadayuki; Iguchi, Manabu; Minda, Hiroyasu; Suzuki, Mieko

This paper proposes an accurate modeling method of the copper interconnect cross-section in which the width and thickness dependence on layout patterns and density caused by processes (CMP, etching, sputtering, lithography, and so on) are fully, incorporated and universally expressed. In addition, we have developed specific test patterns for the model parameters extraction, and an efficient extraction flow. We have extracted the model parameters for 0.15μm CMOS using this method and confirmed that 10%τpd error normally observed with conventional LPE (Layout Parameters Extraction) was completely dissolved. Moreover, it is verified that the model can be applied to more advanced technologies (90nm, 65nm and 55nm CMOS). Since the interconnect delay variations due to the processes constitute a significant part of what have conventionally been treated as random variations, use of the proposed model could enable one to greatly narrow the guardbands required to guarantee a desired yield, thereby facilitating design closure.

The effect of conservation tillage on crop yield in China

Directory of Open Access Journals (Sweden)

Hongwen LI,Jin HE,Huanwen GAO,Ying CHEN,Zhiqiang ZHANG

2015-06-01

Full Text Available Traditional agricultural practices have resulted in decreased soil fertility, shortage of water resources and deterioration of agricultural ecological environment, which are seriously affecting grain production. Conservation tillage (CT research has been developed and applied in China since the 1960s and 1970s, and a series of development policies have been issued by the Chinese government. Recent research and application have shown that CT has positive effects on crop yields in China. According to the data from the Conservation Tillage Research Center (CTRC, Chinese Ministry of Agriculture (MOA, the mean crop yield increase can be at least 4% in double cropping systems in the North China Plain and 6% in single cropping systems in the dryland areas of North-east and North-west China. Crop yield increase was particularly significant in dryland areas and drought years. The mechanism for the yield increase in CT system can be attributed to enhanced soil water content and improved soil properties. Development strategies have been implemented to accelerate the adoption of CT in China.

The Laplace series solution for local fractional Korteweg-de Vries equation

Directory of Open Access Journals (Sweden)

Ye Shan-Shan

2016-01-01

Full Text Available In this paper, we consider a new application of the local fractional Laplace series expansion method to handle the local fractional Korteweg-de Vries equation. The obtained solution with non-differentiable type shows that the technology is accurate and efficient.

Economics and yields of energy plantations: Status and potential

International Nuclear Information System (INIS)

Kenney, W.A.; Gambles, R.L.; Zsuffa, L.

1992-01-01

A study was carried out to: determine the factors affecting the cost of energy conversion feedstocks in short rotation intensive culture plantations of trees; determine the factors influencing biomass yield; identify interrelationships between the previous two objectives; present estimates of potential biomass yields and associated economics; and to identify gaps in the knowledge of the economics and yields of biomass production and their interrelationships. Reported costs for most aspects had a wide range. Currently, yields of 10-15 dry Mg/hectare/y are readily achievable. Using the cost and yield data, and assuming a biomass price of $40/dry Mg, a series of cash flow analyses were performed. For the low cost inputs, all scenarios were marginally profitable. For the high cost inputs, none of the scenarios were profitable. A current scenario, using figures for contract farming, was not profitable, however this system would break even with a yield of 23.3 dry Mg/hectare/y, within the range of some production clones. A future scenario using farm labour with increased productivity, product values, and machinery efficiencies yielded a profit-making situation. The addition of incentives increased profitability. There is great potential for the production of woody biomass in Canada as a feedstock for energy and other products. Continued and more intensive breeding and selection to develop high yielding stress tolerant clones, cost efficient harvesting systems, continued research into optimization of planting density, rotation length and cultural techniques, and characterization of promising clones with respect to nutrient-use efficiency, site requirements and pest/disease resistance are important areas for further work. 81 refs., 3 figs., 13 tabs

Prediction of failure strain and burst pressure in high yield-to-tensile strength ratio linepipe

International Nuclear Information System (INIS)

Law, M.; Bowie, G.

2007-01-01

Failure pressures and strains were predicted for a number of burst tests as part of a project to explore failure strain in high yield-to-tensile strength ratio linepipe. Twenty-three methods for predicting the burst pressure and six methods of predicting the failure strain are compared with test results. Several methods were identified which gave accurate and reliable estimates of burst pressure. No method of accurately predicting the failure strain was found, though the best was noted

Prediction of failure strain and burst pressure in high yield-to-tensile strength ratio linepipe

Energy Technology Data Exchange (ETDEWEB)

Law, M. [Institute of Materials and Engineering Science, Australian Nuclear Science and Technology Organisation (ANSTO), Lucas Heights, NSW (Australia)]. E-mail: mlx@ansto.gov.au; Bowie, G. [BlueScope Steel Ltd., Level 11, 120 Collins St, Melbourne, Victoria 3000 (Australia)

2007-08-15

Failure pressures and strains were predicted for a number of burst tests as part of a project to explore failure strain in high yield-to-tensile strength ratio linepipe. Twenty-three methods for predicting the burst pressure and six methods of predicting the failure strain are compared with test results. Several methods were identified which gave accurate and reliable estimates of burst pressure. No method of accurately predicting the failure strain was found, though the best was noted.

Parametric, nonparametric and parametric modelling of a chaotic circuit time series

Science.gov (United States)

Timmer, J.; Rust, H.; Horbelt, W.; Voss, H. U.

2000-09-01

The determination of a differential equation underlying a measured time series is a frequently arising task in nonlinear time series analysis. In the validation of a proposed model one often faces the dilemma that it is hard to decide whether possible discrepancies between the time series and model output are caused by an inappropriate model or by bad estimates of parameters in a correct type of model, or both. We propose a combination of parametric modelling based on Bock's multiple shooting algorithm and nonparametric modelling based on optimal transformations as a strategy to test proposed models and if rejected suggest and test new ones. We exemplify this strategy on an experimental time series from a chaotic circuit where we obtain an extremely accurate reconstruction of the observed attractor.

AMID: Accurate Magnetic Indoor Localization Using Deep Learning

Directory of Open Access Journals (Sweden)

Namkyoung Lee

2018-05-01

Full Text Available Geomagnetic-based indoor positioning has drawn a great attention from academia and industry due to its advantage of being operable without infrastructure support and its reliable signal characteristics. However, it must overcome the problems of ambiguity that originate with the nature of geomagnetic data. Most studies manage this problem by incorporating particle filters along with inertial sensors. However, they cannot yield reliable positioning results because the inertial sensors in smartphones cannot precisely predict the movement of users. There have been attempts to recognize the magnetic sequence pattern, but these attempts are proven only in a one-dimensional space, because magnetic intensity fluctuates severely with even a slight change of locations. This paper proposes accurate magnetic indoor localization using deep learning (AMID, an indoor positioning system that recognizes magnetic sequence patterns using a deep neural network. Features are extracted from magnetic sequences, and then the deep neural network is used for classifying the sequences by patterns that are generated by nearby magnetic landmarks. Locations are estimated by detecting the landmarks. AMID manifested the proposed features and deep learning as an outstanding classifier, revealing the potential of accurate magnetic positioning with smartphone sensors alone. The landmark detection accuracy was over 80% in a two-dimensional environment.

Accurate quantification of polycyclic aromatic hydrocarbons in dust samples using microwave-assisted solvent extraction combined with isotope-dilution mass spectrometry

International Nuclear Information System (INIS)

Itoh, Nobuyasu; Fushimi, Akihiro; Yarita, Takashi; Aoyagi, Yoshie; Numata, Masahiko

2011-01-01

Highlights: → We applied MAE-IDMS for accurate quantification of PAHs in dust samples. → Both partitioning and isotopic equilibria can be achieved using this technique. → MAE-IDMS can provide accurate concentrations even if extraction efficiencies were low. → Characteristics of samples strongly affected for low extraction efficiencies of PAHs. - Abstract: For accurate quantification of polycyclic aromatic hydrocarbons (PAHs) in dust samples, we investigated the use of microwave-assisted solvent extraction (MAE) combined with isotope-dilution mass spectrometry (IDMS) using deuterium-labelled PAHs (D-PAHs). Although MAE with a methanol/toluene mixture (1:3 by volume) at 160 deg. C for 40 min was best for extracting PAHs from tunnel dust among examined, the recovery yields of D-PAHs decreased with increasing molecular weight (<40% for MW ≥ 264; that of deuterium-labelled indeno[123-cd]pyrene (D-IcdP) was only 7.1%). Although the residues were extracted a second time, the observed concentrations did not change dramatically (<5%), and the recovery yields of heavier D-PAHs (i.e., MW ≥ 264) were approximately half of those of the first extract, including D-IcdP (3.4%). These results suggest that both partitioning and isotopic equilibria of PAHs and D-PAHs between sample and solvent were achieved for extractable heavier PAHs under the condition. Thus, the observed concentrations of PAHs obtained by MAE-IDMS were reasonable, even though recovery yields of D-PAHs were <50%. From the results of carbon analyses and extractable contents, lower recovery yields of D-PAHs from the tunnel dust were due to a large content of char with low extractable contents.

An evaluation of biomass yield stability of switchgrass (Panicum virgatum L.) cultivars

International Nuclear Information System (INIS)

Sharma, N.; Piscioneri, I.; Pignatelli, V.

2003-01-01

The present work deals with evaluation of the adaptation and biomass production of various switchgrass cultivars (upland and lowland type) in Southern Italy. A field trial was established in 1998 with 15 switchgrass varieties in ENEA Trisaia (Matera). The experiment was conducted for four years (1998-2001). During each growing period, a series of measurements were taken. At the end of each growing season, a final harvest was made in order to estimate the fresh and dry matter yields of the different varieties. The mean dry matter yield was recorded at a maximum (12.36 t/ha) in the third year, and it fluctuated from 5.63 (9005439) to 26.08 (SL 93-3) t/ha. The crop yields tend to stabilize from the fourth year of its cultivation. In fact, the yield recorded for this year was reduced to 10.27 t/ha, averaged over all the varieties

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

Science.gov (United States)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Modeling time-series count data: the unique challenges facing political communication studies.

Science.gov (United States)

Fogarty, Brian J; Monogan, James E

2014-05-01

This paper demonstrates the importance of proper model specification when analyzing time-series count data in political communication studies. It is common for scholars of media and politics to investigate counts of coverage of an issue as it evolves over time. Many scholars rightly consider the issues of time dependence and dynamic causality to be the most important when crafting a model. However, to ignore the count features of the outcome variable overlooks an important feature of the data. This is particularly the case when modeling data with a low number of counts. In this paper, we argue that the Poisson autoregressive model (Brandt and Williams, 2001) accurately meets the needs of many media studies. We replicate the analyses of Flemming et al. (1997), Peake and Eshbaugh-Soha (2008), and Ura (2009) and demonstrate that models missing some of the assumptions of the Poisson autoregressive model often yield invalid inferences. We also demonstrate that the effect of any of these models can be illustrated dynamically with estimates of uncertainty through a simulation procedure. The paper concludes with implications of these findings for the practical researcher. Copyright © 2013 Elsevier Inc. All rights reserved.

Simple, fast and accurate two-diode model for photovoltaic modules

Energy Technology Data Exchange (ETDEWEB)

Ishaque, Kashif; Salam, Zainal; Taheri, Hamed [Faculty of Electrical Engineering, Universiti Teknologi Malaysia, UTM 81310, Skudai, Johor Bahru (Malaysia)

2011-02-15

This paper proposes an improved modeling approach for the two-diode model of photovoltaic (PV) module. The main contribution of this work is the simplification of the current equation, in which only four parameters are required, compared to six or more in the previously developed two-diode models. Furthermore the values of the series and parallel resistances are computed using a simple and fast iterative method. To validate the accuracy of the proposed model, six PV modules of different types (multi-crystalline, mono-crystalline and thin-film) from various manufacturers are tested. The performance of the model is evaluated against the popular single diode models. It is found that the proposed model is superior when subjected to irradiance and temperature variations. In particular the model matches very accurately for all important points of the I-V curves, i.e. the peak power, short-circuit current and open circuit voltage. The modeling method is useful for PV power converter designers and circuit simulator developers who require simple, fast yet accurate model for the PV module. (author)

The accurate assessment of small-angle X-ray scattering data.

Science.gov (United States)

Grant, Thomas D; Luft, Joseph R; Carter, Lester G; Matsui, Tsutomu; Weiss, Thomas M; Martel, Anne; Snell, Edward H

2015-01-01

Small-angle X-ray scattering (SAXS) has grown in popularity in recent times with the advent of bright synchrotron X-ray sources, powerful computational resources and algorithms enabling the calculation of increasingly complex models. However, the lack of standardized data-quality metrics presents difficulties for the growing user community in accurately assessing the quality of experimental SAXS data. Here, a series of metrics to quantitatively describe SAXS data in an objective manner using statistical evaluations are defined. These metrics are applied to identify the effects of radiation damage, concentration dependence and interparticle interactions on SAXS data from a set of 27 previously described targets for which high-resolution structures have been determined via X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. The studies show that these metrics are sufficient to characterize SAXS data quality on a small sample set with statistical rigor and sensitivity similar to or better than manual analysis. The development of data-quality analysis strategies such as these initial efforts is needed to enable the accurate and unbiased assessment of SAXS data quality.

Statistical modeling of isoform splicing dynamics from RNA-seq time series data.

Science.gov (United States)

Huang, Yuanhua; Sanguinetti, Guido

2016-10-01

Isoform quantification is an important goal of RNA-seq experiments, yet it remains problematic for genes with low expression or several isoforms. These difficulties may in principle be ameliorated by exploiting correlated experimental designs, such as time series or dosage response experiments. Time series RNA-seq experiments, in particular, are becoming increasingly popular, yet there are no methods that explicitly leverage the experimental design to improve isoform quantification. Here, we present DICEseq, the first isoform quantification method tailored to correlated RNA-seq experiments. DICEseq explicitly models the correlations between different RNA-seq experiments to aid the quantification of isoforms across experiments. Numerical experiments on simulated datasets show that DICEseq yields more accurate results than state-of-the-art methods, an advantage that can become considerable at low coverage levels. On real datasets, our results show that DICEseq provides substantially more reproducible and robust quantifications, increasing the correlation of estimates from replicate datasets by up to 10% on genes with low or moderate expression levels (bottom third of all genes). Furthermore, DICEseq permits to quantify the trade-off between temporal sampling of RNA and depth of sequencing, frequently an important choice when planning experiments. Our results have strong implications for the design of RNA-seq experiments, and offer a novel tool for improved analysis of such datasets. Python code is freely available at http://diceseq.sf.net G.Sanguinetti@ed.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Assessment of Cane Yields on Well-drained Ferralsols in the Sugar-cane Estate of Central Cameroon

Directory of Open Access Journals (Sweden)

Van Ranst, E.

1999-01-01

Full Text Available The potential yields of irrigated and of rainfed sugar-cane on three ferrallitic soil series, well represented in the Nkoteng sugar-cane estate of Central Cameroon, are estimated following different methods. The potential yield of irrigated sugar-cane is estimated from the total maximum evapotranspiration during the crop cycle. The potential yield of rainfed sugar-cane is estimated following two methods for the establishment of a water balance and for the determination of a yield reduction as a result of a water deficit. The calculated potential yields are higher than the observed ones. The yield reduction due to rain fed cropping can mainly be attributed to water shortage during the late yield formation and the ripening periods. A supplementary yield decline is due to a combined action of an acid soil reaction, a possible Al-toxicity a low base saturation, an inadequate CEC, organic matter content and P-availability which may adequately explain the actual yield level.

Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

Science.gov (United States)

Jeffries, G. R.; Cohn, A.; Griffin, T. S.; Bragança, A.

2017-12-01

Understanding the farm size-specific characteristics of crop yields and yield gaps may help to improve yields by enabling better targeting of technical assistance and agricultural development programs. Linking remote sensing-based yield estimates with property boundaries provides a novel view of the relationship between farm size and yield structure (yield magnitude, gaps, and stability over time). A growing literature documents variations in yield gaps, but largely ignores the role of farm size as a factor shaping yield structure. Research on the inverse farm size-productivity relationship (IR) theory - that small farms are more productive than large ones all else equal - has documented that yield magnitude may vary by farm size, but has not considered other yield structure characteristics. We examined farm size - yield structure relationships for soybeans in Brazil for years 2001-2015. Using out-of-sample soybean yield predictions from a statistical model, we documented 1) gaps between the 95th percentile of attained yields and mean yields within counties and individual fields, and 2) yield stability defined as the standard deviation of time-detrended yields at given locations. We found a direct relationship between soy yields and farm size at the national level, while the strength and the sign of the relationship varied by region. Soybean yield gaps were found to be inversely related to farm size metrics, even when yields were only compared to farms of similar size. The relationship between farm size and yield stability was nonlinear, with mid-sized farms having the most stable yields. The work suggests that farm size is an important factor in understanding yield structure and that opportunities for improving soy yields in Brazil are greatest among smaller farms.

Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns

Science.gov (United States)

Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto

2017-09-01

Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.

Quantum Yields in Mixed-Conifer Forests and Ponderosa Pine Plantations

Science.gov (United States)

Wei, L.; Marshall, J. D.; Zhang, J.

2008-12-01

Most process-based physiological models require canopy quantum yield of photosynthesis as a starting point to simulate carbon sequestration and subsequently gross primary production (GPP). The quantum yield is a measure of photosynthetic efficiency expressed in moles of CO2 assimilated per mole of photons absorbed; the process is influenced by environmental factors. In the summer 2008, we measured quantum yields on both sun and shade leaves for four conifer species at five sites within Mica Creek Experimental Watershed (MCEW) in northern Idaho and one conifer species at three sites in northern California. The MCEW forest is typical of mixed conifer stands dominated by grand fir (Abies grandis (Douglas ex D. Don) Lindl.). In northern California, the three sites with contrasting site qualities are ponderosa pine (Pinus ponderosa C. Lawson var. ponderosa) plantations that were experimentally treated with vegetation control, fertilization, and a combination of both. We found that quantum yields in MCEW ranged from ~0.045 to ~0.075 mol CO2 per mol incident photon. However, there were no significant differences between canopy positions, or among sites or tree species. In northern California, the mean value of quantum yield of three sites was 0.051 mol CO2/mol incident photon. No significant difference in quantum yield was found between canopy positions, or among treatments or sites. The results suggest that these conifer species maintain relatively consistent quantum yield in both MCEW and northern California. This consistency simplifies the use of a process-based model to accurately predict forest productivity in these areas.

Changes in diurnal temperature range and national cereal yields

Energy Technology Data Exchange (ETDEWEB)

Lobell, D

2007-04-26

Models of yield responses to temperature change have often considered only changes in average temperature (Tavg), with the implicit assumption that changes in the diurnal temperature range (DTR) can safely be ignored. The goal of this study was to evaluate this assumption using a combination of historical datasets and climate model projections. Data on national crop yields for 1961-2002 in the 10 leading producers of wheat, rice, and maize were combined with datasets on climate and crop locations to evaluate the empirical relationships between Tavg, DTR, and crop yields. In several rice and maize growing regions, including the two major nations for each crop, there was a clear negative response of yields to increased DTR. This finding reflects a nonlinear response of yields to temperature, which likely results from greater water and heat stress during hot days. In many other cases, the effects of DTR were not statistically significant, in part because correlations of DTR with other climate variables and the relatively short length of the time series resulted in wide confidence intervals for the estimates. To evaluate whether future changes in DTR are relevant to crop impact assessments, yield responses to projected changes in Tavg and DTR by 2046-2065 from 11 climate models were estimated. The mean climate model projections indicated an increase in DTR in most seasons and locations where wheat is grown, mixed projections for maize, and a general decrease in DTR for rice. These mean projections were associated with wide ranges that included zero in nearly all cases. The estimated impacts of DTR changes on yields were generally small (<5% change in yields) relative to the consistently negative impact of projected warming of Tavg. However, DTR changes did significantly affect yield responses in several cases, such as in reducing US maize yields and increasing India rice yields. Because DTR projections tend to be positively correlated with Tavg, estimates of yields

Hydrogen atoms can be located accurately and precisely by x-ray crystallography.

Science.gov (United States)

Woińska, Magdalena; Grabowsky, Simon; Dominiak, Paulina M; Woźniak, Krzysztof; Jayatilaka, Dylan

2016-05-01

Precise and accurate structural information on hydrogen atoms is crucial to the study of energies of interactions important for crystal engineering, materials science, medicine, and pharmacy, and to the estimation of physical and chemical properties in solids. However, hydrogen atoms only scatter x-radiation weakly, so x-rays have not been used routinely to locate them accurately. Textbooks and teaching classes still emphasize that hydrogen atoms cannot be located with x-rays close to heavy elements; instead, neutron diffraction is needed. We show that, contrary to widespread expectation, hydrogen atoms can be located very accurately using x-ray diffraction, yielding bond lengths involving hydrogen atoms (A-H) that are in agreement with results from neutron diffraction mostly within a single standard deviation. The precision of the determination is also comparable between x-ray and neutron diffraction results. This has been achieved at resolutions as low as 0.8 Å using Hirshfeld atom refinement (HAR). We have applied HAR to 81 crystal structures of organic molecules and compared the A-H bond lengths with those from neutron measurements for A-H bonds sorted into bonds of the same class. We further show in a selection of inorganic compounds that hydrogen atoms can be located in bridging positions and close to heavy transition metals accurately and precisely. We anticipate that, in the future, conventional x-radiation sources at in-house diffractometers can be used routinely for locating hydrogen atoms in small molecules accurately instead of large-scale facilities such as spallation sources or nuclear reactors.

Ocean time-series near Bermuda: Hydrostation S and the US JGOFS Bermuda Atlantic time-series study

Science.gov (United States)

Michaels, Anthony F.; Knap, Anthony H.

1992-01-01

Bermuda is the site of two ocean time-series programs. At Hydrostation S, the ongoing biweekly profiles of temperature, salinity and oxygen now span 37 years. This is one of the longest open-ocean time-series data sets and provides a view of decadal scale variability in ocean processes. In 1988, the U.S. JGOFS Bermuda Atlantic Time-series Study began a wide range of measurements at a frequency of 14-18 cruises each year to understand temporal variability in ocean biogeochemistry. On each cruise, the data range from chemical analyses of discrete water samples to data from electronic packages of hydrographic and optics sensors. In addition, a range of biological and geochemical rate measurements are conducted that integrate over time-periods of minutes to days. This sampling strategy yields a reasonable resolution of the major seasonal patterns and of decadal scale variability. The Sargasso Sea also has a variety of episodic production events on scales of days to weeks and these are only poorly resolved. In addition, there is a substantial amount of mesoscale variability in this region and some of the perceived temporal patterns are caused by the intersection of the biweekly sampling with the natural spatial variability. In the Bermuda time-series programs, we have added a series of additional cruises to begin to assess these other sources of variation and their impacts on the interpretation of the main time-series record. However, the adequate resolution of higher frequency temporal patterns will probably require the introduction of new sampling strategies and some emerging technologies such as biogeochemical moorings and autonomous underwater vehicles.

Classification and Mapping of Paddy Rice by Combining Landsat and SAR Time Series Data

Directory of Open Access Journals (Sweden)

Seonyoung Park

2018-03-01

Full Text Available Rice is an important food resource, and the demand for rice has increased as population has expanded. Therefore, accurate paddy rice classification and monitoring are necessary to identify and forecast rice production. Satellite data have been often used to produce paddy rice maps with more frequent update cycle (e.g., every year than field surveys. Many satellite data, including both optical and SAR sensor data (e.g., Landsat, MODIS, and ALOS PALSAR, have been employed to classify paddy rice. In the present study, time series data from Landsat, RADARSAT-1, and ALOS PALSAR satellite sensors were synergistically used to classify paddy rice through machine learning approaches over two different climate regions (sites A and B. Six schemes considering the composition of various combinations of input data by sensor and collection date were evaluated. Scheme 6 that fused optical and SAR sensor time series data at the decision level yielded the highest accuracy (98.67% for site A and 93.87% for site B. Performance of paddy rice classification was better in site A than site B, which consists of heterogeneous land cover and has low data availability due to a high cloud cover rate. This study also proposed Paddy Rice Mapping Index (PMI considering spectral and phenological characteristics of paddy rice. PMI represented well the spatial distribution of paddy rice in both regions. Google Earth Engine was adopted to produce paddy rice maps over larger areas using the proposed PMI-based approach.

Precise measurements of the thick target neutron yields of the {sup 7}Li(p,n) reaction

Energy Technology Data Exchange (ETDEWEB)

Matysiak, W., E-mail: matysiw@mcmaster.ca [Department of Medical Physics and Applied Radiation Sciences, McMaster University, Hamilton, Ont., L8S 4K1 (Canada); Prestwich, W.V.; Byun, S.H. [Department of Medical Physics and Applied Radiation Sciences, McMaster University, Hamilton, Ont., L8S 4K1 (Canada)

2011-07-01

Thick target neutron yield of the {sup 7}Li(p,n){sup 7}Be reaction was measured in the proton energy range from 1.95 to 2.3 MeV by determining induced activity of the {sup 7}Be. A HPGe detector was used to detect the 478 keV gamma-rays emitted through {sup 7}Be decay. A series of irradiations with nominal proton energies of 1.95, 2.0, 2.1, 2.2, and 2.3 MeV were carried out. In an independent experiment, raw neutron spectra were collected by a {sup 3}He ion chamber for the same series of proton energies. From the raw neutron spectra, it was noted, that the effective proton energies were lower than the nominal by 50-58 keV. After corrections for the proton energy offsets were applied, the measured neutron yields matched the analytically calculated yields within 20%. Long term stability of neutron yield was tested at two nominal proton energies, 2.1 and 1.95 MeV over an experimental period of one year. The results show that the yield at 2.1 MeV was stable within rmse variation coefficient of 4.7% and remained consistent even when the lithium target was replaced, whereas at 1.95 MeV, the maximum fluctuations reached a factor of 10.

Stable and accurate methods for identification of water bodies from Landsat series imagery using meta-heuristic algorithms

Science.gov (United States)

Gamshadzaei, Mohammad Hossein; Rahimzadegan, Majid

2017-10-01

Identification of water extents in Landsat images is challenging due to surfaces with similar reflectance to water extents. The objective of this study is to provide stable and accurate methods for identifying water extents in Landsat images based on meta-heuristic algorithms. Then, seven Landsat images were selected from various environmental regions in Iran. Training of the algorithms was performed using 40 water pixels and 40 nonwater pixels in operational land imager images of Chitgar Lake (one of the study regions). Moreover, high-resolution images from Google Earth were digitized to evaluate the results. Two approaches were considered: index-based and artificial intelligence (AI) algorithms. In the first approach, nine common water spectral indices were investigated. AI algorithms were utilized to acquire coefficients of optimal band combinations to extract water extents. Among the AI algorithms, the artificial neural network algorithm and also the ant colony optimization, genetic algorithm, and particle swarm optimization (PSO) meta-heuristic algorithms were implemented. Index-based methods represented different performances in various regions. Among AI methods, PSO had the best performance with average overall accuracy and kappa coefficient of 93% and 98%, respectively. The results indicated the applicability of acquired band combinations to extract accurately and stably water extents in Landsat imagery.

New hybrid non-linear transformations of divergent perturbation series for quadratic Zeeman effects

International Nuclear Information System (INIS)

Belkic, D.

1989-01-01

The problem of hydrogen atoms in an external uniform magnetic field (quadratic Zeeman effect) is studied by means of perturbation theory. The power series for the ground-state energy in terms of magnetic-field strength B is divergent. Nevertheless, it is possible to induce convergence of this divergent series by applying various non-linear transformations. These transformations of originally divergent perturbation series yield new sequences, which then converge. The induced convergence is, however, quite slow. A new hybrid Shanks-Levin non-linear transform is devised here for accelerating these slowly converging series and sequences. Significant improvement in the convergence rate is obtained. Agreement with the exact results is excellent. (author)

A Simple yet Accurate Method for Students to Determine Asteroid Rotation Periods from Fragmented Light Curve Data

Science.gov (United States)

Beare, R. A.

2008-01-01

Professional astronomers use specialized software not normally available to students to determine the rotation periods of asteroids from fragmented light curve data. This paper describes a simple yet accurate method based on Microsoft Excel[R] that enables students to find periods in asteroid light curve and other discontinuous time series data of…

Forecasting Inflation Using Interest-Rate and Time-Series Models: Some International Evidence.

OpenAIRE

Hafer, R W; Hein, Scott E

1990-01-01

It has been suggested that inflation forecasts derived from short-term interest rates are as accurate as time-series forecasts. Previous analyses of this notion have focused on U.S. data, providing mixed results. In this article, the authors extend previous work by testing the hypothesis using data taken from the United States and five other countries. Using monthly Eurocurrency rates and the consumer price index for the period 1967-86, their results indicate that time-series forecasts of inf...

Using neutral network to infer the hydrodynamic yield of aspherical sources

International Nuclear Information System (INIS)

Moran, B.; Glenn, L.A.

1993-07-01

We distinguish two kinds of difficulties with yield determination from aspherical sources. The first kind, the spoofing difficulty, occurs when a fraction of the energy of the explosion is channeled in such a way that it is not detected by the CORRTEX cable. In this case, neither neural networks nor any expert system can be expected to accurately estimate the yield without detailed information about device emplacement within the canister. Numerical simulations however, can provide an upper bound on the undetected fraction of the explosive energy. In the second instance, the interpretation difficulty, the data appear abnormal when analyzed using similar-explosion-scaling and the assumption of a spherical front. The inferred yield varies with time and the confidence in the yield estimate decreases. It is this kind of problem we address in this paper and for which neural networks can make a contribution. We used a back propagation neural network to infer the hydrodynamic yield of simulated aspherical sources. We trained the network using a subset of simulations from 3 different aspherical sources, with 3 different yields, and 3 satellite offset separations. The trained network was able to predict the yield within 15% in all cases and to identify the correct type of aspherical source in most cases. The predictive capability of the network increased with a larger training set. The neural network approach can easily incorporate information from new calculations or experiments and is therefore flexible and easy to maintain. We describe the potential capabilities and limitations in using such networks for yield estimations

Using neural networks to infer the hydrodynamic yield of aspherical sources

International Nuclear Information System (INIS)

Moran, B.; Glenn, L.

1993-01-01

We distinguish two kinds of difficulties with yield determination from aspherical sources. The first kind, the spoofing difficulty, occurs when a fraction of the energy of the explosion is channeled in such a way that it is not detected by the CORRTEX cable. In this case, neither neural networks nor any expert system can be expected to accurately estimate the yield without detailed information about device emplacement within the canister. Numerical simulations however, can provide an upper bound on the undetected fraction of the explosive energy. In the second instance, the interpretation difficulty, the data appear abnormal when analyzed using similar-explosion-scaling and the assumption of a spherical front. The inferred yield varies with time and the confidence in the yield estimate decreases. It is this kind of problem we address in this paper and for which neural networks can make a contribution. We used a back propagation neural network to infer the hydrodynamic yield of simulated aspherical sources. We trained the network using a subset of simulations from 3 different aspherical sources, with 3 different yield, and 3 satellite offset separations. The trained network was able to predict the yield within 15% in all cases and to identify the correct type of aspherical source in most cases. The predictive capability of the network increased with a larger training set. The neural network approach can easily incorporate information from new calculations or experiments and is therefore flexible and easy to maintain. We describe the potential capabilities and limitations in using such networks for yield estimations

Time series regression and ARIMAX for forecasting currency flow at Bank Indonesia in Sulawesi region

Science.gov (United States)

Suharsono, Agus; Suhartono, Masyitha, Aulia; Anuravega, Arum

2015-12-01

The purpose of the study is to forecast the outflow and inflow of currency at Indonesian Central Bank or Bank Indonesia (BI) in Sulawesi Region. The currency outflow and inflow data tend to have a trend pattern which is influenced by calendar variation effects. Therefore, this research focuses to apply some forecasting methods that could handle calendar variation effects, i.e. Time Series Regression (TSR) and ARIMAX models, and compare the forecast accuracy with ARIMA model. The best model is selected based on the lowest of Root Mean Squares Errors (RMSE) at out-sample dataset. The results show that ARIMA is the best model for forecasting the currency outflow and inflow at South Sulawesi. Whereas, the best model for forecasting the currency outflow at Central Sulawesi and Southeast Sulawesi, and for forecasting the currency inflow at South Sulawesi and North Sulawesi is TSR. Additionally, ARIMAX is the best model for forecasting the currency outflow at North Sulawesi. Hence, the results show that more complex models do not neccessary yield more accurate forecast than the simpler one.

On the absolute calibration of a DT fusion neutron yield diagnostic

Directory of Open Access Journals (Sweden)

Ruiz C.L.

2013-11-01

Full Text Available Recent advances in Inertial Confinement Fusion (ICF experiments at Lawrence Livermore National Laboratory's National Ignition Facility (NIF have underscored the need for accurate total yield measurements of DT neutrons because yield measurements provide a measure of the predicted performance of the experiments. Future gas-puff DT experiments at Sandia National Laboratory's Z facility will also require similar measurements. For ICF DT experiments, the standard technique for measuring the neutron (14.1 MeV yield, counts the activity (counts/minute induced in irradiated copper samples. This activity occurs by the 63Cu(n,2n62Cu reaction where 62Cu decays by positrons (β+ with a half-life of 9.67 minutes. The calibrations discussed here employ the associated-particle method (APM, where the α (4He particles from the T(d,n4He reaction are measured to infer neutron fluxes on a copper sample. The flux induces 62Cu activity, measured in a coincidence counting system. The method leads to a relationship between a DT neutron yield and copper activity known as the F-factor. The goal in future experiments is to apply this calibration to measure the yield at NIF with a combined uncertainty approaching 5%.

Energy-Based Wavelet De-Noising of Hydrologic Time Series

Science.gov (United States)

Sang, Yan-Fang; Liu, Changming; Wang, Zhonggen; Wen, Jun; Shang, Lunyu

2014-01-01

De-noising is a substantial issue in hydrologic time series analysis, but it is a difficult task due to the defect of methods. In this paper an energy-based wavelet de-noising method was proposed. It is to remove noise by comparing energy distribution of series with the background energy distribution, which is established from Monte-Carlo test. Differing from wavelet threshold de-noising (WTD) method with the basis of wavelet coefficient thresholding, the proposed method is based on energy distribution of series. It can distinguish noise from deterministic components in series, and uncertainty of de-noising result can be quantitatively estimated using proper confidence interval, but WTD method cannot do this. Analysis of both synthetic and observed series verified the comparable power of the proposed method and WTD, but de-noising process by the former is more easily operable. The results also indicate the influences of three key factors (wavelet choice, decomposition level choice and noise content) on wavelet de-noising. Wavelet should be carefully chosen when using the proposed method. The suitable decomposition level for wavelet de-noising should correspond to series' deterministic sub-signal which has the smallest temporal scale. If too much noise is included in a series, accurate de-noising result cannot be obtained by the proposed method or WTD, but the series would show pure random but not autocorrelation characters, so de-noising is no longer needed. PMID:25360533

TOSGAGETM-8000A series X-ray thickness gauge

International Nuclear Information System (INIS)

Obara, Satoshi

2009-01-01

X-ray thickness gauges are widely used for online measurement of the thickness of plates in a steel roiling line. As the thickness of the steel has a direct effect on the yield rate of the rolling line, thickness gauge measurement data are necessary for accuracy and reliability. In recent years, there have also been increasing requirements for rapid delivery, flexible interface specifications, and low cost. To meet these market requirements. Toshiba has developed the TOSGAGE TM -8000A series X-ray thickness gauge, which is the first release of a new series of measuring instruments for rolling applications with a new interface and employing an industrial computer for data processing. (author)

A multiple-scale power series method for solving nonlinear ordinary differential equations

Directory of Open Access Journals (Sweden)

Chein-Shan Liu

2016-02-01

Full Text Available The power series solution is a cheap and effective method to solve nonlinear problems, like the Duffing-van der Pol oscillator, the Volterra population model and the nonlinear boundary value problems. A novel power series method by considering the multiple scales $R_k$ in the power term $(t/R_k^k$ is developed, which are derived explicitly to reduce the ill-conditioned behavior in the data interpolation. In the method a huge value times a tiny value is avoided, such that we can decrease the numerical instability and which is the main reason to cause the failure of the conventional power series method. The multiple scales derived from an integral can be used in the power series expansion, which provide very accurate numerical solutions of the problems considered in this paper.

In-Season Yield Prediction of Cabbage with a Hand-Held Active Canopy Sensor.

Science.gov (United States)

Ji, Rongting; Min, Ju; Wang, Yuan; Cheng, Hu; Zhang, Hailin; Shi, Weiming

2017-10-08

Efficient and precise yield prediction is critical to optimize cabbage yields and guide fertilizer application. A two-year field experiment was conducted to establish a yield prediction model for cabbage by using the Greenseeker hand-held optical sensor. Two cabbage cultivars (Jianbao and Pingbao) were used and Jianbao cultivar was grown for 2 consecutive seasons but Pingbao was only grown in the second season. Four chemical nitrogen application rates were implemented: 0, 80, 140, and 200 kg·N·ha -1 . Normalized difference vegetation index (NDVI) was collected 20, 50, 70, 80, 90, 100, 110, 120, 130, and 140 days after transplanting (DAT). Pearson correlation analysis and regression analysis were performed to identify the relationship between the NDVI measurements and harvested yields of cabbage. NDVI measurements obtained at 110 DAT were significantly correlated to yield and explained 87-89% and 75-82% of the cabbage yield variation of Jianbao cultivar over the two-year experiment and 77-81% of the yield variability of Pingbao cultivar. Adjusting the yield prediction models with CGDD (cumulative growing degree days) could make remarkable improvement to the accuracy of the prediction model and increase the determination coefficient to 0.82, while the modification with DFP (days from transplanting when GDD > 0) values did not. The integrated exponential yield prediction equation was better than linear or quadratic functions and could accurately make in-season estimation of cabbage yields with different cultivars between years.

Quantifying Selection with Pool-Seq Time Series Data.

Science.gov (United States)

Taus, Thomas; Futschik, Andreas; Schlötterer, Christian

2017-11-01

Allele frequency time series data constitute a powerful resource for unraveling mechanisms of adaptation, because the temporal dimension captures important information about evolutionary forces. In particular, Evolve and Resequence (E&R), the whole-genome sequencing of replicated experimentally evolving populations, is becoming increasingly popular. Based on computer simulations several studies proposed experimental parameters to optimize the identification of the selection targets. No such recommendations are available for the underlying parameters selection strength and dominance. Here, we introduce a highly accurate method to estimate selection parameters from replicated time series data, which is fast enough to be applied on a genome scale. Using this new method, we evaluate how experimental parameters can be optimized to obtain the most reliable estimates for selection parameters. We show that the effective population size (Ne) and the number of replicates have the largest impact. Because the number of time points and sequencing coverage had only a minor effect, we suggest that time series analysis is feasible without major increase in sequencing costs. We anticipate that time series analysis will become routine in E&R studies. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Accuracy of genomic selection for alfalfa biomass yield in different reference populations.

Science.gov (United States)

Annicchiarico, Paolo; Nazzicari, Nelson; Li, Xuehui; Wei, Yanling; Pecetti, Luciano; Brummer, E Charles

2015-12-01

Genomic selection based on genotyping-by-sequencing (GBS) data could accelerate alfalfa yield gains, if it displayed moderate ability to predict parent breeding values. Its interest would be enhanced by predicting ability also for germplasm/reference populations other than those for which it was defined. Predicting accuracy may be influenced by statistical models, SNP calling procedures and missing data imputation strategies. Landrace and variety material from two genetically-contrasting reference populations, i.e., 124 elite genotypes adapted to the Po Valley (sub-continental climate; PV population) and 154 genotypes adapted to Mediterranean-climate environments (Me population), were genotyped by GBS and phenotyped in separate environments for dry matter yield of their dense-planted half-sib progenies. Both populations showed no sub-population genetic structure. Predictive accuracy was higher by joint rather than separate SNP calling for the two data sets, and using random forest imputation of missing data. Highest accuracy was obtained using Support Vector Regression (SVR) for PV, and Ridge Regression BLUP and SVR for Me germplasm. Bayesian methods (Bayes A, Bayes B and Bayesian Lasso) tended to be less accurate. Random Forest Regression was the least accurate model. Accuracy attained about 0.35 for Me in the range of 0.30-0.50 missing data, and 0.32 for PV at 0.50 missing data, using at least 10,000 SNP markers. Cross-population predictions based on a smaller subset of common SNPs implied a relative loss of accuracy of about 25% for Me and 30% for PV. Genome-wide association analyses based on large subsets of M. truncatula-aligned markers revealed many SNPs with modest association with yield, and some genome areas hosting putative QTLs. A comparison of genomic vs. conventional selection for parent breeding value assuming 1-year vs. 5-year selection cycles, respectively, indicated over three-fold greater predicted yield gain per unit time for genomic selection

Direct Measurement of Initial 230TH/ 232TH Ratios in Central Texas Speleothems for More Accurate Age Determination

Science.gov (United States)

Wortham, B. E.; Banner, J. L.; James, E.; Loewy, S. L.

2013-12-01

Speleothems, calcite deposits in caves, preserve a record of climate in their growth rate, isotope ratios and trace element concentrations. These variables must be tied to precise ages to produce pre-instrumental records of climate. The 238U-234U- 230Th disequilibrium method of dating can yield precise ages if the amount of 230Th from the decay of radiogenic 238U can be constrained. 230Th in a speleothem calcite growth layer has two potential sources - 1) decay of radioactive 238U since the time of growth of the calcite layer; and 2) initial detrital 230Th, incorporated along with detrital 232Th, into the calcite layer at the time it grew. Although the calcite lattice does not typically incorporate Th, samples can contain impurities with relatively high Th contents. Initial 230Th/232Th is commonly estimated by assuming a source with bulk-Earth U/Th values in a state of secular equilibrium in the 238U-decay chain. The uncertainty in this 230Th/232Th estimate is also assumed, typically at +/-100%. Both assumptions contribute to uncertainty in ages determined for young speleothems. If the amount of initial detrital 230Th can be better quantified for samples or sites, then U-series ages will have smaller uncertainties and more precisely define the time series of climate proxies. This study determined the initial 230Th/232Th of modern calcite to provide more precise dates for central Texas speleothems. Calcite was grown on glass-plate substrates placed under active drips in central Texas caves. The 230Th/232Th of this modern calcite was determined using thermal ionization mass spectrometry. Results show that: 1) initial 230Th/232Th ratios can be accurately determined in these young samples and 2) measuring 230Th/232Th reduces the uncertainties in previously-determined ages on stalagmites from under the same drips. For example, measured initial 230Th/232Th in calcite collected on substrates from different locations in the cave at Westcave Preserve are 15.3 × 0.67 ppm

Evaluation of anisotropic effective stress-strain criteria for the biaxial yield and flow of 2024 aluminum tubes

International Nuclear Information System (INIS)

Stout, M.G.; Hecker, S.S.; Bourcier, R.

1983-01-01

2024 aluminum tubes, heat treated to a T6 and T8 temper, were tested in combinations of tension-internal pressure and tension-torsion loading. Yield loci and flow behavior were determined for both modes of loading and compared to theoretical predictions. Both tempers of 2024 aluminum exhibited crystallographic textures and anisotropic yield and flow. Hill's quadratic yield criterion and the associated flow rule under-estimate balanced biaxial yield and flow, which is consistent with hydraulic bulge data on other face-centered cubic metals. Hill's nonquadratic criterion, which adds one additional parameter, and Bassani's criterion, which adds two parameters, predict the anisotropic yield behavior much more accurately. Predictions of the complete flow behavior, including strain paths, with these anisotropic criteria could be improved markedly by including provisions for planar anisotropy

Hybrid Wavelet De-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series

Science.gov (United States)

WANG, D.; Wang, Y.; Zeng, X.

2017-12-01

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, Wavelet De-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series.

A method for an accurate in-flight calibration of AVHRR data for vegetation index calculation

OpenAIRE

Asmami , Mbarek; Wald , Lucien

1992-01-01

International audience; A significant degradation in the Advanced Very High Resolution Radiometer (AVHRR) responsitivity, on the NOAA satellite series, has occurred since the prelaunch calibration and with time since launch. This affects the index vegetation (NDVI), which is an important source of information for monitoring vegetation conditions on regional and global scales. Many studies have been carried out which use the Viewing Earth calibration approach in order to provide accurate calib...

CHANGES IN CLIMATIC CHARACTERISTICS AND CROP YIELD IN KWARA STATE (NIGERIA

Directory of Open Access Journals (Sweden)

O. Oriola

2017-01-01

Full Text Available This paper assessed the vagaries of climatic elements on crop yield in Kwara State with a view to predicting the future climatic suitability level for selected crops in the state. Descriptive and infrential statistics analytical methods were used to examine the pattern of climatic elements for a period of 30 years. Analysis of variance was used to examine the variations in crop yield and also to determine whether or not significant differences in the harvests of the period under investigation. Correlation analysis was used to determine the relationship between climatic elements and crop yield while multiple regression analysis was used to determine the contribution of each climatic elements to crop yield. Time series analysis was used to project crop yield from 2014 to 2025. GAEZ model was adopted to determine the climatic suitability for the selected crops over time 1960 - 2050 and ArcGIS 10.3 software was used to produce the crop suitability maps. The result revealed that cassava, yam, maize and cowpea would be less suitable for production with the rate at which the climate is changing. The result also revealed that the climatic suitability level for cassava, yam, maize and cowpea would reduce drastically with time. The prediction shows severe impacts of changes in the selected climatic elements on both overall climatic suitability and crop the selected crops yield for by 2050.

The Importance of Juvenile Root Traits for Crop Yields

Science.gov (United States)

White, Philip; Adu, Michael; Broadley, Martin; Brown, Lawrie; Dupuy, Lionel; George, Timothy; Graham, Neil; Hammond, John; Hayden, Rory; Neugebauer, Konrad; Nightingale, Mark; Ramsay, Gavin; Thomas, Catherine; Thompson, Jacqueline; Wishart, Jane; Wright, Gladys

2014-05-01

Genetic variation in root system architecture (RSA) is an under-exploited breeding resource. This is partly a consequence of difficulties in the rapid and accurate assessment of subterranean root systems. However, although the characterisation of root systems of large plants in the field are both time-consuming and labour-intensive, high-throughput (HTP) screens of root systems of juvenile plants can be performed in the field, glasshouse or laboratory. It is hypothesised that improving the root systems of juvenile plants can accelerate access to water and essential mineral elements, leading to rapid crop establishment and, consequently, greater yields. This presentation will illustrate how aspects of the juvenile root systems of potato (Solanum tuberosum L.) and oilseed rape (OSR; Brassica napus L.) correlate with crop yields and examine the reasons for such correlations. It will first describe the significant positive relationships between early root system development, phosphorus acquisition, canopy establishment and eventual yield among potato genotypes. It will report the development of a glasshouse assay for root system architecture (RSA) of juvenile potato plants, the correlations between root system architectures measured in the glasshouse and field, and the relationships between aspects of the juvenile root system and crop yields under drought conditions. It will then describe the development of HTP systems for assaying RSA of OSR seedlings, the identification of genetic loci affecting RSA in OSR, the development of mathematical models describing resource acquisition by OSR, and the correlations between root traits recorded in the HTP systems and yields of OSR in the field.

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

Science.gov (United States)

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 (Pchanges in climatic variables in this region. Yield of rice increased with rainfall (Pclimatic 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.

Series Resistance Monitoring for Photovoltaic Modules in the Vicinity of MPP

DEFF Research Database (Denmark)

Sera, Dezso

2010-01-01

Faults and performance deterioration issues related to increases of the series resistance in PV modules or arrays are one of the most common causes to decrease the energy yield of photovoltaic installations. Therefore, the early detection of such failure types is very important in order to minimize...

Unstable Periodic Orbit Analysis of Histograms of Chaotic Time Series

International Nuclear Information System (INIS)

Zoldi, S.M.

1998-01-01

Using the Lorenz equations, we have investigated whether unstable periodic orbits (UPOs) associated with a strange attractor may predict the occurrence of the robust sharp peaks in histograms of some experimental chaotic time series. Histograms with sharp peaks occur for the Lorenz parameter value r=60.0 but not for r=28.0 , and the sharp peaks for r=60.0 do not correspond to a histogram derived from any single UPO. However, we show that histograms derived from the time series of a non-Axiom-A chaotic system can be accurately predicted by an escape-time weighting of UPO histograms. copyright 1998 The American Physical Society

对称多溴代二苯醚类化合物的精确合成%Accurate synthesis of symmetrical polybrominated diphenyl ethers

Institute of Scientific and Technical Information of China (English)

崔凯; 沈宏; 苏长会; 马洁洁; 丁志远

2016-01-01

A series of symmetrical polybrominated diphenyliodonium trifluoromethanesulfonic were synthesized from brominated io-dobenzene and brominated benzene catalyzed by m-chloroperoxybenzoic acid and trifluoromethanesulfonic acid. Then Corresponding symmetrical polybrominated diphenyl ethers were accurately synthesized with them and brominated phenol in alkaline condition. The advantages of the procedure were:mild reaction condition,easy operation,simple after-treatment,high yield and purity of products.%用间氯过氧苯甲酸和三氟甲磺酸做酸性氧化体系，以溴代碘苯及溴苯合成了对称的溴代二苯基碘盐。再以其同溴代苯酚在碱性条件下反应，精确合成对称的多溴代二苯醚。此法合成目标化合物方法简便，反应条件温和，后处理简单，产品纯度好，收率高。

Dependence of simulated positron emitter yields in ion beam cancer therapy on modeling nuclear fragmentation

DEFF Research Database (Denmark)

Lühr, Armin; Priegnitz, Marlen; Fiedler, Fine

2014-01-01

In ion beam cancer therapy, range verification in patients using positron emission tomography (PET) requires the comparison of measured with simulated positron emitter yields. We found that (1) changes in modeling nuclear interactions strongly affected the positron emitter yields and that (2) Monte...... Carlo simulations with SHIELD-HIT10A reasonably matched the most abundant PET isotopes 11C and 15O. We observed an ion-energy (i.e., depth) dependence of the agreement between SHIELD-HIT10A and measurement. Improved modeling requires more accurate measurements of cross-section values....

The Acoustic and Peceptual Effects of Series and Parallel Processing

Directory of Open Access Journals (Sweden)

Melinda C. Anderson

2009-01-01

Full Text Available Temporal envelope (TE cues provide a great deal of speech information. This paper explores how spectral subtraction and dynamic-range compression gain modifications affect TE fluctuations for parallel and series configurations. In parallel processing, algorithms compute gains based on the same input signal, and the gains in dB are summed. In series processing, output from the first algorithm forms the input to the second algorithm. Acoustic measurements show that the parallel arrangement produces more gain fluctuations, introducing more changes to the TE than the series configurations. Intelligibility tests for normal-hearing (NH and hearing-impaired (HI listeners show (1 parallel processing gives significantly poorer speech understanding than an unprocessed (UNP signal and the series arrangement and (2 series processing and UNP yield similar results. Speech quality tests show that UNP is preferred to both parallel and series arrangements, although spectral subtraction is the most preferred. No significant differences exist in sound quality between the series and parallel arrangements, or between the NH group and the HI group. These results indicate that gain modifications affect intelligibility and sound quality differently. Listeners appear to have a higher tolerance for gain modifications with regard to intelligibility, while judgments for sound quality appear to be more affected by smaller amounts of gain modification.

Population size and yield of Baffin Bay beluga (Delphinapterus leucas stocks

Directory of Open Access Journals (Sweden)

Stuart Innes

2002-07-01

Full Text Available A surplus production model within a Sampling, Importance Resampling (SIR Bayesian analysis was used to estimate stock sizes and yields of Baffin Bay belugas. The catch of belugas in West Greenland increased in 1968 and has remained well above sustainable rates. SIR analysis indicated a decline of about 50% between 1981 and 1994, with a credibility interval that included a previous estimate of 62%. The estimated stock sizes of belugas wintering off West Greenland in 1998 and 1999 were approximately 5,100 and 4,100 respectively and were not significantly different than an estimate based on aerial surveys combined for both years. Projected to 1999 this stock can sustain median landings of 109 whales with a total kill of about 155, based on posterior estimates of struck and lost plus under-reporting. The declining stock size index series did not provide sufficient information to estimate the potential maximum rate of population growth, the number of whales struck and lost, or the shape of the production curve with precision. Estimating these parameters requires an index time series with a marked step change in catch or a series with increasing stock sizes. The stock size estimate for the belugas wintering in the North Water in 1999 was approximately 14,800 but there is no information about the population biology of these whales. The estimated maximum sustainable yield (landed for the North Water stock was 317 belugas.

A global evaluation of harmonic analysis of time series under distrinct gap conditions

NARCIS (Netherlands)

Zhou, J.; Hu, G.; Menenti, M.

2013-01-01

Reconstruction of time series of satellite image data to obtain continuous, consistent and accurate data for downstream applications is playing a crucial role in remote sensing applications such as vegetation dynamics, land cover changes, land-atmosphere interactions and climate changes. Among the

Taylor Series Trajectory Calculations Including Oblateness Effects and Variable Atmospheric Density

Science.gov (United States)

Scott, James R.

2011-01-01

Taylor series integration is implemented in NASA Glenn's Spacecraft N-body Analysis Program, and compared head-to-head with the code's existing 8th- order Runge-Kutta Fehlberg time integration scheme. This paper focuses on trajectory problems that include oblateness and/or variable atmospheric density. Taylor series is shown to be significantly faster and more accurate for oblateness problems up through a 4x4 field, with speedups ranging from a factor of 2 to 13. For problems with variable atmospheric density, speedups average 24 for atmospheric density alone, and average 1.6 to 8.2 when density and oblateness are combined.

Impacts of drought on grape yields in Western Cape, South Africa

Science.gov (United States)

Araujo, Julio A.; Abiodun, Babatunde J.; Crespo, Olivier

2016-01-01

Droughts remain a threat to grape yields in South Africa. Previous studies on the impacts of climate on grape yield in the country have focussed on the impact of rainfall and temperature separately; meanwhile, grape yields are affected by drought, which is a combination of rainfall and temperature influences. The present study investigates the impacts of drought on grape yields in the Western Cape (South Africa) at district and farm scales. The study used a new drought index that is based on simple water balance (Standardized Precipitation Evapotranspiration Index; hereafter, SPEI) to identify drought events and used a correlation analysis to identify the relationship between drought and grape yields. A crop simulation model (Agricultural Production Systems sIMulator, APSIM) was applied at the farm scale to investigate the role of irrigation in mitigating the impacts of drought on grape yield. The model gives a realistic simulation of grape yields. The Western Cape has experienced a series of severe droughts in the past few decades. The severe droughts occurred when a decrease in rainfall occurred simultaneously with an increase in temperature. El Niño Southern Oscillation (ENSO) appears to be an important driver of drought severity in the Western Cape, because most of the severe droughts occurred in El Niño years. At the district scale, the correlation between drought index and grape yield is weak ( r≈-0.5), but at the farm scale, it is strong ( r≈-0.9). This suggests that many farmers are able to mitigate the impacts of drought on grape yields through irrigation management. At the farm scale, where the impact of drought on grape yields is high, poor yield years coincide with moderate or severe drought periods. The APSIM simulation, which gives a realistic simulation of grape yields at the farm scale, suggests that grape yields become more sensitive to spring and summer droughts in the absence of irrigation. Results of this study may guide decision-making on

Time series clustering in large data sets

Directory of Open Access Journals (Sweden)

Jiří Fejfar

2011-01-01

Full Text Available The clustering of time series is a widely researched area. There are many methods for dealing with this task. We are actually using the Self-organizing map (SOM with the unsupervised learning algorithm for clustering of time series. After the first experiment (Fejfar, Weinlichová, Šťastný, 2009 it seems that the whole concept of the clustering algorithm is correct but that we have to perform time series clustering on much larger dataset to obtain more accurate results and to find the correlation between configured parameters and results more precisely. The second requirement arose in a need for a well-defined evaluation of results. It seems useful to use sound recordings as instances of time series again. There are many recordings to use in digital libraries, many interesting features and patterns can be found in this area. We are searching for recordings with the similar development of information density in this experiment. It can be used for musical form investigation, cover songs detection and many others applications.The objective of the presented paper is to compare clustering results made with different parameters of feature vectors and the SOM itself. We are describing time series in a simplistic way evaluating standard deviations for separated parts of recordings. The resulting feature vectors are clustered with the SOM in batch training mode with different topologies varying from few neurons to large maps.There are other algorithms discussed, usable for finding similarities between time series and finally conclusions for further research are presented. We also present an overview of the related actual literature and projects.

Prediction of County-Level Corn Yields Using an Energy-Crop Growth Index.

Science.gov (United States)

Andresen, Jeffrey A.; Dale, Robert F.; Fletcher, Jerald J.; Preckel, Paul V.

1989-01-01

Weather conditions significantly affect corn yields. while weather remains as the major uncontrolled variable in crop production, an understanding of the influence of weather on yields can aid in early and accurate assessment of the impact of weather and climate on crop yields and allow for timely agricultural extension advisories to help reduce farm management costs and improve marketing, decisions. Based on data for four representative countries in Indiana from 1960 to 1984 (excluding 1970 because of the disastrous southern corn leaf blight), a model was developed to estimate corn (Zea mays L.) yields as a function of several composite soil-crop-weather variables and a technology-trend marker, applied nitrogen fertilizer (N). The model was tested by predicting corn yields for 15 other counties. A daily energy-crop growth (ECG) variable in which different weights were used for the three crop-weather variables which make up the daily ECG-solar radiation intercepted by the canopy, a temperature function, and the ratio of actual to potential evapotranspiration-performed better than when the ECG components were weighted equally. The summation of the weighted daily ECG over a relatively short period (36 days spanning silk) was found to provide the best index for predicting county average corn yield. Numerical estimation results indicate that the ratio of actual to potential evapotranspiration (ET/PET) is much more important than the other two ECG factors in estimating county average corn yield in Indiana.

Characterization of time series via Rényi complexity-entropy curves

Science.gov (United States)

Jauregui, M.; Zunino, L.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2018-05-01

One of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the Shannon entropy and the statistical complexity. Recently, this idea has been generalized by considering the Tsallis monoparametric generalization of the Shannon entropy, yielding complexity-entropy curves. These curves have proven to enhance the discrimination among different time series related to stochastic and chaotic processes of numerical and experimental nature. Here we further explore these complexity-entropy curves in the context of the Rényi entropy, which is another monoparametric generalization of the Shannon entropy. By combining the Rényi entropy with the proper generalization of the statistical complexity, we associate a parametric curve (the Rényi complexity-entropy curve) with a given time series. We explore this approach in a series of numerical and experimental applications, demonstrating the usefulness of this new technique for time series analysis. We show that the Rényi complexity-entropy curves enable the differentiation among time series of chaotic, stochastic, and periodic nature. In particular, time series of stochastic nature are associated with curves displaying positive curvature in a neighborhood of their initial points, whereas curves related to chaotic phenomena have a negative curvature; finally, periodic time series are represented by vertical straight lines.

Spatial Sampling of Weather Data for Regional Crop Yield Simulations

Science.gov (United States)

Van Bussel, Lenny G. J.; Ewert, Frank; Zhao, Gang; Hoffmann, Holger; Enders, Andreas; Wallach, Daniel; Asseng, Senthold; Baigorria, Guillermo A.; Basso, Bruno; Biernath, Christian;

A comparative analysis of spectral exponent estimation techniques for 1/f(β) processes with applications to the analysis of stride interval time series.

Science.gov (United States)

Schaefer, Alexander; Brach, Jennifer S; Perera, Subashan; Sejdić, Ervin

2014-01-30

The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f)=1/f(β). The scaling exponent β is thus often interpreted as a "biomarker" of relative health and decline. This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. Copyright © 2013 Elsevier B.V. All rights reserved.

A comparative analysis of spectral exponent estimation techniques for 1/fβ processes with applications to the analysis of stride interval time series

Science.gov (United States)

Schaefer, Alexander; Brach, Jennifer S.; Perera, Subashan; Sejdić, Ervin

2013-01-01

Background The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f) = 1/fβ. The scaling exponent β is thus often interpreted as a “biomarker” of relative health and decline. New Method This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. Results The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Comparison with Existing Methods: Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. Conclusions The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. PMID:24200509

Optimizing rice yields while minimizing yield-scaled global warming potential.

Science.gov (United States)

Pittelkow, Cameron M; Adviento-Borbe, Maria A; van Kessel, Chris; Hill, James E; Linquist, Bruce A

2014-05-01

To meet growing global food demand with limited land and reduced environmental impact, agricultural greenhouse gas (GHG) emissions are increasingly evaluated with respect to crop productivity, i.e., on a yield-scaled as opposed to area basis. Here, we compiled available field data on CH4 and N2 O emissions from rice production systems to test the hypothesis that in response to fertilizer nitrogen (N) addition, yield-scaled global warming potential (GWP) will be minimized at N rates that maximize yields. Within each study, yield N surplus was calculated to estimate deficit or excess N application rates with respect to the optimal N rate (defined as the N rate at which maximum yield was achieved). Relationships between yield N surplus and GHG emissions were assessed using linear and nonlinear mixed-effects models. Results indicate that yields increased in response to increasing N surplus when moving from deficit to optimal N rates. At N rates contributing to a yield N surplus, N2 O and yield-scaled N2 O emissions increased exponentially. In contrast, CH4 emissions were not impacted by N inputs. Accordingly, yield-scaled CH4 emissions decreased with N addition. Overall, yield-scaled GWP was minimized at optimal N rates, decreasing by 21% compared to treatments without N addition. These results are unique compared to aerobic cropping systems in which N2 O emissions are the primary contributor to GWP, meaning yield-scaled GWP may not necessarily decrease for aerobic crops when yields are optimized by N fertilizer addition. Balancing gains in agricultural productivity with climate change concerns, this work supports the concept that high rice yields can be achieved with minimal yield-scaled GWP through optimal N application rates. Moreover, additional improvements in N use efficiency may further reduce yield-scaled GWP, thereby strengthening the economic and environmental sustainability of rice systems. © 2013 John Wiley & Sons Ltd.

An evaluation of the lamb vision system as a predictor of lamb carcass red meat yield percentage.

Science.gov (United States)

Brady, A S; Belk, K E; LeValley, S B; Dalsted, N L; Scanga, J A; Tatum, J D; Smith, G C

2003-06-01

An objective method for predicting red meat yield in lamb carcasses is needed to accurately assess true carcass value. This study was performed to evaluate the ability of the lamb vision system (LVS; Research Management Systems USA, Fort Collins, CO) to predict fabrication yields of lamb carcasses. Lamb carcasses (n = 246) were evaluated using LVS and hot carcass weight (HCW), as well as by USDA expert and on-line graders, before fabrication of carcass sides to either bone-in or boneless cuts. On-line whole number, expert whole-number, and expert nearest-tenth USDA yield grades and LVS + HCW estimates accounted for 53, 52, 58, and 60%, respectively, of the observed variability in boneless, saleable meat yields, and accounted for 56, 57, 62, and 62%, respectively, of the variation in bone-in, saleable meat yields. The LVS + HCW system predicted 77, 65, 70, and 87% of the variation in weights of boneless shoulders, racks, loins, and legs, respectively, and 85, 72, 75, and 86% of the variation in weights of bone-in shoulders, racks, loins, and legs, respectively. Addition of longissimus muscle area (REA), adjusted fat thickness (AFT), or both REA and AFT to LVS + HCW models resulted in improved prediction of boneless saleable meat yields by 5, 3, and 5 percentage points, respectively. Bone-in, saleable meat yield estimations were improved in predictive accuracy by 7.7, 6.6, and 10.1 percentage points, and in precision, when REA alone, AFT alone, or both REA and AFT, respectively, were added to the LVS + HCW output models. Use of LVS + HCW to predict boneless red meat yields of lamb carcasses was more accurate than use of current on-line whole-number, expert whole-number, or expert nearest-tenth USDA yield grades. Thus, LVS + HCW output, when used alone or in combination with AFT and/or REA, improved on-line estimation of boneless cut yields from lamb carcasses. The ability of LVS + HCW to predict yields of wholesale cuts suggests that LVS could be used as an objective

Atomic Oxygen Erosion Yield Predictive Tool for Spacecraft Polymers in Low Earth Orbit

Science.gov (United States)

Bank, Bruce A.; de Groh, Kim K.; Backus, Jane A.

2008-01-01

A predictive tool was developed to estimate the low Earth orbit (LEO) atomic oxygen erosion yield of polymers based on the results of the Polymer Erosion and Contamination Experiment (PEACE) Polymers experiment flown as part of the Materials International Space Station Experiment 2 (MISSE 2). The MISSE 2 PEACE experiment accurately measured the erosion yield of a wide variety of polymers and pyrolytic graphite. The 40 different materials tested were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The resulting erosion yield data was used to develop a predictive tool which utilizes chemical structure and physical properties of polymers that can be measured in ground laboratory testing to predict the in-space atomic oxygen erosion yield of a polymer. The properties include chemical structure, bonding information, density and ash content. The resulting predictive tool has a correlation coefficient of 0.914 when compared with actual MISSE 2 space data for 38 polymers and pyrolytic graphite. The intent of the predictive tool is to be able to make estimates of atomic oxygen erosion yields for new polymers without requiring expensive and time consumptive in-space testing.

A Comparison between Standard and Functional Clustering Methodologies: Application to Agricultural Fields for Yield Pattern Assessment

Directory of Open Access Journals (Sweden)

Simone Pascucci

2018-04-01

Full Text Available The recognition of spatial patterns within agricultural fields, presenting similar yield potential areas, stable through time, is very important for optimizing agricultural practices. This study proposes the evaluation of different clustering methodologies applied to multispectral satellite time series for retrieving temporally stable (constant patterns in agricultural fields, related to within-field yield spatial distribution. The ability of different clustering procedures for the recognition and mapping of constant patterns in fields of cereal crops was assessed. Crop vigor patterns, considered to be related to soils characteristics, and possibly indicative of yield potential, were derived by applying the different clustering algorithms to time series of Landsat images acquired on 94 agricultural fields near Rome (Italy. Two different approaches were applied and validated using Landsat 7 and 8 archived imagery. The first approach automatically extracts and calculates for each field of interest (FOI the Normalized Difference Vegetation Index (NDVI, then exploits the standard K-means clustering algorithm to derive constant patterns at the field level. The second approach applies novel clustering procedures directly to spectral reflectance time series, in particular: (1 standard K-means; (2 functional K-means; (3 multivariate functional principal components clustering analysis; (4 hierarchical clustering. The different approaches were validated through cluster accuracy estimates on a reference set of FOIs for which yield maps were available for some years. Results show that multivariate functional principal components clustering, with an a priori determination of the optimal number of classes for each FOI, provides a better accuracy than those of standard clustering algorithms. The proposed novel functional clustering methodologies are effective and efficient for constant pattern retrieval and can be used for a sustainable management of

SOFIA: An innovative setup to measure complete isotopic yield of fission fragments

Directory of Open Access Journals (Sweden)

Pellereau E.

2013-12-01

Full Text Available We performed an experiment dedicated to the accurate isotopic yield measurement of fission fragments over the whole range. SOFIA exploits the inverse kinematics technique: using heavy ion beams at relativistic energies, fission is induced by Coulomb excitation in a high-Z target. The fragments are emitted forward and both of them are identified in charge and mass. The setup will be presented, as well as preliminary spectra.

Effect of Aqueous Ammonia Soaking on the methane yield and composition of digested manure fibers applying different ammonia concentrations and treatment durations

DEFF Research Database (Denmark)

Mirtsou-Xanthopoulou, Chrysoula; Jurado, Esperanza; Skiadas, Ioannis

2014-01-01

, their economical profitable operation relies on increasing the methane yield from manure, and especially of its solid fraction which is not so easily degradable. In the present study, Aqueous Ammonia Soaking (AAS) in six different concentrations in ammonia (5%, 10%, 15%, 20%, 25% and 32%) and for 1, 3 and 5 days...... at 22°C was applied on digested fibers separated from the effluent of a manure-fed, full-scale anaerobic digester. A methane yield increase from 76% to 104% was achieved during the first series of experiments, while the difference in reagent concentration did not considerably affect the methane yield...... is a very promising treatment resulting to an overall increase of the methane yield of digested manure fibers from 76 to 265% depending on the conditions and the batch of digested fibers used (an even higher increase of 190-265% was achieved during the 2nd series of experiments, where different AAS...

Pointwise convergence of Fourier series

CERN Document Server

Arias de Reyna, Juan

2002-01-01

This book contains a detailed exposition of Carleson-Hunt theorem following the proof of Carleson: to this day this is the only one giving better bounds. It points out the motivation of every step in the proof. Thus the Carleson-Hunt theorem becomes accessible to any analyst.The book also contains the first detailed exposition of the fine results of Hunt, Sjölin, Soria, etc on the convergence of Fourier Series. Its final chapters present original material. With both Fefferman's proof and the recent one of Lacey and Thiele in print, it becomes more important than ever to understand and compare these two related proofs with that of Carleson and Hunt. These alternative proofs do not yield all the results of the Carleson-Hunt proof. The intention of this monograph is to make Carleson's proof accessible to a wider audience, and to explain its consequences for the pointwise convergence of Fourier series for functions in spaces near $äcal Lü^1$, filling a well-known gap in the literature.

Sequential series for nuclear reactions

International Nuclear Information System (INIS)

Izumo, Ko

1975-01-01

A new time-dependent treatment of nuclear reactions is given, in which the wave function of compound nucleus is expanded by a sequential series of the reaction processes. The wave functions of the sequential series form another complete set of compound nucleus at the limit Δt→0. It is pointed out that the wave function is characterized by the quantities: the number of degrees of freedom of motion n, the period of the motion (Poincare cycle) tsub(n), the delay time t sub(nμ) and the relaxation time tausub(n) to the equilibrium of compound nucleus, instead of the usual quantum number lambda, the energy eigenvalue Esub(lambda) and the total width GAMMAsub(lambda) of resonance levels, respectively. The transition matrix elements and the yields of nuclear reactions also become the functions of time given by the Fourier transform of the usual ones. The Poincare cycles of compound nuclei are compared with the observed correlations among resonance levels, which are about 10 -17 --10 -16 sec for medium and heavy nuclei and about 10 -20 sec for the intermediate resonances. (auth.)

Yield and dimensional quality of sawnwood in Guantanamo

Directory of Open Access Journals (Sweden)

Ibian Leyva Miguel

2017-12-01

Full Text Available The paper was carried out in the mobile sawmills LT 40 Yammar and Pekín of the Integral Military Farm Disembark by Duaba and the fixed sawmill of Cayo Güin branded Armentía of the Baracoa Agroforestry Company between the months of November of the 2014 to December of 2015 with the aim of improving the yield and dimensional quality of the lumber of Pinus cubensis Griseb. With this as main objective, the quality of the raw material used (long, thick, conicity, ovality, eccentricity and curvature of the shaft was analyzed. The yield was through a representative sampling of 132 logs distributed in the different sawmills and for dimensional quality, 100 pieces. As result, was observed that the raw material used was homogeneous in the diameter of the logs and the defect of the wood in the three sawmills, but in the Cayo Güín site, the logs were of greater dimensions. The Yammar and Perkin sawmills have an average yield of 70% higher than the one obtained in Cayo Güin where the result was of 55.5%. Mobile sawmills have greater dimensional control of sawn timber due to lower variation of the total process, Nonetheless, is accurate to state that the sawing system in the Cayo Güin establishment is out of control.

Building Chaotic Model From Incomplete Time Series

Science.gov (United States)

Siek, Michael; Solomatine, Dimitri

2010-05-01

and missing value estimates; and (2) the accuracy of the built chaotic model predictions. The model results indicate that the proposed methods are able to build a chaotic model from incomplete time series and to provide reliable and accurate predictions.

Multiple linear regression and artificial neural networks for delta-endotoxin and protease yields modelling of Bacillus thuringiensis.

Science.gov (United States)

Ennouri, Karim; Ben Ayed, Rayda; Triki, Mohamed Ali; Ottaviani, Ennio; Mazzarello, Maura; Hertelli, Fathi; Zouari, Nabil

2017-07-01

The aim of the present work was to develop a model that supplies accurate predictions of the yields of delta-endotoxins and proteases produced by B. thuringiensis var. kurstaki HD-1. Using available medium ingredients as variables, a mathematical method, based on Plackett-Burman design (PB), was employed to analyze and compare data generated by the Bootstrap method and processed by multiple linear regressions (MLR) and artificial neural networks (ANN) including multilayer perceptron (MLP) and radial basis function (RBF) models. The predictive ability of these models was evaluated by comparison of output data through the determination of coefficient (R 2 ) and mean square error (MSE) values. The results demonstrate that the prediction of the yields of delta-endotoxin and protease was more accurate by ANN technique (87 and 89% for delta-endotoxin and protease determination coefficients, respectively) when compared with MLR method (73.1 and 77.2% for delta-endotoxin and protease determination coefficients, respectively), suggesting that the proposed ANNs, especially MLP, is a suitable new approach for determining yields of bacterial products that allow us to make more appropriate predictions in a shorter time and with less engineering effort.

Yield gap mapping as a support tool for risk management in agriculture

Science.gov (United States)

Lahlou, Ouiam; Imani, Yasmina; Slimani, Imane; Van Wart, Justin; Yang, Haishun

2016-04-01

The increasing frequency and magnitude of droughts in Morocco and the mounting losses from extended droughts in the agricultural sector emphasized the need to develop reliable and timely tools to manage drought and to mitigate resulting catastrophic damage. In 2011, Morocco launched a cereals multi-risk insurance with drought as the most threatening and the most frequent hazard in the country. However, and in order to assess the gap and to implement the more suitable compensation, it is essential to quantify the potential yield in each area. In collaboration with the University of Nebraska-Lincoln, a study is carried out in Morocco and aims to determine the yield potentials and the yield gaps in the different agro-climatic zones of the country. It fits into the large project: Global Yield Gap and Water Productivity Atlas: http://www.yieldgap.org/. The yield gap (Yg) is the magnitude and difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual yields, reached by farmers. World Food Studies (WOFOST), which is a Crop simulation mechanistic model, has been used for this purpose. Prior to simulations, reliable information about actual yields, weather data, crop management data and soil data have been collected in 7 Moroccan buffer zones considered, each, within a circle of 100 km around a weather station point, homogenously spread across the country and where cereals are widely grown. The model calibration was also carried out using WOFOST default varieties data. The map-based results represent a robust tool, not only for drought insurance organization, but for agricultural and agricultural risk management. Moreover, accurate and geospatially granular estimates of Yg and Yw will allow to focus on regions with largest unexploited yield gaps and greatest potential to close them, and consequently to improve food security in the country.

Inferring causality from noisy time series data

DEFF Research Database (Denmark)

Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian

2016-01-01

Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... and even causality direction in synchronized time-series and in the presence of intermediate coupling. We find that the presence of noise deterministically reduces the level of cross-mapping fidelity, while the convergence rate exhibits higher levels of robustness. Finally, we propose that controlled noise...

Effect of Integrated Nutrient Management on Yield and Yield ...

African Journals Online (AJOL)

Declining soil fertility is one of the major problems causing yield reduction of barley ... (VC) with inorganic NP on growth, yield and yield components of food barley. ... The experiments were laid out in a randomized complete block design with ...

Evaluation and compilation of fission product yields 1993

International Nuclear Information System (INIS)

England, T.R.; Rider, B.F.

1995-01-01

This document is the latest in a series of compilations of fission yield data. Fission yield measurements reported in the open literature and calculated charge distributions have been used to produce a recommended set of yields for the fission products. The original data with reference sources, and the recommended yields axe presented in tabular form. These include many nuclides which fission by neutrons at several energies. These energies include thermal energies (T), fission spectrum energies (F), 14 meV High Energy (H or HE), and spontaneous fission (S), in six sets of ten each. Set A includes U235T, U235F, U235HE, U238F, U238HE, Pu239T, Pu239F, Pu241T, U233T, Th232F. Set B includes U233F, U233HE, U236F, Pu239H, Pu240F, Pu241F, Pu242F, Th232H, Np237F, Cf252S. Set C includes U234F, U237F, Pu240H, U234HE, U236HE, Pu238F, Am241F, Am243F, Np238F, Cm242F. Set D includes Th227T, Th229T, Pa231F, Am241T, Am241H, Am242MT, Cm245T, Cf249T, Cf251T, Es254T. Set E includes Cf250S, Cm244S, Cm248S, Es253S, Fm254S, Fm255T, Fm256S, Np237H, U232T, U238S. Set F includes Cm243T, Cm246S, Cm243F, Cm244F, Cm246F, Cm248F, Pu242H, Np237T, Pu240T, and Pu242T to complete fission product yield evaluations for 60 fissioning systems in all. This report also serves as the primary documentation for the second evaluation of yields in ENDF/B-VI released in 1993

Evaluation and compilation of fission product yields 1993

Energy Technology Data Exchange (ETDEWEB)

England, T.R.; Rider, B.F.

1995-12-31

This document is the latest in a series of compilations of fission yield data. Fission yield measurements reported in the open literature and calculated charge distributions have been used to produce a recommended set of yields for the fission products. The original data with reference sources, and the recommended yields axe presented in tabular form. These include many nuclides which fission by neutrons at several energies. These energies include thermal energies (T), fission spectrum energies (F), 14 meV High Energy (H or HE), and spontaneous fission (S), in six sets of ten each. Set A includes U235T, U235F, U235HE, U238F, U238HE, Pu239T, Pu239F, Pu241T, U233T, Th232F. Set B includes U233F, U233HE, U236F, Pu239H, Pu240F, Pu241F, Pu242F, Th232H, Np237F, Cf252S. Set C includes U234F, U237F, Pu240H, U234HE, U236HE, Pu238F, Am241F, Am243F, Np238F, Cm242F. Set D includes Th227T, Th229T, Pa231F, Am241T, Am241H, Am242MT, Cm245T, Cf249T, Cf251T, Es254T. Set E includes Cf250S, Cm244S, Cm248S, Es253S, Fm254S, Fm255T, Fm256S, Np237H, U232T, U238S. Set F includes Cm243T, Cm246S, Cm243F, Cm244F, Cm246F, Cm248F, Pu242H, Np237T, Pu240T, and Pu242T to complete fission product yield evaluations for 60 fissioning systems in all. This report also serves as the primary documentation for the second evaluation of yields in ENDF/B-VI released in 1993.

Effects of diurnal temperature range and drought on wheat yield in Spain

Science.gov (United States)

Hernandez-Barrera, S.; Rodriguez-Puebla, C.; Challinor, A. J.

2017-07-01

This study aims to provide new insight on the wheat yield historical response to climate processes throughout Spain by using statistical methods. Our data includes observed wheat yield, pseudo-observations E-OBS for the period 1979 to 2014, and outputs of general circulation models in phase 5 of the Coupled Models Inter-comparison Project (CMIP5) for the period 1901 to 2099. In investigating the relationship between climate and wheat variability, we have applied the approach known as the partial least-square regression, which captures the relevant climate drivers accounting for variations in wheat yield. We found that drought occurring in autumn and spring and the diurnal range of temperature experienced during the winter are major processes to characterize the wheat yield variability in Spain. These observable climate processes are used for an empirical model that is utilized in assessing the wheat yield trends in Spain under different climate conditions. To isolate the trend within the wheat time series, we implemented the adaptive approach known as Ensemble Empirical Mode Decomposition. Wheat yields in the twenty-first century are experiencing a downward trend that we claim is a consequence of widespread drought over the Iberian Peninsula and an increase in the diurnal range of temperature. These results are important to inform about the wheat vulnerability in this region to coming changes and to develop adaptation strategies.

Determination of secondary electron yields from low pressure breakdown

International Nuclear Information System (INIS)

Maric, D; Zivanov, S.; Strinic, A.; Malovic, G.; Djuric, M.; Petrovic, Z. Lj.

2000-01-01

In order to model accurately the secondary yields in gas breakdown and collisional plasmas both the numerous processes discussed in related experiments must be included and also proper determination of γ (E/n) must be provided. In addition to the application of the correct ionization rate it is also essential to include the nonequilibrium region where electrons gain energy and achieve hydrodynamics equilibrium. For lower values of E/n, greater values of γ than those based on the literature data for αn(E/n) have been found, possibly due to existence of the photoelectric effects

Yield trends and yield gap analysis of major crops in the world

OpenAIRE

Hengsdijk, H.; Langeveld, J.W.A.

2009-01-01

This study aims to quantify the gap between current and potential yields of major crops in the world, and the production constraints that contribute to this yield gap. Using an expert-based evaluation of yield gaps and the literature, global and regional yields and yield trends of major crops are quantified, yield gaps evaluated by crop experts, current yield progress by breeding estimated, and different yield projections compared. Results show decreasing yield growth for wheat and rice, but ...

Equity yields

NARCIS (Netherlands)

Vrugt, E.; van Binsbergen, J.H.; Koijen, R.S.J.; Hueskes, W.

2013-01-01

We study a new data set of dividend futures with maturities up to ten years across three world regions: the US, Europe, and Japan. We use these asset prices to construct equity yields, analogous to bond yields. We decompose the equity yields to obtain a term structure of expected dividend growth

On generalizations of the series of Taylor, Lagrange, Laurent and Teixeira

Directory of Open Access Journals (Sweden)

L. M. B. C. Campos

1990-01-01

Full Text Available The classical theorems of Taylor, Lagrange, Laurent and Teixeira, are extended from the representation of a complex function F(z, to its derivative F(ν(z of complex order ν, understood as either a ‘Liouville’ (1832 or a ‘Rieman (1847’ differintegration (Campos 1984, 1985; these results are distinct from, and alternative to, other extensions of Taylor's series using differintegrations (Osler 1972, Lavoie & Osler & Tremblay 1976. We consider a complex function F(z, which is analytic (has an isolated singularity at ζ, and expand its derivative of complex order F(ν(z, in an ascending (ascending-descending series of powers of an auxiliary function f(z, yielding the generalized Teixeira (Lagrange series, which includes, for f(z=z−ζ, the generalized Taylor (Laurent series. The generalized series involve non-integral powers and/or coefficients evaluated by fractional derivatives or integrals, except in the case ν=0, when the classical theorems of Taylor (1715, Lagrange (1770, Laurent (1843 and Teixeira (1900 are regained. As an application, these generalized series can be used to generate special functions with complex parameters (Campos 1986, e.g., the Hermite and Bessel types.

Online evaluation of a commercial video image analysis system (Computer Vision System) to predict beef carcass red meat yield and for augmenting the assignment of USDA yield grades. United States Department of Agriculture.

Science.gov (United States)

Cannell, R C; Belk, K E; Tatum, J D; Wise, J W; Chapman, P L; Scanga, J A; Smith, G C

2002-05-01

Objective quantification of differences in wholesale cut yields of beef carcasses at plant chain speeds is important for the application of value-based marketing. This study was conducted to evaluate the ability of a commercial video image analysis system, the Computer Vision System (CVS) to 1) predict commercially fabricated beef subprimal yield and 2) augment USDA yield grading, in order to improve accuracy of grade assessment. The CVS was evaluated as a fully installed production system, operating on a full-time basis at chain speeds. Steer and heifer carcasses (n = 296) were evaluated using CVS, as well as by USDA expert and online graders, before the fabrication of carcasses into industry-standard subprimal cuts. Expert yield grade (YG), online YG, CVS estimated carcass yield, and CVS measured ribeye area in conjunction with expert grader estimates of the remaining YG factors (adjusted fat thickness, percentage of kidney-pelvic-heart fat, hot carcass weight) accounted for 67, 39, 64, and 65% of the observed variation in fabricated yields of closely trimmed subprimals. The dual component CVS predicted wholesale cut yields more accurately than current online yield grading, and, in an augmentation system, CVS ribeye measurement replaced estimated ribeye area in determination of USDA yield grade, and the accuracy of cutability prediction was improved, under packing plant conditions and speeds, to a level close to that of expert graders applying grades at a comfortable rate of speed offline.

Effects of Adopting Different Kinds of Collecting Method for Years on Film Residual Coefficient and Maize Yields

OpenAIRE

TANG Wen-xue; MA Zhong-ming; WEI Tao

2017-01-01

Wide usage of mulching technology has increased crop yields, but the large amounts of mulching film residue resulting from widespread use of plastic film in China has brought about a series of pollution hazards. Based on a 4-year (2011-2014) long-term experiment, the effects of different kinds of collecting mothod (zero plastic film residues, conventional plastic film residues, whole plastic film residues remainded) on plastic film residues, residual coefficient and maize yield were explored....

Documentation of the U.S. Geological Survey Oceanographic Time-Series Measurement Database

Science.gov (United States)

Montgomery, Ellyn T.; Martini, Marinna A.; Lightsom, Frances L.; Butman, Bradford

2008-01-02

The U.S. Geological Survey (USGS) Oceanographic Time-Series Data Collection (previously named the USGS Oceanographic Time-Series Measurement Database) contains oceanographic observations made as part of studies designed to increase understanding of sediment transport processes and associated dynamics. Analysis of these data has contributed to more accurate prediction of the movement and fate of sediments and other suspended materials in the coastal ocean. The measurements were collected primarily by investigators at the USGS Woods Hole Coastal and Marine Science Center (WHCMSC) and colleagues, beginning in 1975. Most of the field experiments were carried out on the U.S. continental shelf and slope.

An advection-based model to increase the temporal resolution of PIV time series.

Science.gov (United States)

Scarano, Fulvio; Moore, Peter

A numerical implementation of the advection equation is proposed to increase the temporal resolution of PIV time series. The method is based on the principle that velocity fluctuations are transported passively, similar to Taylor's hypothesis of frozen turbulence . In the present work, the advection model is extended to unsteady three-dimensional flows. The main objective of the method is that of lowering the requirement on the PIV repetition rate from the Eulerian frequency toward the Lagrangian one. The local trajectory of the fluid parcel is obtained by forward projection of the instantaneous velocity at the preceding time instant and backward projection from the subsequent time step. The trajectories are approximated by the instantaneous streamlines, which yields accurate results when the amplitude of velocity fluctuations is small with respect to the convective motion. The verification is performed with two experiments conducted at temporal resolutions significantly higher than that dictated by Nyquist criterion. The flow past the trailing edge of a NACA0012 airfoil closely approximates frozen turbulence , where the largest ratio between the Lagrangian and Eulerian temporal scales is expected. An order of magnitude reduction of the needed acquisition frequency is demonstrated by the velocity spectra of super-sampled series. The application to three-dimensional data is made with time-resolved tomographic PIV measurements of a transitional jet. Here, the 3D advection equation is implemented to estimate the fluid trajectories. The reduction in the minimum sampling rate by the use of super-sampling in this case is less, due to the fact that vortices occurring in the jet shear layer are not well approximated by sole advection at large time separation. Both cases reveal that the current requirements for time-resolved PIV experiments can be revised when information is poured from space to time . An additional favorable effect is observed by the analysis in the

Visibility graphlet approach to chaotic time series

Energy Technology Data Exchange (ETDEWEB)

Mutua, Stephen [Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China); Computer Science Department, Masinde Muliro University of Science and Technology, P.O. Box 190-50100, Kakamega (Kenya); Gu, Changgui, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn; Yang, Huijie, E-mail: gu-changgui@163.com, E-mail: hjyang@ustc.edu.cn [Business School, University of Shanghai for Science and Technology, Shanghai 200093 (China)

2016-05-15

Many novel methods have been proposed for mapping time series into complex networks. Although some dynamical behaviors can be effectively captured by existing approaches, the preservation and tracking of the temporal behaviors of a chaotic system remains an open problem. In this work, we extended the visibility graphlet approach to investigate both discrete and continuous chaotic time series. We applied visibility graphlets to capture the reconstructed local states, so that each is treated as a node and tracked downstream to create a temporal chain link. Our empirical findings show that the approach accurately captures the dynamical properties of chaotic systems. Networks constructed from periodic dynamic phases all converge to regular networks and to unique network structures for each model in the chaotic zones. Furthermore, our results show that the characterization of chaotic and non-chaotic zones in the Lorenz system corresponds to the maximal Lyapunov exponent, thus providing a simple and straightforward way to analyze chaotic systems.

Regional crop gross primary production and yield estimation using fused Landsat-MODIS data

Science.gov (United States)

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, pcrop 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.

Laser fluorescence on radio-active isotopes produced in very low yield

International Nuclear Information System (INIS)

Dancy, D.E.; Billowes, J.; Grant, I.S.; Evans, D.E.; Griffith, J.A.R.; Wells, S.A.; Eastham, D.A.; Groves, J.; Smith, J.R.H.; Tolfree, D.W.L.; Walker, P.M.

1990-01-01

Fast particle-photon coincidence techniques, developed at Daresbury with strontium isotopes, allow ultra-sensitive laser fluorescence spectroscopy of beams of radio-active isotopes which can only be produced in very low yields. The technique has now been applied to neutron-deficient barium isotopes down to 120 Ba. From measured hyperfine splitting and isotope shifts, nuclear moments and changes in mean square radii have been determined. The work has revealed an abrupt increase in the mean square radius for 121 Ba large enough to disrupt the systematic staggering of nuclear size seen for the series. In a recent experiment an isomeric state of 127 Ba with a half-life of about 2 seconds has been produced in a very low yield; nevertheless we have succeeded in obtaining a fluorescence spectrum. (orig.)

Fast and accurate implementation of Fourier spectral approximations of nonlocal diffusion operators and its applications

International Nuclear Information System (INIS)

Du, Qiang; Yang, Jiang

2017-01-01

This work is concerned with the Fourier spectral approximation of various integral differential equations associated with some linear nonlocal diffusion and peridynamic operators under periodic boundary conditions. For radially symmetric kernels, the nonlocal operators under consideration are diagonalizable in the Fourier space so that the main computational challenge is on the accurate and fast evaluation of their eigenvalues or Fourier symbols consisting of possibly singular and highly oscillatory integrals. For a large class of fractional power-like kernels, we propose a new approach based on reformulating the Fourier symbols both as coefficients of a series expansion and solutions of some simple ODE models. We then propose a hybrid algorithm that utilizes both truncated series expansions and high order Runge–Kutta ODE solvers to provide fast evaluation of Fourier symbols in both one and higher dimensional spaces. It is shown that this hybrid algorithm is robust, efficient and accurate. As applications, we combine this hybrid spectral discretization in the spatial variables and the fourth-order exponential time differencing Runge–Kutta for temporal discretization to offer high order approximations of some nonlocal gradient dynamics including nonlocal Allen–Cahn equations, nonlocal Cahn–Hilliard equations, and nonlocal phase-field crystal models. Numerical results show the accuracy and effectiveness of the fully discrete scheme and illustrate some interesting phenomena associated with the nonlocal models.

Identification of Dynamic Loads Based on Second-Order Taylor-Series Expansion Method

Directory of Open Access Journals (Sweden)

Xiaowang Li

2016-01-01

Full Text Available A new method based on the second-order Taylor-series expansion is presented to identify the structural dynamic loads in the time domain. This algorithm expresses the response vectors as Taylor-series approximation and then a series of formulas are deduced. As a result, an explicit discrete equation which associates system response, system characteristic, and input excitation together is set up. In a multi-input-multi-output (MIMO numerical simulation study, sinusoidal excitation and white noise excitation are applied on a cantilever beam, respectively, to illustrate the effectiveness of this algorithm. One also makes a comparison between the new method and conventional state space method. The results show that the proposed method can obtain a more accurate identified force time history whether the responses are polluted by noise or not.

Refined composite multiscale weighted-permutation entropy of financial time series

Science.gov (United States)

Zhang, Yongping; Shang, Pengjian

2018-04-01

For quantifying the complexity of nonlinear systems, multiscale weighted-permutation entropy (MWPE) has recently been proposed. MWPE has incorporated amplitude information and been applied to account for the multiple inherent dynamics of time series. However, MWPE may be unreliable, because its estimated values show large fluctuation for slight variation of the data locations, and a significant distinction only for the different length of time series. Therefore, we propose the refined composite multiscale weighted-permutation entropy (RCMWPE). By comparing the RCMWPE results with other methods' results on both synthetic data and financial time series, RCMWPE method shows not only the advantages inherited from MWPE but also lower sensitivity to the data locations, more stable and much less dependent on the length of time series. Moreover, we present and discuss the results of RCMWPE method on the daily price return series from Asian and European stock markets. There are significant differences between Asian markets and European markets, and the entropy values of Hang Seng Index (HSI) are close to but higher than those of European markets. The reliability of the proposed RCMWPE method has been supported by simulations on generated and real data. It could be applied to a variety of fields to quantify the complexity of the systems over multiple scales more accurately.

CT-guided procedures: evaluation of a phantom system to teach accurate needle placement

International Nuclear Information System (INIS)

Dimmick, S.; Jones, M.; Challen, J.; Iedema, J.; Wattuhewa, U.; Coucher, J.

2007-01-01

Aim: To evaluate the use of a phantom system to help teach the basic techniques of accurate CT-guided needle placement, thereby avoiding the risks associated with teaching on patients. Materials and Methods: Gelatine phantoms with five, 1.9 cm embedded spherical wooden targets were constructed. Four trainee operators performed 15 simulated biopsy procedures on the targets (series one) and repeated identical procedures 2 weeks later (series two). Statistical analysis of accuracy of needle placement and subject confidence were performed. Results: Significant sequential improvement in axial plane angular error was noted with the average error decreasing by 0.33 degrees after every five procedures performed (95% CI: -0.58 to -0.08, p = 0.01). Operator confidence indicated significant improvement both within each series and from series one to series two (95% CI: 0.08 to 1.17, p = 0.025 and 95% CI: 0.00 to 0.58, p = 0.05) respectively. However, variability in operator performance made statistically significant improvement in other variables unproven. Conclusion: Despite the study comprising a relatively small number of participants and procedures, it clearly demonstrated the effectiveness of teaching operators to perform CT-guided procedures using a phantom system. Needle placement accuracy significantly improved, with a reduction in axial angular error, and improved operator confidence without the risks associated with training on patients. Three of the operators in this study had never performed a CT-guided procedure previously, and their proficiency, after a relatively short but intense period of training, was impressive. The use of phantoms should be considered routinely for basic training of CT-guided needle placement

An accurate algorithm to calculate the Hurst exponent of self-similar processes

International Nuclear Information System (INIS)

Fernández-Martínez, M.; Sánchez-Granero, M.A.; Trinidad Segovia, J.E.; Román-Sánchez, I.M.

2014-01-01

In this paper, we introduce a new approach which generalizes the GM2 algorithm (introduced in Sánchez-Granero et al. (2008) [52]) as well as fractal dimension algorithms (FD1, FD2 and FD3) (first appeared in Sánchez-Granero et al. (2012) [51]), providing an accurate algorithm to calculate the Hurst exponent of self-similar processes. We prove that this algorithm performs properly in the case of short time series when fractional Brownian motions and Lévy stable motions are considered. We conclude the paper with a dynamic study of the Hurst exponent evolution in the S and P500 index stocks. - Highlights: • We provide a new approach to properly calculate the Hurst exponent. • This generalizes FD algorithms and GM2, introduced previously by the authors. • This method (FD4) results especially appropriate for short time series. • FD4 may be used in both unifractal and multifractal contexts. • As an empirical application, we show that S and P500 stocks improved their efficiency

An accurate algorithm to calculate the Hurst exponent of self-similar processes

Energy Technology Data Exchange (ETDEWEB)

Fernández-Martínez, M., E-mail: fmm124@ual.es [Department of Mathematics, Faculty of Science, Universidad de Almería, 04120 Almería (Spain); Sánchez-Granero, M.A., E-mail: misanche@ual.es [Department of Mathematics, Faculty of Science, Universidad de Almería, 04120 Almería (Spain); Trinidad Segovia, J.E., E-mail: jetrini@ual.es [Department of Accounting and Finance, Faculty of Economics and Business, Universidad de Almería, 04120 Almería (Spain); Román-Sánchez, I.M., E-mail: iroman@ual.es [Department of Accounting and Finance, Faculty of Economics and Business, Universidad de Almería, 04120 Almería (Spain)

2014-06-27

In this paper, we introduce a new approach which generalizes the GM2 algorithm (introduced in Sánchez-Granero et al. (2008) [52]) as well as fractal dimension algorithms (FD1, FD2 and FD3) (first appeared in Sánchez-Granero et al. (2012) [51]), providing an accurate algorithm to calculate the Hurst exponent of self-similar processes. We prove that this algorithm performs properly in the case of short time series when fractional Brownian motions and Lévy stable motions are considered. We conclude the paper with a dynamic study of the Hurst exponent evolution in the S and P500 index stocks. - Highlights: • We provide a new approach to properly calculate the Hurst exponent. • This generalizes FD algorithms and GM2, introduced previously by the authors. • This method (FD4) results especially appropriate for short time series. • FD4 may be used in both unifractal and multifractal contexts. • As an empirical application, we show that S and P500 stocks improved their efficiency.

Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

Directory of Open Access Journals (Sweden)

Nahuel R. Peralta

2016-10-01

Full Text Available A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn yield at different sites within a field. A test was conducted on yield monitor data and RapidEye satellite imagery obtained for 22 cornfields located in five different counties (Clay, Dickinson, Rice, Saline, and Washington of Kansas (total of 457 ha. Three basic tests were conducted on the data: (1 spatial dependence on each of the yield and vegetation indices (VIs using Moran’s I test; (2 model selection for the relationship between imagery data and actual yield using ordinary least square regression (OLS and spatial econometric (SPL models; and (3 model validation for yield forecasting purposes. Spatial autocorrelation analysis (Moran’s I test for both yield and VIs (red edge NDVI = NDVIre, normalized difference vegetation index = NDVIr, SRre = red-edge simple ratio, near infrared = NIR and green-NDVI = NDVIG was tested positive and statistically significant for most of the fields (p < 0.05, except for one. Inclusion of spatial adjustment to model improved the model fit on most fields as compared to OLS models, with the spatial adjustment coefficient significant for half of the fields studied. When selected models were used for prediction to validate dataset, a striking similarity (RMSE = 0.02 was obtained between predicted and observed yield within a field. Yield maps could assist implementing more effective site-specific management tools and could be utilized as a proxy of yield monitor data. In summary, high-resolution satellite imagery data can be reasonably used to forecast yield via utilization of models that include spatial adjustment to

Refinement and evaluation of the Massachusetts firm-yield estimator model version 2.0

Science.gov (United States)

Levin, Sara B.; Archfield, Stacey A.; Massey, Andrew J.

2011-01-01

The firm yield is the maximum average daily withdrawal that can be extracted from a reservoir without risk of failure during an extended drought period. Previously developed procedures for determining the firm yield of a reservoir were refined and applied to 38 reservoir systems in Massachusetts, including 25 single- and multiple-reservoir systems that were examined during previous studies and 13 additional reservoir systems. Changes to the firm-yield model include refinements to the simulation methods and input data, as well as the addition of several scenario-testing capabilities. The simulation procedure was adapted to run at a daily time step over a 44-year simulation period, and daily streamflow and meteorological data were compiled for all the reservoirs for input to the model. Another change to the model-simulation methods is the adjustment of the scaling factor used in estimating groundwater contributions to the reservoir. The scaling factor is used to convert the daily groundwater-flow rate into a volume by multiplying the rate by the length of reservoir shoreline that is hydrologically connected to the aquifer. Previous firm-yield analyses used a constant scaling factor that was estimated from the reservoir surface area at full pool. The use of a constant scaling factor caused groundwater flows during periods when the reservoir stage was very low to be overestimated. The constant groundwater scaling factor used in previous analyses was replaced with a variable scaling factor that is based on daily reservoir stage. This change reduced instability in the groundwater-flow algorithms and produced more realistic groundwater-flow contributions during periods of low storage. Uncertainty in the firm-yield model arises from many sources, including errors in input data. The sensitivity of the model to uncertainty in streamflow input data and uncertainty in the stage-storage relation was examined. A series of Monte Carlo simulations were performed on 22 reservoirs

CORRELATION ANALYSIS OF AGRONOMIC CHARACTERS AND GRAIN YIELD OF RICE FOR TIDAL SWAMP AREAS

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Aris Hairmansis

2013-05-01

Full Text Available Development of rice varieties for tidal swamp areas is emphasized on the improvement of rice yield potential in specific environment. However, grain yield is a complex trait and highly dependent on the other agronomic characters; while information related to the relationship between agronomic characters and grain yield in the breeding program particularly for tidal swamp areas is very limited. The objective of this study was to investigate relationship between agronomic characters and grain yield of rice as a basis for selection of high yielding rice varieties for tidal swamp areas. Agronomic characters and grain yield of nine advanced rice breeding lines and two rice varieties were evaluated in a series of experiments in tidal swamp areas, Karang Agung Ulu Village, Banyuasin, South Sumatra, for four cropping seasons in dry season (DS 2005, wet season (WS 2005/2006, DS 2006, and DS 2007. Result from path analysis revealed that the following characters had positive direct effect on grain yield, i.e. number of productive tillers per hill (p = 0.356, number of filled grains per panicle (p = 0.544, and spikelet fertility (p = 0.215. Plant height had negative direct effect (p = -0.332 on grain yield, while maturity, number of spikelets per panicle, and 1000-grain weight showed negligible effect on rice grain yield. Present study suggests that indirect selection of high yielding tidal swamp rice can be done by selecting breeding lines which have many product tive tillers, dense filled grains, and high spikelet fertility.

Fully stripped heavy ion yield vs energy for Xe and Au ions

International Nuclear Information System (INIS)

Thieberger, P.; Wegner, H.E.; Alonzo, J.; Gould, H.; Anholt, R.E.; Meyerhof, W.E.

1985-01-01

The Bevalac is now capable of accelerating U-238 ions to approximately 1 GeV/amu and measurements have shown that fully stripped U-238 ions are produced with good yield at these energies. However, knowing the stripping yields at different energies for U-238 does not allow an accurate prediction for other, lower Z projectiles. Consequently, extensive stripping yield measurements were made for Au-197 and Xe-139 ions. In addition to the stripping measurements from the direct Bevalac beam, pickup measurements were also made with specially prepared bare, one electron, and two electron ions. Since many research groups are considering heavy ion storage rings and/or synchrotrons, the pickup cross section for bare ions is important to estimate beam lifetime in terms of the average machine vacuum. Since the Mylar target provides a pickup probability similar to air, a preliminary analysis of the Xe 54+ and U 92+ data are presented along with predictions for other ions ranging down to Fe 26+ . 11 refs., 3 figs., 1 tab

Fully stripped heavy ion yield vs energy for Xe and Au ions

Energy Technology Data Exchange (ETDEWEB)

Thieberger, P.; Wegner, H.E.; Alonzo, J.; Gould, H.; Anholt, R.E.; Meyerhof, W.E.

1985-01-01

The Bevalac is now capable of accelerating U-238 ions to approximately 1 GeV/amu and measurements have shown that fully stripped U-238 ions are produced with good yield at these energies. However, knowing the stripping yields at different energies for U-238 does not allow an accurate prediction for other, lower Z projectiles. Consequently, extensive stripping yield measurements were made for Au-197 and Xe-139 ions. In addition to the stripping measurements from the direct Bevalac beam, pickup measurements were also made with specially prepared bare, one electron, and two electron ions. Since many research groups are considering heavy ion storage rings and/or synchrotrons, the pickup cross section for bare ions is important to estimate beam lifetime in terms of the average machine vacuum. Since the Mylar target provides a pickup probability similar to air, a preliminary analysis of the Xe/sup 54 +/ and U/sup 92 +/ data are presented along with predictions for other ions ranging down to Fe/sup 26 +/. 11 refs., 3 figs., 1 tab.

Uncertainty in Simulating Wheat Yields Under Climate Change

Science.gov (United States)

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.;

Resummation of divergent perturbation series: Application to the vibrational states of H2CO molecule.

Science.gov (United States)

Duchko, A N; Bykov, A D

2015-10-21

Large-order Rayleigh-Schrödinger perturbation theory (RSPT) is applied to the calculation of anharmonic vibrational energy levels of H2CO molecule. We use the model of harmonic oscillators perturbed by anharmonic terms of potential energy. Since the perturbation series typically diverge due to strong couplings, we apply the algebraic approximation technique because of its effectiveness shown earlier by Goodson and Sergeev [J. Chem. Phys. 110, 8205 (1999); ibid. 124, 094111 (2006)] and in our previous articles [A. D. Bykov et al. Opt. Spectrosc. 114, 396 (2013); ibid. 116, 598 (2014)]. To facilitate the resummation of terms contributing to perturbed states, when resonance mixing between states is especially strong and perturbation series diverge very quick, we used repartition of the Hamiltonian by shifting the normal mode frequencies. Energy levels obtained by algebraic approximants were compared with the results of variational calculation. It was found that for low energy states (up to ∼5000 cm(-1)), algebraic approximants gave accurate values of energy levels, which were in excellent agreement with the variational method. For highly excited states, strong and multiple resonances complicate series resummation, but a suitable change of normal mode frequencies allows one to reduce the resonance mixing and to get accurate energy levels. The theoretical background of the problem of RSPT series divergence is discussed along with its numerical analysis. For these purposes, the vibrational energy is considered as a function of a complex perturbation parameter. Layout and classification of its singularities allow us to model the asymptotic behavior of the perturbation series and prove the robustness of the algorithm.

A comparison of various Gibbs energy dissipation correlations for predicting microbial growth yields

Energy Technology Data Exchange (ETDEWEB)

Liu, J.-S. [Laboratory of Chemical and Biochemical Engineering, Swiss Federal Institute of Technology, EPFL, CH-1015 Lausanne (Switzerland); Vojinovic, V. [Laboratory of Chemical and Biochemical Engineering, Swiss Federal Institute of Technology, EPFL, CH-1015 Lausanne (Switzerland); Patino, R. [Cinvestav-Merida, Departamento de Fisica Aplicada, Km. 6 carretera antigua a Progreso, AP 73 Cordemex, 97310 Merida, Yucatan (Mexico); Maskow, Th. [UFZ Centre for Environmental Research, Department of Environmental Microbiology, Permoserstrasse 15, D-04318 Leipzig (Germany); Stockar, U. von [Laboratory of Chemical and Biochemical Engineering, Swiss Federal Institute of Technology, EPFL, CH-1015 Lausanne (Switzerland)]. E-mail: urs.vonStockar@epfl.ch

2007-06-25

Thermodynamic analysis may be applied in order to predict microbial growth yields roughly, based on an empirical correlation of the Gibbs energy of the overall growth reaction or Gibbs energy dissipation. Due to the well-known trade-off between high biomass yield and high Gibbs energy dissipation necessary for fast growth, an optimal range of Gibbs energy dissipation exists and it can be correlated to physical characteristics of the growth substrates. A database previously available in the literature has been extended significantly in order to test such correlations. An analysis of the relationship between biomass yield and Gibbs energy dissipation reveals that one does not need a very precise estimation of the latter to predict the former roughly. Approximating the Gibbs energy dissipation with a constant universal value of -500 kJ C-mol{sup -1} of dry biomass grown predicts many experimental growth yields nearly as well as a carefully designed, complex correlation available from the literature, even though a number of predictions are grossly out of range. A new correlation for Gibbs energy dissipation is proposed which is just as accurate as the complex literature correlation despite its dramatically simpler structure.

A comparison of various Gibbs energy dissipation correlations for predicting microbial growth yields

International Nuclear Information System (INIS)

Liu, J.-S.; Vojinovic, V.; Patino, R.; Maskow, Th.; Stockar, U. von

2007-01-01

Thermodynamic analysis may be applied in order to predict microbial growth yields roughly, based on an empirical correlation of the Gibbs energy of the overall growth reaction or Gibbs energy dissipation. Due to the well-known trade-off between high biomass yield and high Gibbs energy dissipation necessary for fast growth, an optimal range of Gibbs energy dissipation exists and it can be correlated to physical characteristics of the growth substrates. A database previously available in the literature has been extended significantly in order to test such correlations. An analysis of the relationship between biomass yield and Gibbs energy dissipation reveals that one does not need a very precise estimation of the latter to predict the former roughly. Approximating the Gibbs energy dissipation with a constant universal value of -500 kJ C-mol -1 of dry biomass grown predicts many experimental growth yields nearly as well as a carefully designed, complex correlation available from the literature, even though a number of predictions are grossly out of range. A new correlation for Gibbs energy dissipation is proposed which is just as accurate as the complex literature correlation despite its dramatically simpler structure

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

Science.gov (United States)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

Yield, yield components and dry matter digestibility of alfalfa experimental populations

Directory of Open Access Journals (Sweden)

Katić Slobodan

2010-01-01

Full Text Available Alfalfa is the most important forage crop grown in the temperate regions. It is cultivated for production of vegetative aerial mass used fresh or as hay, and recently as haylage and silage. In many centres worldwide, efforts are made to breed and create new alfalfa cultivars with both higher yields and of higher nutritional value. The aim of this paper was to determine yield and digestibility of 12 experimental populations of alfalfa, and to compare their results to the yields of well-known domestic alfalfa commercial cultivars. The results show significant differences in yield of green forage and dry matter among alfalfa populations, as well as in yield components, height, proportion of leaves in yield and growth rate (tab. 1, 2 and 3. Differences between in vitro digestible dry matter (% and yields of in vitro digestible dry matter (t ha-1 were also significant (tab. 5 and 6. Yield and quality of experimental populations were at the same level or higher than of control cultivars. Synthetic SINUSA exceeded the control cutivars (NS Mediana ZMS V and Banat VS in yield and quality of dry matter. .

Added-values of high spatiotemporal remote sensing data in crop yield estimation

Science.gov (United States)

Gao, F.; Anderson, M. C.

2017-12-01

Timely and accurate estimation of crop yield before harvest is critical for food market and administrative planning. Remote sensing derived parameters have been used for estimating crop yield by using either empirical or crop growth models. The uses of remote sensing vegetation index (VI) in crop yield modeling have been typically evaluated at regional and country scales using coarse spatial resolution (a few hundred to kilo-meters) data or assessed over a small region at field level using moderate resolution spatial resolution data (10-100m). Both data sources have shown great potential in capturing spatial and temporal variability in crop yield. However, the added value of data with both high spatial and temporal resolution data has not been evaluated due to the lack of such data source with routine, global coverage. In recent years, more moderate resolution data have become freely available and data fusion approaches that combine data acquired from different spatial and temporal resolutions have been developed. These make the monitoring crop condition and estimating crop yield at field scale become possible. Here we investigate the added value of the high spatial and temporal VI for describing variability of crop yield. The explanatory ability of crop yield based on high spatial and temporal resolution remote sensing data was evaluated in a rain-fed agricultural area in the U.S. Corn Belt. Results show that the fused Landsat-MODIS (high spatial and temporal) VI explains yield variability better than single data source (Landsat or MODIS alone), with EVI2 performing slightly better than NDVI. The maximum VI describes yield variability better than cumulative VI. Even though VI is effective in explaining yield variability within season, the inter-annual variability is more complex and need additional information (e.g. weather, water use and management). Our findings augment the importance of high spatiotemporal remote sensing data and supports new moderate

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

Science.gov (United States)

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

Science.gov (United States)

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Slope Controls Grain Yield and Climatic Yield in Mountainous Yunnan province, China

Science.gov (United States)

Duan, X.; Rong, L.; Gu, Z.; Feng, D.

2017-12-01

Mountainous regions are increasingly vulnerable to food insecurity because of limited arable land, growing population pressure, and climate change. Development of sustainable mountain agriculture will require an increased understanding of the effects of environmental factors on grain and climatic yields. The objective of this study was to explore the relationships between actual grain yield, climatic yield, and environmental factors in a mountainous region in China. We collected data on the average grain yield per unit area in 119 counties in Yunnan province from 1985 to 2012, and chose 17 environmental factors for the same period. Our results showed that actual grain yield ranged from 1.43 to 6.92 t·ha-1, and the climatic yield ranged from -0.15 to -0.01 t·ha-1. Lower climatic yield but higher grain yield was generally found in central areas and at lower slopes and elevations in the western and southwestern counties of Yunnan province. Higher climatic yield but lower grain yield were found in northwestern parts of Yunnan province on steep slopes. Annual precipation and temperature had a weak influence on the climatic yield. Slope explained 44.62 and 26.29% of the variation in grain yield and climatic yield. The effects of topography on grain and climatic yields were greater than climatic factors. Slope was the most important environmental variable for the variability in climatic and grain yields in the mountainous Yunnan province due to the highly heterogeneous topographic conditions. Conversion of slopes to terraces in areas with higher climatic yields is an effective way to maintain grain production in response to climate variability. Additionally, soil amendments and soil and water conservation measures should be considered to maintain soil fertility and aid in sustainable development in central areas, and in counties at lower slopes and elevations in western and southwestern Yunnan province.

Enumeration of self-avoiding walks on the square lattice

International Nuclear Information System (INIS)

Jensen, Iwan

2004-01-01

We describe a new algorithm for the enumeration of self-avoiding walks on the square lattice. Using up to 128 processors on a HP Alpha server cluster we have enumerated the number of self-avoiding walks on the square lattice to length 71. Series for the metric properties of mean-square end-to-end distance, mean-square radius of gyration and mean-square distance of monomers from the end points have been derived to length 59. An analysis of the resulting series yields accurate estimates of the critical exponents γ and ν confirming predictions of their exact values. Likewise we obtain accurate amplitude estimates yielding precise values for certain universal amplitude combinations. Finally we report on an analysis giving compelling evidence that the leading non-analytic correction-to-scaling exponent Δ 1 = 3/2

Evidence for a climate signal in trends of global crop yield variability over the past 50 years

International Nuclear Information System (INIS)

Osborne, T M; Wheeler, T R

2013-01-01

Low variability of crop production from year to year is desirable for many reasons, including reduced income risk and stability of supplies. Therefore, it is important to understand the nature of yield variability, whether it is changing through time, and how it varies between crops and regions. Previous studies have shown that national crop yield variability has changed in the past, with the direction and magnitude dependent on crop type and location. Whilst such studies acknowledge the importance of climate variability in determining yield variability, it has been assumed that its magnitude and its effect on crop production have not changed through time and, hence, that changes to yield variability have been due to non-climatic factors. We address this assumption by jointly examining yield and climate variability for three major crops (rice, wheat and maize) over the past 50 years. National yield time series and growing season temperature and precipitation were de-trended and related using multiple linear regression. Yield variability changed significantly in half of the crop–country combinations examined. For several crop–country combinations, changes in yield variability were related to changes in climate variability. (letter)

Separating heat stress from moisture stress: analyzing yield response to high temperature in irrigated maize

Science.gov (United States)

Carter, Elizabeth K.; Melkonian, Jeff; Riha, Susan J.; Shaw, Stephen B.

2016-09-01

Several recent studies have indicated that high air temperatures are limiting maize (Zea mays L.) yields in the US Corn Belt and project significant yield losses with expected increases in growing season temperatures. Further work has suggested that high air temperatures are indicative of high evaporative demand, and that decreases in maize yields which correlate to high temperatures and vapor pressure deficits (VPD) likely reflect underlying soil moisture limitations. It remains unclear whether direct high temperature impacts on yields, independent of moisture stress, can be observed under current temperature regimes. Given that projected high temperature and moisture may not co-vary the same way as they have historically, quantitative analyzes of direct temperature impacts are critical for accurate yield projections and targeted mitigation strategies under shifting temperature regimes. To evaluate yield response to above optimum temperatures independent of soil moisture stress, we analyzed climate impacts on irrigated maize yields obtained from the National Corn Growers Association (NCGA) corn yield contests for Nebraska, Kansas and Missouri. In irrigated maize, we found no evidence of a direct negative impact on yield by daytime air temperature, calculated canopy temperature, or VPD when analyzed seasonally. Solar radiation was the primary yield-limiting climate variable. Our analyses suggested that elevated night temperature impacted yield by increasing rates of phenological development. High temperatures during grain-fill significantly interacted with yields, but this effect was often beneficial and included evidence of acquired thermo-tolerance. Furthermore, genetics and management—information uniquely available in the NCGA contest data—explained more yield variability than climate, and significantly modified crop response to climate. Thermo-acclimation, improved genetics and changes to management practices have the potential to partially or completely

Fourier Transform Mass Spectrometry and Nuclear Magnetic Resonance Analysis for the Rapid and Accurate Characterization of Hexacosanoylceramide.

Science.gov (United States)

Ross, Charles W; Simonsick, William J; Bogusky, Michael J; Celikay, Recep W; Guare, James P; Newton, Randall C

2016-06-28

Ceramides are a central unit of all sphingolipids which have been identified as sites of biological recognition on cellular membranes mediating cell growth and differentiation. Several glycosphingolipids have been isolated, displaying immunomodulatory and anti-tumor activities. These molecules have generated considerable interest as potential vaccine adjuvants in humans. Accurate analyses of these and related sphingosine analogues are important for the characterization of structure, biological function, and metabolism. We report the complementary use of direct laser desorption ionization (DLDI), sheath flow electrospray ionization (ESI) Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) and high-field nuclear magnetic resonance (NMR) analysis for the rapid, accurate identification of hexacosanoylceramide and starting materials. DLDI does not require stringent sample preparation and yields representative ions. Sheath-flow ESI yields ions of the product and byproducts and was significantly better than monospray ESI due to improved compound solubility. Negative ion sheath flow ESI provided data of starting materials and products all in one acquisition as hexacosanoic acid does not ionize efficiently when ceramides are present. NMR provided characterization of these lipid molecules complementing the results obtained from MS analyses. NMR data was able to differentiate straight chain versus branched chain alkyl groups not easily obtained from mass spectrometry.

Fourier Transform Mass Spectrometry and Nuclear Magnetic Resonance Analysis for the Rapid and Accurate Characterization of Hexacosanoylceramide

Directory of Open Access Journals (Sweden)

Charles W. Ross

2016-06-01

Full Text Available Ceramides are a central unit of all sphingolipids which have been identified as sites of biological recognition on cellular membranes mediating cell growth and differentiation. Several glycosphingolipids have been isolated, displaying immunomodulatory and anti-tumor activities. These molecules have generated considerable interest as potential vaccine adjuvants in humans. Accurate analyses of these and related sphingosine analogues are important for the characterization of structure, biological function, and metabolism. We report the complementary use of direct laser desorption ionization (DLDI, sheath flow electrospray ionization (ESI Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS and high-field nuclear magnetic resonance (NMR analysis for the rapid, accurate identification of hexacosanoylceramide and starting materials. DLDI does not require stringent sample preparation and yields representative ions. Sheath-flow ESI yields ions of the product and byproducts and was significantly better than monospray ESI due to improved compound solubility. Negative ion sheath flow ESI provided data of starting materials and products all in one acquisition as hexacosanoic acid does not ionize efficiently when ceramides are present. NMR provided characterization of these lipid molecules complementing the results obtained from MS analyses. NMR data was able to differentiate straight chain versus branched chain alkyl groups not easily obtained from mass spectrometry.

A series of inorganic solid nitrogen sources for the synthesis of metal nitride clusterfullerenes: the dependence of production yield on the oxidation state of nitrogen and counter ion.

Science.gov (United States)

Liu, Fupin; Guan, Jian; Wei, Tao; Wang, Song; Jiao, Mingzhi; Yang, Shangfeng

2013-04-01

A series of nitrogen-containing inorganic solid compounds with variable oxidation states of nitrogen and counter ions have been successfully applied as new inorganic solid nitrogen sources toward the synthesis of Sc-based metal nitride clusterfullerenes (Sc-NCFs), including ammonium salts [(NH4)xH(3-x)PO4 (x = 0-2), (NH4)2SO4, (NH4)2CO3, NH4X (X = F, Cl), NH4SCN], thiocyanate (KSCN), nitrates (Cu(NO3)2, NaNO3), and nitrite (NaNO2). Among them, ammonium phosphates ((NH4)xH(3-x)PO4, x = 1-3) and ammonium thiocyanate (NH4SCN) are revealed to behave as better nitrogen sources than others, and the highest yield of Sc-NCFs is achieved when NH4SCN was used as a nitrogen source. The optimum molar ratio of Sc2O3:(NH4)3PO4·3H2O:C and Sc2O3:NH4SCN:C has been determined to be 1:2:15 and 1:3:15, respectively. The thermal decomposition products of these 12 inorganic compounds have been discussed in order to understand their different performances toward the synthesis of Sc-NCFs, and accordingly the dependence of the production yield of Sc-NCFs on the oxidation state of nitrogen and counter ion is interpreted. The yield of Sc3N@C80 (I(h) + D(5h)) per gram Sc2O3 by using the N2-based group of nitrogen sources (thiocyanate, nitrates, and nitrite) is overall much lower than those by using gaseous N2 and NH4SCN, indicating the strong dependence of the yield of Sc-NCFs on the oxidation state of nitrogen, which is attributed to the "in-situ" redox reaction taking place for the N2-based group of nitrogen sources during discharging. For NH3-based group of nitrogen sources (ammonium salts) which exhibits a (-3) oxidation states of nitrogen, their performance as nitrogen sources is found to be sensitively dependent on the anion, and this is understood by considering their difference on the thermal stability and/or decomposition rate. Contrarily, for the N2-based group of nitrogen sources, the formation of Sc-NCFs is independent to both the oxidation state of nitrogen (+3 or +5) and the

Yield trends and yield gap analysis of major crops in the world

NARCIS (Netherlands)

Hengsdijk, H.; Langeveld, J.W.A.

2009-01-01

This study aims to quantify the gap between current and potential yields of major crops in the world, and the production constraints that contribute to this yield gap. Using an expert-based evaluation of yield gaps and the literature, global and regional yields and yield trends of major crops are

A Time--Independent Born--Oppenheimer Approximation with Exponentially Accurate Error Estimates

CERN Document Server

Hagedorn, G A

2004-01-01

We consider a simple molecular--type quantum system in which the nuclei have one degree of freedom and the electrons have two levels. The Hamiltonian has the form \\[ H(\\epsilon)\\ =\\ -\\,\\frac{\\epsilon^4}2\\, \\frac{\\partial^2\\phantom{i}}{\\partial y^2}\\ +\\ h(y), \\] where $h(y)$ is a $2\\times 2$ real symmetric matrix. Near a local minimum of an electron level ${\\cal E}(y)$ that is not at a level crossing, we construct quasimodes that are exponentially accurate in the square of the Born--Oppenheimer parameter $\\epsilon$ by optimal truncation of the Rayleigh--Schr\\"odinger series. That is, we construct $E_\\epsilon$ and $\\Psi_\\epsilon$, such that $\\|\\Psi_\\epsilon\\|\\,=\\,O(1)$ and \\[ \\|\\,(H(\\epsilon)\\,-\\,E_\\epsilon))\\,\\Psi_\\epsilon\\,\\|\\ 0. \\

Simulation Models of Leaf Area Index and Yield for Cotton Grown with Different Soil Conditioners.

Directory of Open Access Journals (Sweden)

Lijun Su

Full Text Available Simulation models of leaf area index (LAI and yield for cotton can provide a theoretical foundation for predicting future variations in yield. This paper analyses the increase in LAI and the relationships between LAI, dry matter, and yield for cotton under three soil conditioners near Korla, Xinjiang, China. Dynamic changes in cotton LAI were evaluated using modified logistic, Gaussian, modified Gaussian, log normal, and cubic polynomial models. Universal models for simulating the relative leaf area index (RLAI were established in which the application rate of soil conditioner was used to estimate the maximum LAI (LAIm. In addition, the relationships between LAIm and dry matter mass, yield, and the harvest index were investigated, and a simulation model for yield is proposed. A feasibility analysis of the models indicated that the cubic polynomial and Gaussian models were less accurate than the other three models for simulating increases in RLAI. Despite significant differences in LAIs under the type and amount of soil conditioner applied, LAIm could be described by aboveground dry matter using Michaelis-Menten kinetics. Moreover, the simulation model for cotton yield based on LAIm and the harvest index presented in this work provided important theoretical insights for improving water use efficiency in cotton cultivation and for identifying optimal application rates of soil conditioners.

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

Science.gov (United States)

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

On yield gaps and yield gains in intercropping

NARCIS (Netherlands)

Gou, Fang; Yin, Wen; Hong, Yu; Werf, van der Wopke; Chai, Qiang; Heerink, Nico; Ittersum, van Martin K.

2017-01-01

Wheat-maize relay intercropping has been widely used by farmers in northwest China, and based on field experiments agronomists report it has a higher productivity than sole crops. However, the yields from farmers’ fields have not been investigated yet. Yield gap analysis provides a framework to

Avoiding fractional electrons in subsystem DFT based ab-initio molecular dynamics yields accurate models for liquid water and solvated OH radical

International Nuclear Information System (INIS)

Genova, Alessandro; Pavanello, Michele; Ceresoli, Davide

2016-01-01

In this work we achieve three milestones: (1) we present a subsystem DFT method capable of running ab-initio molecular dynamics simulations accurately and efficiently. (2) In order to rid the simulations of inter-molecular self-interaction error, we exploit the ability of semilocal frozen density embedding formulation of subsystem DFT to represent the total electron density as a sum of localized subsystem electron densities that are constrained to integrate to a preset, constant number of electrons; the success of the method relies on the fact that employed semilocal nonadditive kinetic energy functionals effectively cancel out errors in semilocal exchange–correlation potentials that are linked to static correlation effects and self-interaction. (3) We demonstrate this concept by simulating liquid water and solvated OH • radical. While the bulk of our simulations have been performed on a periodic box containing 64 independent water molecules for 52 ps, we also simulated a box containing 256 water molecules for 22 ps. The results show that, provided one employs an accurate nonadditive kinetic energy functional, the dynamics of liquid water and OH • radical are in semiquantitative agreement with experimental results or higher-level electronic structure calculations. Our assessments are based upon comparisons of radial and angular distribution functions as well as the diffusion coefficient of the liquid.

Avoiding fractional electrons in subsystem DFT based ab-initio molecular dynamics yields accurate models for liquid water and solvated OH radical.

Science.gov (United States)

Genova, Alessandro; Ceresoli, Davide; Pavanello, Michele

2016-06-21

In this work we achieve three milestones: (1) we present a subsystem DFT method capable of running ab-initio molecular dynamics simulations accurately and efficiently. (2) In order to rid the simulations of inter-molecular self-interaction error, we exploit the ability of semilocal frozen density embedding formulation of subsystem DFT to represent the total electron density as a sum of localized subsystem electron densities that are constrained to integrate to a preset, constant number of electrons; the success of the method relies on the fact that employed semilocal nonadditive kinetic energy functionals effectively cancel out errors in semilocal exchange-correlation potentials that are linked to static correlation effects and self-interaction. (3) We demonstrate this concept by simulating liquid water and solvated OH(•) radical. While the bulk of our simulations have been performed on a periodic box containing 64 independent water molecules for 52 ps, we also simulated a box containing 256 water molecules for 22 ps. The results show that, provided one employs an accurate nonadditive kinetic energy functional, the dynamics of liquid water and OH(•) radical are in semiquantitative agreement with experimental results or higher-level electronic structure calculations. Our assessments are based upon comparisons of radial and angular distribution functions as well as the diffusion coefficient of the liquid.

Yield Behavior of Solution Treated and Aged Ti-6Al-4V

Science.gov (United States)

Ring, Andrew J.; Baker, Eric H.; Salem, Jonathan A.; Thesken, John C.

2014-01-01

Post yield uniaxial tension-compression tests were run on a solution treated and aged (STA), titanium 6-percent aluminum 4-percent vanadium (Ti-6Al-4V) alloy to determine the yield behavior on load reversal. The material exhibits plastic behavior almost immediately on load reversal implying a strong Bauschinger effect. The resultant stress-strain data was compared to a 1D mechanics model and a finite element model used to design a composite overwrapped pressure vessel (COPV). Although the models and experimental data compare well for the initial loading and unloading in the tensile regime, agreement is lost in the compressive regime due to the Bauschinger effect and the assumption of perfect plasticity. The test data presented here are being used to develop more accurate cyclic hardening constitutive models for future finite element design analysis of COPVs.

Fourier series

CERN Document Server

Tolstov, Georgi P

1962-01-01

Richard A. Silverman's series of translations of outstanding Russian textbooks and monographs is well-known to people in the fields of mathematics, physics, and engineering. The present book is another excellent text from this series, a valuable addition to the English-language literature on Fourier series.This edition is organized into nine well-defined chapters: Trigonometric Fourier Series, Orthogonal Systems, Convergence of Trigonometric Fourier Series, Trigonometric Series with Decreasing Coefficients, Operations on Fourier Series, Summation of Trigonometric Fourier Series, Double Fourie

Rice yield as a function of transplanting data using historic weather data from the Philippines

International Nuclear Information System (INIS)

Centeno, H.A.; Aclan, A.P.; Kropff, M.J.; Cassman, K.G.

1993-01-01

Crop yield potential differs among environments in different years, and between seasons in the same year. Under good farm management with ample supply of water and nutrients, and without any pests and diseases, cultivar characteristics, temperature and solar radiation determine the potential yield of a crop. In 1992, 12-day old seedlings of rice (Oryza sativa L.) cv IR72 were transplanted at IRRI [International Rice Research Inst., Los Banos, Laguna, Philippines] farm under irrigated conditions. Highest nitrogen input was 110 kg N/ha during the wet season (WS) and 225 kg N/ha in the dry season (DS). Nitrogen inputs in the wet season were lower to avoid lodging and to match crop N requirements. In both seasons, detailed measurements were obtained for a quantitative understanding of the determinants of rice yield potential. The eco-physiological growth model (ORYZA1) accurately simulated observed yields in the wet and dry seasons (6 and 9.5 t/ha, respectively). The model was used to simulate yields with different planting dates, using historic weather data from selected sites in the Philippines. Rice yield was simulated using leaf nitrogen levels measured in WS and DS experiments. In Los Banos, the highest yields were obtained when the crop was transplanted in December. When the leaf nitrogen measurements from the 1992 dry season experiment were incorporated in the model, predicted yield was higher throughout the year, with the effect more pronounced during the dry season

Prediction model of biocrude yield and nitrogen heterocyclic compounds analysis by hydrothermal liquefaction of microalgae with model compounds.

Science.gov (United States)

Sheng, Lili; Wang, Xin; Yang, Xiaoyi

2018-01-01

The model of biocrude yield and the nitrogen heterocyclic compounds in biocrude of microalgae hydrothermal liquefaction are two of the most concerned issues in this field at present. This study explored a hydrothermal liquefaction biocrude yield model involved in the interaction among biochemical compounds in microalgae and analysed nitrogen heterocyclic compounds in biocrude. The model compound (castor oil, soya protein and glucose) and Nanochloropsis were liquefied at 280°C for 1h. The products were analyzed by GC-MS, element analysis and FTIR. The results suggested that interactions among different components in microalgae enhanced biocrude yield. The biocrude yield prediction model involved cross-interactions performed more accurate than previous models.When the ratio of protein and carbohydrate around 3, the cross-interaction and nitrogen heterocyclic compounds in biocrude would both reach the highest extent. Copyright © 2017. Published by Elsevier Ltd.

A class of fully second order accurate projection methods for solving the incompressible Navier-Stokes equations

International Nuclear Information System (INIS)

Liu Miaoer; Ren Yuxin; Zhang Hanxin

2004-01-01

In this paper, a continuous projection method is designed and analyzed. The continuous projection method consists of a set of partial differential equations which can be regarded as an approximation of the Navier-Stokes (N-S) equations in each time interval of a given time discretization. The local truncation error (LTE) analysis is applied to the continuous projection methods, which yields a sufficient condition for the continuous projection methods to be temporally second order accurate. Based on this sufficient condition, a fully second order accurate discrete projection method is proposed. A heuristic stability analysis is performed to this projection method showing that the present projection method can be stable. The stability of the present scheme is further verified through numerical experiments. The second order accuracy of the present projection method is confirmed by several numerical test cases

Time series analytics using sliding window metaheuristic optimization-based machine learning system for identifying building energy consumption patterns

International Nuclear Information System (INIS)

Chou, Jui-Sheng; Ngo, Ngoc-Tri

2016-01-01

Highlights: • This study develops a novel time-series sliding window forecast system. • The system integrates metaheuristics, machine learning and time-series models. • Site experiment of smart grid infrastructure is installed to retrieve real-time data. • The proposed system accurately predicts energy consumption in residential buildings. • The forecasting system can help users minimize their electricity usage. - Abstract: Smart grids are a promising solution to the rapidly growing power demand because they can considerably increase building energy efficiency. This study developed a novel time-series sliding window metaheuristic optimization-based machine learning system for predicting real-time building energy consumption data collected by a smart grid. The proposed system integrates a seasonal autoregressive integrated moving average (SARIMA) model and metaheuristic firefly algorithm-based least squares support vector regression (MetaFA-LSSVR) model. Specifically, the proposed system fits the SARIMA model to linear data components in the first stage, and the MetaFA-LSSVR model captures nonlinear data components in the second stage. Real-time data retrieved from an experimental smart grid installed in a building were used to evaluate the efficacy and effectiveness of the proposed system. A k-week sliding window approach is proposed for employing historical data as input for the novel time-series forecasting system. The prediction system yielded high and reliable accuracy rates in 1-day-ahead predictions of building energy consumption, with a total error rate of 1.181% and mean absolute error of 0.026 kW h. Notably, the system demonstrates an improved accuracy rate in the range of 36.8–113.2% relative to those of the linear forecasting model (i.e., SARIMA) and nonlinear forecasting models (i.e., LSSVR and MetaFA-LSSVR). Therefore, end users can further apply the forecasted information to enhance efficiency of energy usage in their buildings, especially

Patient specific dynamic geometric models from sequential volumetric time series image data.

Science.gov (United States)

Cameron, B M; Robb, R A

2004-01-01

Generating patient specific dynamic models is complicated by the complexity of the motion intrinsic and extrinsic to the anatomic structures being modeled. Using a physics-based sequentially deforming algorithm, an anatomically accurate dynamic four-dimensional model can be created from a sequence of 3-D volumetric time series data sets. While such algorithms may accurately track the cyclic non-linear motion of the heart, they generally fail to accurately track extrinsic structural and non-cyclic motion. To accurately model these motions, we have modified a physics-based deformation algorithm to use a meta-surface defining the temporal and spatial maxima of the anatomic structure as the base reference surface. A mass-spring physics-based deformable model, which can expand or shrink with the local intrinsic motion, is applied to the metasurface, deforming this base reference surface to the volumetric data at each time point. As the meta-surface encompasses the temporal maxima of the structure, any extrinsic motion is inherently encoded into the base reference surface and allows the computation of the time point surfaces to be performed in parallel. The resultant 4-D model can be interactively transformed and viewed from different angles, showing the spatial and temporal motion of the anatomic structure. Using texture maps and per-vertex coloring, additional data such as physiological and/or biomechanical variables (e.g., mapping electrical activation sequences onto contracting myocardial surfaces) can be associated with the dynamic model, producing a 5-D model. For acquisition systems that may capture only limited time series data (e.g., only images at end-diastole/end-systole or inhalation/exhalation), this algorithm can provide useful interpolated surfaces between the time points. Such models help minimize the number of time points required to usefully depict the motion of anatomic structures for quantitative assessment of regional dynamics.

Direct quantum mechanical calculation of the F + H{sub 2} {yields} HF + H thermal rate constant

Energy Technology Data Exchange (ETDEWEB)

Moix, Marc [Computer Simulation and Modeling (COSMO) Lab, Parc Cientific de Barcelona, Josep Samitier 5, 08028 Barcelona (Spain); Institut de Quimica Teorica i Computacional de la UB (IQTCUB), Universitat de Barcelona (Spain); Huarte-Larranaga, Fermin [Computer Simulation and Modeling (COSMO) Lab, Parc Cientific de Barcelona, Josep Samitier 5, 08028 Barcelona (Spain); Institut de Quimica Teorica i Computacional de la UB (IQTCUB), Universitat de Barcelona (Spain)], E-mail: fhuarte@pcb.ub.es

2008-07-03

Accurate full-dimensional quantum mechanical thermal rate constant values have been calculated for the F+H{sub 2}{yields}HF+H reaction on the Stark-Werner ab initio potential energy surface. These calculations are based on a flux correlation functions and employ a rigorous statistical sampling scheme to account for the overall rotation and the MCTDH scheme for the wave packet propagation. Our results shed some light on discrepancies on the thermal rate found for previous flux correlation based calculations with respect to accurate reactive scattering results. The resonance pattern of the all-J cumulative reaction probability is analyzed in terms of the partial wave contributions.

Taylor Series-Based Long-Term Creep-Life Prediction of Alloy 617

International Nuclear Information System (INIS)

Yin, Song Nan; Kim, Woo Gon; Kim, Yong Wan; Park, Jae Young; Kim, Soen Jin

2010-01-01

In this study, a Taylor series (T-S) model based on the Arrhenius, McVetty, and Monkman-Grant equations was developed using a mathematical analysis. In order to reduce fitting errors, the McVetty equation was transformed by considering the first three terms of the Taylor series equation. The model parameters were accurately determined by a statistical technique of maximum likelihood estimation, and this model was applied to the creep data of alloy 617. The T-S model results showed better agreement with the experimental data than other models such as the Eno, exponential, and L-M models. In particular, the T-S model was converted into an isothermal Taylor series (IT-S) model that can predict the creep strength at a given temperature. It was identified that the estimations obtained using the converted ITS model was better than that obtained using the T-S model for predicting the long-term creep life of alloy 617

Influence of pressure on pyrolysis of black liquor: 2. Char yields and component release.

Science.gov (United States)

Whitty, Kevin; Kullberg, Mika; Sorvari, Vesa; Backman, Rainer; Hupa, Mikko

2008-02-01

This is the second in a series of papers concerning the behavior of black liquor during pyrolysis at elevated pressures. Two industrial black liquors were pyrolyzed under pressurized conditions in two laboratory-scale devices, a pressurized single-particle reactor and a pressurized grid heater. Temperatures ranging between 650 and 1100 degrees C and pressures in the range 1-20 bar were studied. Char yields were calculated and based on analysis of some of the chars the fate of carbon, sodium, potassium and sulfur was determined as a function of pyrolysis pressure. At temperatures below 800 degrees C little variation in char yield was observed at different pressures. At higher temperatures char yield increased with pressure due to slower decomposition of sodium carbonate. For the same reason, sodium release decreased with pressure. Sulfur release, however, increased with pressure primarily because there was less opportunity for its capture in the less-swollen chars.

On-line analysis of reactor noise using time-series analysis

International Nuclear Information System (INIS)

McGevna, V.G.

1981-10-01

A method to allow use of time series analysis for on-line noise analysis has been developed. On-line analysis of noise in nuclear power reactors has been limited primarily to spectral analysis and related frequency domain techniques. Time series analysis has many distinct advantages over spectral analysis in the automated processing of reactor noise. However, fitting an autoregressive-moving average (ARMA) model to time series data involves non-linear least squares estimation. Unless a high speed, general purpose computer is available, the calculations become too time consuming for on-line applications. To eliminate this problem, a special purpose algorithm was developed for fitting ARMA models. While it is based on a combination of steepest descent and Taylor series linearization, properties of the ARMA model are used so that the auto- and cross-correlation functions can be used to eliminate the need for estimating derivatives. The number of calculations, per iteration varies lineegardless of the mee 0.2% yield strength displayed anisotropy, with axial and circumferential values being greater than radial. For CF8-CPF8 and CF8M-CPF8M castings to meet current ASME Code S acid fuel cells

Quantifying evolutionary dynamics from variant-frequency time series

Science.gov (United States)

Khatri, Bhavin S.

2016-09-01

From Kimura’s neutral theory of protein evolution to Hubbell’s neutral theory of biodiversity, quantifying the relative importance of neutrality versus selection has long been a basic question in evolutionary biology and ecology. With deep sequencing technologies, this question is taking on a new form: given a time-series of the frequency of different variants in a population, what is the likelihood that the observation has arisen due to selection or neutrality? To tackle the 2-variant case, we exploit Fisher’s angular transformation, which despite being discovered by Ronald Fisher a century ago, has remained an intellectual curiosity. We show together with a heuristic approach it provides a simple solution for the transition probability density at short times, including drift, selection and mutation. Our results show under that under strong selection and sufficiently frequent sampling these evolutionary parameters can be accurately determined from simulation data and so they provide a theoretical basis for techniques to detect selection from variant or polymorphism frequency time-series.

Use of optical sensor for in-season nitrogen management and grain yield prediction in maize

Directory of Open Access Journals (Sweden)

Bandhu Raj Baral

2015-12-01

Full Text Available Precision agriculture technologies have developed optical sensors which can determine plant’s normalized difference vegetation index (NDVI.To evaluate the relationship between maize grain yield and early season NDVI readings, an experiment was conducted at farm land of National Maize Research Program, Rampur, Chitwan during winter season of 2012. Eight different levels of N 0, 30, 60, 90, 120, 150, 180 and 210 kg N/ha were applied for hybrid maize RML 32 × RML 17 to study grain yield response and NDVI measurement. Periodic NDVI was measured at 10 days interval from 55 days after sowing (DAS to 115 DAS by using Green seeker hand held crop sensor. Periodic NDVI measurement taken at a range of growing degree days (GDD was critical for predicting grain yield potential. Poor exponential relationship existed between NDVI from early reading measured before 208 GDD (55 DAS and grain yield. At the 261GDD (65DAS a strong relationship (R2 = 0.70 was achieved between NDVI and grain yield. Later sensor measurements after 571 GDD (95DAS failed to distinguish variation in green biomass as a result of canopy closure. N level had significantly influenced on NDVI reading, measured grain yield, calculated in season estimated yield (INSEY, predicted yield with added N (YPN, response index (RI and grain N demand. Measuring NDVI reading by GDD (261–571 GDD allow a practical window of opportunity for side dress N applications. This study showed that yield potential in maize could be accurately predicted in season with NDVI measured with the Green Seeker crop sensor.

Comparative Analysis of the $^{178m2}$Hf Yield at Reactions with Different Projectiles

CERN Document Server

Karamian, S A

2004-01-01

The long-lived high-spin $^{178m2}$Hf $K$-isomer can be produced in nuclear reactions with different projectiles. The reaction yields and cross-sections have been measured in the series of experiments and the results are now overviewed. The systematics of isomer-to-ground state ratios are drawn and real production capabilities are estimated for the best reactions. Such a summary is relevant to the significance of the isomer studies both for the nuclear-science knowledge and for possible applications. Potential isomer applications have been earlier stressed in popular publications with probably overestimated expectations. The real possibilities are restricted in part by the production yield and by other shortcomings as well.

Studies in Sri Lanka on cowpea: N2 fixation, growth, yield, and effects on cereals

International Nuclear Information System (INIS)

Senaratne, R.; Dayatilake, G.A.; Subasinghe, S.

1998-01-01

The impact of seed inoculation and N-fertilization on nodulation, plant dry-matter production, and seed yield was studied through a series of field experiments with cultivars of cowpea. In some instances there were positive growth responses to applied N, indicating the potential to improve N 2 fixation and yields by combining compatible genotypes and bradyrhizobial strains. Beneficial residual effects on growth of subsequent maize could not be related to N 2 fixation by the preceding cowpea. Although there was no evidence of direct transfer of N from cowpea to intercropped maize, there was greater efficiency of use of N for total crop production during intercropping

Resummation of divergent perturbation series: Application to the vibrational states of H2CO molecule

International Nuclear Information System (INIS)

Duchko, A. N.; Bykov, A. D.

2015-01-01

Large-order Rayleigh–Schrödinger perturbation theory (RSPT) is applied to the calculation of anharmonic vibrational energy levels of H 2 CO molecule. We use the model of harmonic oscillators perturbed by anharmonic terms of potential energy. Since the perturbation series typically diverge due to strong couplings, we apply the algebraic approximation technique because of its effectiveness shown earlier by Goodson and Sergeev [J. Chem. Phys. 110, 8205 (1999); ibid. 124, 094111 (2006)] and in our previous articles [A. D. Bykov et al. Opt. Spectrosc. 114, 396 (2013); ibid. 116, 598 (2014)]. To facilitate the resummation of terms contributing to perturbed states, when resonance mixing between states is especially strong and perturbation series diverge very quick, we used repartition of the Hamiltonian by shifting the normal mode frequencies. Energy levels obtained by algebraic approximants were compared with the results of variational calculation. It was found that for low energy states (up to ∼5000 cm −1 ), algebraic approximants gave accurate values of energy levels, which were in excellent agreement with the variational method. For highly excited states, strong and multiple resonances complicate series resummation, but a suitable change of normal mode frequencies allows one to reduce the resonance mixing and to get accurate energy levels. The theoretical background of the problem of RSPT series divergence is discussed along with its numerical analysis. For these purposes, the vibrational energy is considered as a function of a complex perturbation parameter. Layout and classification of its singularities allow us to model the asymptotic behavior of the perturbation series and prove the robustness of the algorithm

The US Stock Market Leads the Federal Funds Rate and Treasury Bond Yields

Science.gov (United States)

Guo, Kun; Zhou, Wei-Xing; Cheng, Si-Wei; Sornette, Didier

2011-01-01

Using a recently introduced method to quantify the time-varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P 500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started in mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen as key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P 500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis. PMID:21857954

The US stock market leads the federal funds rate and treasury bond yields.

Directory of Open Access Journals (Sweden)

Kun Guo

Full Text Available Using a recently introduced method to quantify the time-varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method, we test two fundamental tenets of the theory of fixed income: (i the stock market variations and the yield changes should be anti-correlated; (ii the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P 500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR, 3M, 6M, 1Y, 2Y, and 3Y and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y. In all cases, we observe the opposite of (i and (ii. First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started in mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen as key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P 500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis.

The US stock market leads the federal funds rate and treasury bond yields.

Science.gov (United States)

Guo, Kun; Zhou, Wei-Xing; Cheng, Si-Wei; Sornette, Didier

2011-01-01

Using a recently introduced method to quantify the time-varying lead-lag dependencies between pairs of economic time series (the thermal optimal path method), we test two fundamental tenets of the theory of fixed income: (i) the stock market variations and the yield changes should be anti-correlated; (ii) the change in central bank rates, as a proxy of the monetary policy of the central bank, should be a predictor of the future stock market direction. Using both monthly and weekly data, we found very similar lead-lag dependence between the S&P 500 stock market index and the yields of bonds inside two groups: bond yields of short-term maturities (Federal funds rate (FFR), 3M, 6M, 1Y, 2Y, and 3Y) and bond yields of long-term maturities (5Y, 7Y, 10Y, and 20Y). In all cases, we observe the opposite of (i) and (ii). First, the stock market and yields move in the same direction. Second, the stock market leads the yields, including especially the FFR. Moreover, we find that the short-term yields in the first group lead the long-term yields in the second group before the financial crisis that started in mid-2007 and the inverse relationship holds afterwards. These results suggest that the Federal Reserve is increasingly mindful of the stock market behavior, seen as key to the recovery and health of the economy. Long-term investors seem also to have been more reactive and mindful of the signals provided by the financial stock markets than the Federal Reserve itself after the start of the financial crisis. The lead of the S&P 500 stock market index over the bond yields of all maturities is confirmed by the traditional lagged cross-correlation analysis.

Homogeneity analysis of high yield manufacturing process of mems-based pzt thick film vibrational energy harvesters

DEFF Research Database (Denmark)

Lei, Anders; Xu, Ruichao; Pedersen, C.M.

2011-01-01

This work presents a high yield wafer scale fabrication of MEMS-based unimorph silicon/PZT thick film vibrational energy harvesters aimed towards vibration sources with peak frequencies in the range of a few hundred Hz. By combining KOH etching with mechanical front side protection, SOI wafer...... to accurately define the thickness of the silicon part of the harvester and a silicon compatible PZT thick film screen-printing technique, we are able to fabricate energy harvesters on wafer scale with a yield higher than 90%. The characterization of the fabricated harvesters is focused towards the full wafer....../mass-production aspect; hence the analysis of uniformity in harvested power and resonant frequency....

Extrapolating effects of conservation tillage on yield, soil moisture and dry spell mitigation using simulation modelling

Science.gov (United States)

Mkoga, Z. J.; Tumbo, S. D.; Kihupi, N.; Semoka, J.

There is big effort to disseminate conservation tillage practices in Tanzania. Despite wide spread field demonstrations there has been some field experiments meant to assess and verify suitability of the tillage options in local areas. Much of the experiments are short lived and thus long term effects of the tillage options are unknown. Experiments to study long term effects of the tillage options are lacking because they are expensive and cannot be easily managed. Crop simulation models have the ability to use long term weather data and the local soil parameters to assess long term effects of the tillage practices. The Agricultural Production Systems Simulator (APSIM) crop simulation model; was used to simulate long term production series of soil moisture and grain yield based on the soil and weather conditions in Mkoji sub-catchment of the great Ruaha river basin in Tanzania. A 24 year simulated maize yield series based on conventional tillage with ox-plough, without surface crop residues (CT) treatment was compared with similar yield series based on conservation tillage (ox-ripping, with surface crop residues (RR)). Results showed that predicted yield averages were significantly higher in conservation tillage than in conventional tillage ( P APSIM simulation model, showed that average soil moisture in the conservation tillage was significantly higher ( P < 0.05) (about 0.29 mm/mm) than in conventional tillage (0.22 mm/mm) treatment during the seasons which received rainfall between 468 and 770 mm. Similarly the conservation tillage treatment recorded significantly higher yields (4.4 t/ha) ( P < 0.01) than the conventional tillage (3.6 t/ha) treatment in the same range of seasonal rainfall. On the other hand there was no significant difference in soil moisture for the seasons which received rainfall above 770 mm. In these seasons grain yield in conservation tillage treatment was significantly lower (3.1 kg/ha) than in the conventional tillage treatment (4.8 kg

Current Directional Protection of Series Compensated Line Using Intelligent Classifier

Directory of Open Access Journals (Sweden)

M. Mollanezhad Heydarabadi

2016-12-01

Full Text Available Current inversion condition leads to incorrect operation of current based directional relay in power system with series compensated device. Application of the intelligent system for fault direction classification has been suggested in this paper. A new current directional protection scheme based on intelligent classifier is proposed for the series compensated line. The proposed classifier uses only half cycle of pre-fault and post fault current samples at relay location to feed the classifier. A lot of forward and backward fault simulations under different system conditions upon a transmission line with a fixed series capacitor are carried out using PSCAD/EMTDC software. The applicability of decision tree (DT, probabilistic neural network (PNN and support vector machine (SVM are investigated using simulated data under different system conditions. The performance comparison of the classifiers indicates that the SVM is a best suitable classifier for fault direction discriminating. The backward faults can be accurately distinguished from forward faults even under current inversion without require to detect of the current inversion condition.

Ground-level ozone in China: Distribution and effects on crop yields

International Nuclear Information System (INIS)

Wang Xiaoke; Manning, William; Feng Zongwei; Zhu Yongguan

2007-01-01

Rapid economic development and an increasing demand for food in China have drawn attention to the role of ozone at pollution levels on crop yields. Some assessments of ozone effects on crop yields have been carried out in China. Determination of ozone distribution by geographical location and resulting crop loss estimations have been made by Chinese investigators and others from abroad. It is evident that surface level ozone levels in China exceed critical levels for occurrence of crop losses. Current levels of information from ozone dose/response studies are limited. Given the size of China, existing ozone monitoring sites are too few to provide enough data to scale ozone distribution to a national level. There are large uncertainties in the database for ozone effects on crop loss and for ozone distribution. Considerable research needs to be done to allow accurate estimation of crop losses caused by ozone in China. - More research is needed to reliably estimate ozone caused crop losses in China

[Effects of Chemical Fertilizers and Organic Fertilizer on Yield of Ligusticum chuanxiong Rhizome].

Science.gov (United States)

Liang, Qin; Chen, Xing-fu; Li, Yan; Zhang, Jun; Meng, Jie; Peng, Shi-ming

2015-10-01

To study the effects of different N, P, K and organic fertilizer (OF) on yield of Ligusticum chuanxiong rhizome, in order to provide the theoretical foundation for the establishment of standardization cultivation techniques. The field plot experiments used Ligusticum chuanxiong rhizome which planted in Pengshan as material, and were studied by the four factors and five levels with quadratic regression rotation-orthogonal combination design. According to the data obtained, a function model which could predict the fertilization and yield of Ligusticum chuanxiong rhizome accurately was established. The model analysis showed that the yields of Ligusticum chuanxiong rhizome were significantly influenced by the N, P, K and OF applications. Among these factors, the order of increase rates by the fertilizers was K > OF > N > P; The effect of interaction between N and K, N and OF, K and OF on the yield of Ligusticum chuanxiong rhizome were significantly different. High levels of N and P, N and organic fertilizer, K and organic fertilizer were conducive to improve the yield of Ligusticum chuanxiong rhizome. The results showed that the optimal fertilizer application rates of N was 148.20 - 172.28 kg/hm2, P was 511.92 - 599.40 kg/hm2, K was 249.70 - 282.37 kg/hm2, and OF was 940.00 - 1 104.00 kg/hm2. N, P, K and OF obviously affect the yield of Ligusticum chuanxiong rhizome. K and OF can significantly increase the yield of Ligusticum chuanxiong rhizome. Thus it is suggested that properly high mount of K and OF and appropriate increasing N are two favorable factors for cultivating Ligusticum chuanxiong.

`Indoor` series vending machines; `Indoor` series jido hanbaiki

Energy Technology Data Exchange (ETDEWEB)

Gensui, T.; Kida, A. [Fuji Electric Co. Ltd., Tokyo (Japan); Okumura, H. [Fuji Denki Reiki Co. Ltd., Tokyo (Japan)

1996-07-10

This paper introduces three series of vending machines that were designed to match the interior of an office building. The three series are vending machines for cups, paper packs, cans, and tobacco. Among the three series, `Interior` series has a symmetric design that was coated in a grain pattern. The inside of the `Interior` series is coated by laser satin to ensure a sense of superior quality and a refined style. The push-button used for product selection is hot-stamped on the plastic surface to ensure the hair-line luster. `Interior Phase II` series has a bay window design with a sense of superior quality and lightness. The inside of the `Interior Phase II` series is coated by laser satin. `Interior 21` series is integrated with the wall except the sales operation panel. The upper and lower dress panels can be detached and attached. The door lock is a wire-type structure with high operativity. The operation block is coated by titanium color. The dimensions of three series are standardized. 6 figs., 1 tab.

How Accurately Do Maize Crop Models Simulate the Interactions of Atmospheric CO2 Concentration Levels With Limited Water Supply on Water Use and Yield?

Science.gov (United States)

Durand, Jean-Louis; Delusca, Kenel; Boote, Ken; Lizaso, Jon; Manderscheid, Remy; Weigel, Hans Johachim; Ruane, Alexander Clark; Rosenzweig, Cynthia E.; Jones, Jim; Ahuja, Laj;

Development of Simulink-Based SiC MOSFET Modeling Platform for Series Connected Devices

DEFF Research Database (Denmark)

Tsolaridis, Georgios; Ilves, Kalle; Reigosa, Paula Diaz

2016-01-01

A new MATLAB/Simulink-based modeling platform has been developed for SiC MOSFET power modules. The modeling platform describes the electrical behavior f a single 1.2 kV/ 350 A SiC MOSFET power module, as well as the series connection of two of them. A fast parameter initialization is followed...... by an optimization process to facilitate the extraction of the model’s parameters in a more automated way relying on a small number of experimental waveforms. Through extensive experimental work, it is shown that the model accurately predicts both static and dynamic performances. The series connection of two Si......C power modules has been investigated through the validation of the static and dynamic conditions. Thanks to the developed model, a better understanding of the challenges introduced by uneven voltage balance sharing among series connected devices is possible....

Studies on improvement of tomato productivity in a large-scale greenhouse: Prediction of tomato yield based on integrated solar radiation

International Nuclear Information System (INIS)

Hisaeda, K.; Nishina, H.

2007-01-01

As there are currently many large-scale production facilities that have contracts with the large retailing companies, accurate prediction of yield is necessary. The present study developed a method to predict tomato yield accurately using the data on the outside solar radiation. The present study was conducted in a Venlo-type greenhouse (29,568 square m) at Sera Farm Co., Ltd. in Sera-cho in Hiroshima prefecture. The cultivar used for this experiment was plum tomato. The sowing took place on July 18, the planting took place on August 30, and the harvesting started on October 9, 2002. The planting density was 2.5 plants msup(-2). As the results of the analysis of correlation between the weekly tomato yield and the integrated solar radiation for the period from October 7 to July 28 (43 weeks), the highest correlation (r = 0.518) between the weekly tomato yield and the solar radiation integrated from seven to one weeks before the harvesting was observed. Further investigation by the same correlation analysis was conducted for the 25 weeks period from December 8 to May 26, during which time the effect of growing stages and air temperature were considered to be relatively small. The results showed the highest correlation (r = 0.730) between the weekly tomato yield and the solar radiation integrated from eight to one weeks before the harvesting. The tomato yield occasionally needed to be adjusted at Sera Farm. Consequently, the correlation between the three-week moving average of tomato yield and the integrated solar radiation was calculated. The results showed the highest correlation was obtained for the period from eight to one weeks before the harvesting (r = 0.860). This study therefore showed that it was possible to predict the tomato yield (y: kg.msup(-2).weeksup(-1)) using the following equation on the solar radiation integrated from eight to one weeks before the harvesting(x: MJ.msup(-2)): y = 7.50 x 10 sup(-6)x + 0.148 (rsup(2) = 0.740)

VARIABILITY OF YIELD AND YIELD COMPONENTS IN “EGUSI ...

African Journals Online (AJOL)

journal

Estimate of expected genetic advance in seed yield plant-1 ranged between. 25.90-48.40%. ..... values in fruit and seed yield characters have been reported in culinary melon, ... and Khund, A. 2004. Extent of heterosis and heritability in some.

Potential of Ranunculus acris L. for biomonitoring trace element contamination of riverbank soils: photosystem II activity and phenotypic responses for two soil series.

Science.gov (United States)

Marchand, Lilian; Lamy, Pierre; Bert, Valerie; Quintela-Sabaris, Celestino; Mench, Michel

2016-02-01

Foliar ionome, photosystem II activity, and leaf growth parameters of Ranunculus acris L., a potential biomonitor of trace element (TE) contamination and phytoavailability, were assessed using two riverbank soil series. R. acris was cultivated on two potted soil series obtained by mixing a TE (Cd, Cu, Pb, and Zn)-contaminated technosol with either an uncontaminated sandy riverbank soil (A) or a silty clay one slightly contaminated by TE (B). Trace elements concentrations in the soil-pore water and the leaves, leaf dry weight (DW) yield, total leaf area (TLA), specific leaf area (SLA), and photosystem II activity were measured for both soil series after a 50-day growth period. As soil contamination increased, changes in soluble TE concentrations depended on soil texture. Increase in total soil TE did not affect the leaf DW yield, the TLA, the SLA, and the photosystem II activity of R. acris over the 50-day exposure. The foliar ionome did not reflect the total and soluble TE concentrations in both soil series. Foliar ionome of R. acris was only effective to biomonitor total and soluble soil Na concentrations in both soil series and total and soluble soil Mo concentrations in the soil series B.

An adaptive state of charge estimation approach for lithium-ion series-connected battery system

Science.gov (United States)

Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael

2018-07-01

Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.

Fission product yields

International Nuclear Information System (INIS)

Valenta, V.; Hep, J.

1978-01-01

Data are summed up necessary for determining the yields of individual fission products from different fissionable nuclides. Fractional independent yields, cumulative and isobaric yields are presented here for the thermal fission of 235 U, 239 Pu, 241 Pu and for fast fission (approximately 1 MeV) of 235 U, 238 U, 239 Pu, 241 Pu; these values are included into the 5th version of the YIELDS library, supplementing the BIBFP library. A comparison is made of experimental data and possible improvements of calculational methods are suggested. (author)

Yield estimation for nuclear explosions of semipalatinsk using rayleigh waves recorded at SRO, Mashhad

International Nuclear Information System (INIS)

Naghizadeh, M.; Javaherian, A.; Sadidkhooy, A.

2005-01-01

Surface wave amplitudes from explosion sources show less variation for a given event than body wave amplitudes, so it is natural to expect that yield estimation derived from surface waves will be more accurate than yield estimation derived from body waves. However yield estimation from surface waves is complicated by the presence of tectonic strain release, which acts like one or more earthquake sources superimposed on the explosion. Explosions on an island or near a mountain slope can exhibit anomalous surface waves similar to those caused by tectonic strain release. One of the methods in estimating the yield of nuclear explosions is to determine a relationship between the magnitude and the yield of an explosion. The kind of magnitude employed has an important role in this regard. In this paper, vertical component of long period seismograms at SRO, Mashhad from explosions occurred in semipalatinsk test site, semipalatinsk test site east of Kazakhstan) are considered. First, by using the relationships of IASPEI and Rezapour and Pearce (1998), we determined surface wave magnitude (MS) which is defined as the logarithm of the amplitude plus a distance correction. Then we derived a relation for M S versus yield for a data set which includes a 15 long period seismograms recorded at SRO Mashhad station from semipalatinsk test site nuclear explosions. Furthermore, by digitizing the vertical component of seismograms and transforming them to the frequency domain, the mean amplitude of records at frequency ranges of 0.04-0.06 Hz were calculated. Then, surface wave magnitudes in the frequency domain (M Sf ) and their corresponding yield-magnitude relationship were obtained. By comparing correlation coefficients of these two yield-magnitude relationships, following relationship M S = 1.079 log(Y) + 1.714, was chosen for estimating the yield of semipalatinsk test site nuclear explosion from seismograms of SRO

Computational design of new molecular scaffolds for medicinal chemistry, part II: generalization of analog series-based scaffolds

Science.gov (United States)

Dimova, Dilyana; Stumpfe, Dagmar; Bajorath, Jürgen

2018-01-01

Aim: Extending and generalizing the computational concept of analog series-based (ASB) scaffolds. Materials & methods: Methodological modifications were introduced to further increase the coverage of analog series (ASs) and compounds by ASB scaffolds. From bioactive compounds, ASs were systematically extracted and second-generation ASB scaffolds isolated. Results: More than 20,000 second-generation ASB scaffolds with single or multiple substitution sites were extracted from active compounds, achieving more than 90% coverage of ASs. Conclusion: Generalization of the ASB scaffold approach has yielded a large knowledge base of scaffold-capturing compound series and target information. PMID:29379641

Statistical Analysis of Large Simulated Yield Datasets for Studying Climate Effects

Science.gov (United States)

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

Time series from hyperion to track productivity in pivot agriculture in saudi arabia

KAUST Repository

Houborg, Rasmus

2017-12-13

The hyperspectral satellite sensing capacity is expected to increase substantially in the near future with the planned deployment of hyperspectral systems by both space agencies and commercial companies. These enhanced observational resources will offer new and improved ways to monitor the dynamics and characteristics of terrestrial ecosystems. This study investigates the utility of time series of hyperspectral imagery, acquired by Hyperion onboard EO-1, for quantifying variations in canopy chlorophyll (Chl_c), plant productivity, and yield over an intensive farming area in the desert of Saudi Arabia. Chl_c is estimated on the basis of predictive multi-variate empirical models established via a machine learning approach using a training dataset of in-situ measured target variables and explanatory hyperspectral indices. Resulting time series of Chl_c are translated into Gross Primary Productivity (GPP) and Yield based on semi-empirical relationships, and evaluated against ground-based observations. Results indicate significant benefit in utilizing the full suite of hyperspectral indices over multi-spectral indices constructible from Landsat-8 and Sentinel-2.

Time series from hyperion to track productivity in pivot agriculture in saudi arabia

KAUST Repository

Houborg, Rasmus; McCabe, Matthew; Angel, Yoseline; Middleton, Elizabeth M.

2017-01-01

The hyperspectral satellite sensing capacity is expected to increase substantially in the near future with the planned deployment of hyperspectral systems by both space agencies and commercial companies. These enhanced observational resources will offer new and improved ways to monitor the dynamics and characteristics of terrestrial ecosystems. This study investigates the utility of time series of hyperspectral imagery, acquired by Hyperion onboard EO-1, for quantifying variations in canopy chlorophyll (Chl_c), plant productivity, and yield over an intensive farming area in the desert of Saudi Arabia. Chl_c is estimated on the basis of predictive multi-variate empirical models established via a machine learning approach using a training dataset of in-situ measured target variables and explanatory hyperspectral indices. Resulting time series of Chl_c are translated into Gross Primary Productivity (GPP) and Yield based on semi-empirical relationships, and evaluated against ground-based observations. Results indicate significant benefit in utilizing the full suite of hyperspectral indices over multi-spectral indices constructible from Landsat-8 and Sentinel-2.

Statistical modelling of grapevine yield in the Port Wine region under present and future climate conditions

Science.gov (United States)

Santos, João A.; Malheiro, Aureliano C.; Karremann, Melanie K.; Pinto, Joaquim G.

2011-03-01

The impact of projected climate change on wine production was analysed for the Demarcated Region of Douro, Portugal. A statistical grapevine yield model (GYM) was developed using climate parameters as predictors. Statistically significant correlations were identified between annual yield and monthly mean temperatures and monthly precipitation totals during the growing cycle. These atmospheric factors control grapevine yield in the region, with the GYM explaining 50.4% of the total variance in the yield time series in recent decades. Anomalously high March rainfall (during budburst, shoot and inflorescence development) favours yield, as well as anomalously high temperatures and low precipitation amounts in May and June (May: flowering and June: berry development). The GYM was applied to a regional climate model output, which was shown to realistically reproduce the GYM predictors. Finally, using ensemble simulations under the A1B emission scenario, projections for GYM-derived yield in the Douro Region, and for the whole of the twenty-first century, were analysed. A slight upward trend in yield is projected to occur until about 2050, followed by a steep and continuous increase until the end of the twenty-first century, when yield is projected to be about 800 kg/ha above current values. While this estimate is based on meteorological parameters alone, changes due to elevated CO2 may further enhance this effect. In spite of the associated uncertainties, it can be stated that projected climate change may significantly benefit wine yield in the Douro Valley.

Estimating agricultural yield gap in Africa using MODIS NDVI dataset

Science.gov (United States)

Luan, Y.; Zhu, W.; Luo, X.; Liu, J.; Cui, X.

2013-12-01

Global agriculture has undergone a period of rapid intensification characterized as 'Green Revolution', except for Africa, which is the region most affected by unreliable food access and undernourishment. Increasing crop production will be one of the most challenges and most effectual way to mitigate food insecurity there, as Africa's agricultural yield is on a much lower level comparing to global average. In this study we characterize cropland vegetation phenology in Africa based on MODIS NDVI time series between 2000 and 2012. Cumulated NDVI is a proxy for net primary productivity and used as an indicator for evaluating the potential yield gap in Africa. It is achieved via translating the gap between optimum attainable productivity level in each classification of cropping systems and actual productivity level by the relationship of cumulated NDVI and cereal-equivalent production. The results show most of cropland area in Africa have decreasing trend in cumulated NDVI, distributing in the Nile Delta, Eastern Africa and central of semi-arid to arid savanna area, except significant positive cumulated NDVI trends are mainly found between Senegal and Benin. Using cumulated NDVI and statistics of cereal equivalent production, we find remarkable potential yield gap at the Horn of East Africa (especially in Somalia), Northern Africa (Morocco, Algeria and Tunisia). Meanwhile, countries locating at the savanna area near Sahel desert and South Africa also show significant potential, though they already have a relatively high level of productivity. Our results can help provide policy recommendation for local government or NGO to tackle food security problems by identifying zones with high potential of yield improvement.

yield and yield componemts of extra early maize (zea mays l.)

African Journals Online (AJOL)

SHARIFAI

maize crop and improve the soil structures and chemical nutrients of the soil. The significant interaction between intra-row spacing and poultry manure on cob diameter, 100 grain weight and grain yield showed the importance of poultry manure on yield and yield components of maize crop. Poultry manure increases both ...

An adapted yield criterion for the evolution of subsequent yield surfaces

Science.gov (United States)

Küsters, N.; Brosius, A.

2017-09-01

In numerical analysis of sheet metal forming processes, the anisotropic material behaviour is often modelled with isotropic work hardening and an average Lankford coefficient. In contrast, experimental observations show an evolution of the Lankford coefficients, which can be associated with a yield surface change due to kinematic and distortional hardening. Commonly, extensive efforts are carried out to describe these phenomena. In this paper an isotropic material model based on the Yld2000-2d criterion is adapted with an evolving yield exponent in order to change the yield surface shape. The yield exponent is linked to the accumulative plastic strain. This change has the effect of a rotating yield surface normal. As the normal is directly related to the Lankford coefficient, the change can be used to model the evolution of the Lankford coefficient during yielding. The paper will focus on the numerical implementation of the adapted material model for the FE-code LS-Dyna, mpi-version R7.1.2-d. A recently introduced identification scheme [1] is used to obtain the parameters for the evolving yield surface and will be briefly described for the proposed model. The suitability for numerical analysis will be discussed for deep drawing processes in general. Efforts for material characterization and modelling will be compared to other common yield surface descriptions. Besides experimental efforts and achieved accuracy, the potential of flexibility in material models and the risk of ambiguity during identification are of major interest in this paper.

A hybrid wavelet de-noising and Rank-Set Pair Analysis approach for forecasting hydro-meteorological time series.

Science.gov (United States)

Wang, Dong; Borthwick, Alistair G; He, Handan; Wang, Yuankun; Zhu, Jieyu; Lu, Yuan; Xu, Pengcheng; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Liu, Jiufu; Zou, Ying; He, Ruimin

2018-01-01

Accurate, fast forecasting of hydro-meteorological time series is presently a major challenge in drought and flood mitigation. This paper proposes a hybrid approach, wavelet de-noising (WD) and Rank-Set Pair Analysis (RSPA), that takes full advantage of a combination of the two approaches to improve forecasts of hydro-meteorological time series. WD allows decomposition and reconstruction of a time series by the wavelet transform, and hence separation of the noise from the original series. RSPA, a more reliable and efficient version of Set Pair Analysis, is integrated with WD to form the hybrid WD-RSPA approach. Two types of hydro-meteorological data sets with different characteristics and different levels of human influences at some representative stations are used to illustrate the WD-RSPA approach. The approach is also compared to three other generic methods: the conventional Auto Regressive Integrated Moving Average (ARIMA) method, Artificial Neural Networks (ANNs) (BP-error Back Propagation, MLP-Multilayer Perceptron and RBF-Radial Basis Function), and RSPA alone. Nine error metrics are used to evaluate the model performance. Compared to three other generic methods, the results generated by WD-REPA model presented invariably smaller error measures which means the forecasting capability of the WD-REPA model is better than other models. The results show that WD-RSPA is accurate, feasible, and effective. In particular, WD-RSPA is found to be the best among the various generic methods compared in this paper, even when the extreme events are included within a time series. Copyright © 2017 Elsevier Inc. All rights reserved.

Molecular acidity: An accurate description with information-theoretic approach in density functional reactivity theory.

Science.gov (United States)

Cao, Xiaofang; Rong, Chunying; Zhong, Aiguo; Lu, Tian; Liu, Shubin

2018-01-15

Molecular acidity is one of the important physiochemical properties of a molecular system, yet its accurate calculation and prediction are still an unresolved problem in the literature. In this work, we propose to make use of the quantities from the information-theoretic (IT) approach in density functional reactivity theory and provide an accurate description of molecular acidity from a completely new perspective. To illustrate our point, five different categories of acidic series, singly and doubly substituted benzoic acids, singly substituted benzenesulfinic acids, benzeneseleninic acids, phenols, and alkyl carboxylic acids, have been thoroughly examined. We show that using IT quantities such as Shannon entropy, Fisher information, Ghosh-Berkowitz-Parr entropy, information gain, Onicescu information energy, and relative Rényi entropy, one is able to simultaneously predict experimental pKa values of these different categories of compounds. Because of the universality of the quantities employed in this work, which are all density dependent, our approach should be general and be applicable to other systems as well. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Comparison of HSPF and SWAT models performance for runoff and sediment yield prediction.

Science.gov (United States)

Im, Sangjun; Brannan, Kevin M; Mostaghimi, Saied; Kim, Sang Min

2007-09-01

A watershed model can be used to better understand the relationship between land use activities and hydrologic/water quality processes that occur within a watershed. The physically based, distributed parameter model (SWAT) and a conceptual, lumped parameter model (HSPF), were selected and their performance were compared in simulating runoff and sediment yields from the Polecat Creek watershed in Virginia, which is 12,048 ha in size. A monitoring project was conducted in Polecat Creek watershed during the period of October 1994 to June 2000. The observed data (stream flow and sediment yield) from the monitoring project was used in the calibration/validations of the models. The period of September 1996 to June 2000 was used for the calibration and October 1994 to December 1995 was used for the validation of the models. The outputs from the models were compared to the observed data at several sub-watershed outlets and at the watershed outlet of the Polecat Creek watershed. The results indicated that both models were generally able to simulate stream flow and sediment yields well during both the calibration/validation periods. For annual and monthly loads, HSPF simulated hydrologic and sediment yield more accurately than SWAT at all monitoring sites within the watershed. The results of this study indicate that both the SWAT and HSPF watershed models performed sufficiently well in the simulation of stream flow and sediment yield with HSPF performing moderately better than SWAT for simulation time-steps greater than a month.

Towards accurate emergency response behavior

International Nuclear Information System (INIS)

Sargent, T.O.

1981-01-01

Nuclear reactor operator emergency response behavior has persisted as a training problem through lack of information. The industry needs an accurate definition of operator behavior in adverse stress conditions, and training methods which will produce the desired behavior. Newly assembled information from fifty years of research into human behavior in both high and low stress provides a more accurate definition of appropriate operator response, and supports training methods which will produce the needed control room behavior. The research indicates that operator response in emergencies is divided into two modes, conditioned behavior and knowledge based behavior. Methods which assure accurate conditioned behavior, and provide for the recovery of knowledge based behavior, are described in detail

OSM-Classic : An optical imaging technique for accurately determining strain

Science.gov (United States)

Aldrich, Daniel R.; Ayranci, Cagri; Nobes, David S.

OSM-Classic is a program designed in MATLAB® to provide a method of accurately determining strain in a test sample using an optical imaging technique. Measuring strain for the mechanical characterization of materials is most commonly performed with extensometers, LVDT (linear variable differential transistors), and strain gauges; however, these strain measurement methods suffer from their fragile nature and it is not particularly easy to attach these devices to the material for testing. To alleviate these potential problems, an optical approach that does not require contact with the specimen can be implemented to measure the strain. OSM-Classic is a software that interrogates a series of images to determine elongation in a test sample and hence, strain of the specimen. It was designed to provide a graphical user interface that includes image processing with a dynamic region of interest. Additionally, the stain is calculated directly while providing active feedback during the processing.

The impact of large-scale circulation patterns on summer crop yields in IP

Science.gov (United States)

Capa Morocho, Mirian; Rodríguez Fonseca, Belén; Ruiz Ramos, Margarita

2014-05-01

Large-scale circulations patterns (ENSO, NAO) have been shown to have a significant impact on seasonal weather, and therefore on crop yield over many parts of the world(Garnett and Khandekar, 1992; Aasa et al., 2004; Rozas and Garcia-Gonzalez, 2012). In this study, we analyze the influence of large-scale circulation patterns and regional climate on the principal components of maize yield variability in Iberian Peninsula (IP) using reanalysis datasets. Additionally, we investigate the modulation of these relationships by multidecadal patterns. This study is performed analyzing long time series of maize yield, only climate dependent, computed with the crop model CERES-maize (Jones and Kiniry, 1986) included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5). To simulate yields, reanalysis daily data of radiation, maximum and minimum temperature and precipitation were used. The reanalysis climate data were obtained from National Center for Environmental Prediction (20th Century and NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) data server (ERA 40 and ERA Interim). Simulations were run at five locations: Lugo (northwestern), Lerida (NE), Madrid (central), Albacete (southeastern) and Córdoba (S IP) (Gabaldón et al., 2013). From these time series standardized anomalies were calculated. Afterwards, time series were time filtered to focus on the interannual-to-multiannual variability, splitting up in two components: low frequency (LF) and high frequency (HF) time scales. The principal components of HF yield anomalies in IP were compared with a set of documented patterns. These relationships were compared with multidecadal patterns, as Atlanctic Multidecadal Oscillations (AMO) and Interdecadal Pacific Oscillations (IPO). The results of this study have important implications in crop forecasting. In this way, it may have a positive impact on both public (agricultural planning) and private (decision support to farmers, insurance

Inheritance of grain yield and its correlation with yield components in ...

African Journals Online (AJOL)

SAM

2014-03-19

Mar 19, 2014 ... 7 × 7 incomplete diallel cross of seven wheat parents during the crop season of 2009 to 2010. Mean square of general ... Genetic background and yield traits of the seven parents. Parent. Pedigree. Released year ..... Correlation and path analysis for yield and yield contributing characters in wheat (Triticum ...

Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction

Science.gov (United States)

Wagstaff, Kiri L.; Lane, Terran

2010-01-01

An algorithm was developed to generate crop yield predictions from orbital remote sensing observations, by analyzing thousands of pixels per county and the associated historical crop yield data for those counties. The algorithm determines which pixels contain which crop. Since each known yield value is associated with thousands of individual pixels, this is a multiple instance learning problem. Because individual crop growth is related to the resulting yield, this relationship has been leveraged to identify pixels that are individually related to corn, wheat, cotton, and soybean yield. Those that have the strongest relationship to a given crop s yield values are most likely to contain fields with that crop. Remote sensing time series data (a new observation every 8 days) was examined for each pixel, which contains information for that pixel s growth curve, peak greenness, and other relevant features. An alternating-projection (AP) technique was used to first estimate the "salience" of each pixel, with respect to the given target (crop yield), and then those estimates were used to build a regression model that relates input data (remote sensing observations) to the target. This is achieved by constructing an exemplar for each crop in each county that is a weighted average of all the pixels within the county; the pixels are weighted according to the salience values. The new regression model estimate then informs the next estimate of the salience values. By iterating between these two steps, the algorithm converges to a stable estimate of both the salience of each pixel and the regression model. The salience values indicate which pixels are most relevant to each crop under consideration.

Application of cross-sectional time series modeling for the prediction of energy expenditure from heart rate and accelerometry

Science.gov (United States)

Accurate estimation of energy expenditure (EE) in children and adolescents is required for a better understanding of physiological, behavioral, and environmental factors affecting energy balance. Cross-sectional time series (CSTS) models, which account for correlation structure of repeated observati...

Resummation of divergent perturbation series: Application to the vibrational states of H{sub 2}CO molecule

Energy Technology Data Exchange (ETDEWEB)

Duchko, A. N. [National Research Tomsk Polytechnic University, Tomsk (Russian Federation); V.E. Zuev Institute of Atmospheric Optics, Tomsk (Russian Federation); Bykov, A. D., E-mail: adbykov@rambler.ru [V.E. Zuev Institute of Atmospheric Optics, Tomsk (Russian Federation)

2015-10-21

Large-order Rayleigh–Schrödinger perturbation theory (RSPT) is applied to the calculation of anharmonic vibrational energy levels of H{sub 2}CO molecule. We use the model of harmonic oscillators perturbed by anharmonic terms of potential energy. Since the perturbation series typically diverge due to strong couplings, we apply the algebraic approximation technique because of its effectiveness shown earlier by Goodson and Sergeev [J. Chem. Phys. 110, 8205 (1999); ibid. 124, 094111 (2006)] and in our previous articles [A. D. Bykov et al. Opt. Spectrosc. 114, 396 (2013); ibid. 116, 598 (2014)]. To facilitate the resummation of terms contributing to perturbed states, when resonance mixing between states is especially strong and perturbation series diverge very quick, we used repartition of the Hamiltonian by shifting the normal mode frequencies. Energy levels obtained by algebraic approximants were compared with the results of variational calculation. It was found that for low energy states (up to ∼5000 cm{sup −1}), algebraic approximants gave accurate values of energy levels, which were in excellent agreement with the variational method. For highly excited states, strong and multiple resonances complicate series resummation, but a suitable change of normal mode frequencies allows one to reduce the resonance mixing and to get accurate energy levels. The theoretical background of the problem of RSPT series divergence is discussed along with its numerical analysis. For these purposes, the vibrational energy is considered as a function of a complex perturbation parameter. Layout and classification of its singularities allow us to model the asymptotic behavior of the perturbation series and prove the robustness of the algorithm.

Variation Trend Analysis of Runoff and Sediment Time Series Based on the R/S Analysis of Simulated Loess Tilled Slopes in the Loess Plateau, China

Directory of Open Access Journals (Sweden)

Ju Zhang

2017-12-01

Full Text Available The objective of this study was to illustrate the temporal variation of runoff and sediment of loess tilled slopes under successive rainfall conditions. Loess tilled slopes with four microtopography types (straight cultivated slope, artificial backhoe, artificial digging, and contour tillage under five slope gradients (5°, 10°, 15°, 20°, 25° were simulated and a rainfall intensity of 60 mm/h was adopted. The temporal trends of runoff and sediment yield were predicted based on the Rescaled Range (R/S analysis method. The results indicate that the Hurst indices of runoff time series and sediment time series are higher than 0.5, and a long-term positive correlation exists between the future and the past. This means that runoff and sediment of loess tilled slopes in the future will have the same trends as in the past. The results obtained by the classical R/S analysis method were the same as those of the modified R/S analysis method. The rationality and reliability of the R/S analysis method were further identified and the method can be used for predicting the trend of runoff and sediment yield. The correlation between the microtopography and the Hurst indices of the runoff and sediment yield time series, as well as between the slopes and the Hurst indices, were tested, and the result was that there was no significant correlation between them. The microtopography and slopes cannot affect the correlation and continuity of runoff and sediment yield time series. This study provides an effective method for predicting variations in the trends of runoff and sediment yield on loess tilled slopes.

Multiscale simulation of yield strength in reduced-activation ferritic/martensitic steel

Energy Technology Data Exchange (ETDEWEB)

Wang, Chen Chong; Zhang, Chi; Yang, Zhigang [Key Laboratory of Advanced Materials of Ministry of Education, School of Materials Science and Engineering, Tsinghua University, Beijing (China); Zhao, Ji Jun [State Key Laboratory of Materials Modification by Laser, Electron, and Ion Beams, School of Physics and Optoelectronic Technology and College of Advanced Science and Technology, Dalian University of Technology, Dalian (China)

2017-04-15

One of the important requirements for the application of reduced-activation ferritic/martensitic (RAFM) steel is to retain proper mechanical properties under irradiation and high-temperature conditions. To simulate the yield strength and stress-strain curve of steels during high-temperature and irradiation conditions, a multiscale simulation method consisting of both microstructure and strengthening simulations was established. The simulation results of microstructure parameters were added to a superposition strengthening model, which consisted of constitutive models of different strengthening methods. Based on the simulation results, the strength contribution for different strengthening methods at both room temperature and high-temperature conditions was analyzed. The simulation results of the yield strength in irradiation and high-temperature conditions were mainly consistent with the experimental results. The optimal application field of this multiscale model was 9Cr series (7–9 wt.%Cr) RAFM steels in a condition characterized by 0.1–5 dpa (or 0 dpa) and a temperature range of 25–500°C.

Field Measurements of Black Carbon Yields from Gas Flaring.

Science.gov (United States)

Conrad, Bradley M; Johnson, Matthew R

2017-02-07

Black carbon (BC) emissions from gas flaring in the oil and gas industry are postulated to have critical impacts on climate and public health, but actual emission rates remain poorly characterized. This paper presents in situ field measurements of BC emission rates and flare gas volume-specific BC yields for a diverse range of flares. Measurements were performed during a series of field campaigns in Mexico and Ecuador using the sky-LOSA optical measurement technique, in concert with comprehensive Monte Carlo-based uncertainty analyses. Parallel on-site measurements of flare gas flow rate and composition were successfully performed at a subset of locations enabling direct measurements of fuel-specific BC yields from flares under field conditions. Quantified BC emission rates from individual flares spanned more than 4 orders of magnitude (up to 53.7 g/s). In addition, emissions during one notable ∼24-h flaring event (during which the plume transmissivity dropped to zero) would have been even larger than this maximum rate, which was measured as this event was ending. This highlights the likely importance of superemitters to global emission inventories. Flare gas volume-specific BC yields were shown to be strongly correlated with flare gas heating value. A newly derived correlation fitting current field data and previous lab data suggests that, in the context of recent studies investigating transport of flare-generated BC in the Arctic and globally, impacts of flaring in the energy industry may in fact be underestimated.

A 40 Year Time Series of SBUV Observations: the Version 8.6 Processing

Science.gov (United States)

McPeters, Richard; Bhartia, P. K.; Flynn, L.

2012-01-01

Under a NASA program to produce long term data records from instruments on multiple satellites (MEaSUREs), data from a series of eight SBUV and SBUV 12 instruments have been reprocessed to create a 40 year long ozone time series. Data from the Nimbus 4 BUV, Nimbus 7 SBUV, and SBUV/2 instruments on NOAA 9, 11, 14, 16, 17, and 18 were used covering the period 1970 to 1972 and 1979 to the present. In past analyses an ozone time series was created from these instruments by adjusting ozone itself, instrument by instrument, for consistency during overlap periods. In the version 8.6 processing adjustments were made to the radiance calibration of each instrument to maintain a consistent calibration over the entire time series. Data for all eight instruments were then reprocessed using the adjusted radiances. Reprocessing is necessary to produce an accurate latitude dependence. Other improvements incorporated in version 8.6 included the use of the ozone cross sections of Brion, Daumont, and Malicet, and the use of a cloud height climatology derived from Aura OMI measurements. The new cross sections have a more accurate temperature dependence than the cross sections previously used. The OMI-based cloud heights account for the penetration of UV into the upper layers of clouds. The consistency of the version 8.6 time series was evaluated by intra-instrument comparisons during overlap periods, comparisons with ground-based instruments, and comparisons with measurements made by instruments on other satellites such as SAGE II and UARS MLS. These comparisons show that for the instruments on NOAA 16, 17 and 18, the instrument calibrations were remarkably stable and consistent from instrument to instrument. The data record from the Nimbus 7 SBUV was also very stable, and SAGE and ground-based comparisons show that the' calibration was consistent with measurements made years laterby the NOAA 16 instrument. The calibrations of the SBUV/2 instruments on NOAA 9, 11, and 14 were more of

Estimation of 305 Day Milk Yield from Cumulative Monthly and Bimonthly Test Day Records in Indonesian Holstein Cattle

Science.gov (United States)

Rahayu, A. P.; Hartatik, T.; Purnomoadi, A.; Kurnianto, E.

2018-02-01

The aims of this study were to estimate 305 day first lactation milk yield of Indonesian Holstein cattle from cumulative monthly and bimonthly test day records and to analyze its accuracy.The first lactation records of 258 dairy cows from 2006 to 2014 consisted of 2571 monthly (MTDY) and 1281 bimonthly test day yield (BTDY) records were used. Milk yields were estimated by regression method. Correlation coefficients between actual and estimated milk yield by cumulative MTDY were 0.70, 0.78, 0.83, 0.86, 0.89, 0.92, 0.94 and 0.96 for 2-9 months, respectively, meanwhile by cumulative BTDY were 0.69, 0.81, 0.87 and 0.92 for 2, 4, 6 and 8 months, respectively. The accuracy of fitting regression models (R2) increased with the increasing in the number of cumulative test day used. The used of 5 cumulative MTDY was considered sufficient for estimating 305 day first lactation milk yield with 80.6% accuracy and 7% error percentage of estimation. The estimated milk yield from MTDY was more accurate than BTDY by 1.1 to 2% less error percentage in the same time.

[Prediction of the side-cut product yield of atmospheric/vacuum distillation unit by NIR crude oil rapid assay].

Science.gov (United States)

Wang, Yan-Bin; Hu, Yu-Zhong; Li, Wen-Le; Zhang, Wei-Song; Zhou, Feng; Luo, Zhi

2014-10-01

In the present paper, based on the fast evaluation technique of near infrared, a method to predict the yield of atmos- pheric and vacuum line was developed, combined with H/CAMS software. Firstly, the near-infrared (NIR) spectroscopy method for rapidly determining the true boiling point of crude oil was developed. With commercially available crude oil spectroscopy da- tabase and experiments test from Guangxi Petrochemical Company, calibration model was established and a topological method was used as the calibration. The model can be employed to predict the true boiling point of crude oil. Secondly, the true boiling point based on NIR rapid assay was converted to the side-cut product yield of atmospheric/vacuum distillation unit by H/CAMS software. The predicted yield and the actual yield of distillation product for naphtha, diesel, wax and residual oil were compared in a 7-month period. The result showed that the NIR rapid crude assay can predict the side-cut product yield accurately. The near infrared analytic method for predicting yield has the advantages of fast analysis, reliable results, and being easy to online operate, and it can provide elementary data for refinery planning optimization and crude oil blending.

Tunneling effects in electromagnetic wave scattering by nonspherical particles: A comparison of the Debye series and physical-geometric optics approximations

International Nuclear Information System (INIS)

Bi, Lei; Yang, Ping

2016-01-01

The accuracy of the physical-geometric optics (PG-O) approximation is examined for the simulation of electromagnetic scattering by nonspherical dielectric particles. This study seeks a better understanding of the tunneling effect on the phase matrix by employing the invariant imbedding method to rigorously compute the zeroth-order Debye series, from which the tunneling efficiency and the phase matrix corresponding to the diffraction and external reflection are obtained. The tunneling efficiency is shown to be a factor quantifying the relative importance of the tunneling effect over the Fraunhofer diffraction near the forward scattering direction. Due to the tunneling effect, different geometries with the same projected cross section might have different diffraction patterns, which are traditionally assumed to be identical according to the Babinet principle. For particles with a fixed orientation, the PG-O approximation yields the external reflection pattern with reasonable accuracy, but ordinarily fails to predict the locations of peaks and minima in the diffraction pattern. The larger the tunneling efficiency, the worse the PG-O accuracy is at scattering angles less than 90°. If the particles are assumed to be randomly oriented, the PG-O approximation yields the phase matrix close to the rigorous counterpart, primarily due to error cancellations in the orientation-average process. Furthermore, the PG-O approximation based on an electric field volume-integral equation is shown to usually be much more accurate than the Kirchhoff surface integral equation at side-scattering angles, particularly when the modulus of the complex refractive index is close to unity. Finally, tunneling efficiencies are tabulated for representative faceted particles. - Highlights: • Concepts of diffraction, reflection and tunneling are refined. • The diffraction together with reflection is rigorously treated. • An improved invariant imbedding method is employed to compute the Debye

Circumstances under which various approximate relativistic and nonrelativistic theories yield accurate Compton scattering doubly differential cross sections at high photon energy

International Nuclear Information System (INIS)

LaJohn, L A; Pratt, R H

2009-01-01

We discuss the increase in error with increasing nuclear charge Z in the use of the relativistic impulse approximation (RIA) for the calculation of Compton K-shell scattering doubly differential cross sections (DDCS). We also show that nonrelativistic (nr) expressions can be used to obtain accurate peak region DDCS at scattering angles less than about 35 0 even at incident photon energies ω i exceeding 1 MeV, if Z<30. This is possible because in the Compton peak region, as θ→0, a low momentum transfer limit is being approached.

Effects of cutting frequency on alfalfa yield and yield components in ...

African Journals Online (AJOL)

Effects of cutting frequency on alfalfa yield and yield components in Songnen Plain, Northeast China. J Chen, F Tang, R Zhu, C Gao, G Di, Y Zhang. Abstract. The productivity and quality of alfalfa (Medicago sativa L.) is strongly influenced by cutting frequency (F). To clarify that the yield and quality of alfalfa if affected by F, ...

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

Science.gov (United States)

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

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

Directory of Open Access Journals (Sweden)

Xinpeng Xu

Full Text Available 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.

Science.gov (United States)

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.

The ATOMFT integrator - Using Taylor series to solve ordinary differential equations

Science.gov (United States)

Berryman, Kenneth W.; Stanford, Richard H.; Breckheimer, Peter J.

1988-01-01

This paper discusses the application of ATOMFT, an integration package based on Taylor series solution with a sophisticated user interface. ATOMFT has the capabilities to allow the implementation of user defined functions and the solution of stiff and algebraic equations. Detailed examples, including the solutions to several astrodynamics problems, are presented. Comparisons with its predecessor ATOMCC and other modern integrators indicate that ATOMFT is a fast, accurate, and easy method to use to solve many differential equation problems.

Development and application of a modified dynamic time warping algorithm (DTW-S to analyses of primate brain expression time series

Directory of Open Access Journals (Sweden)

Vingron Martin

2011-08-01

Full Text Available Abstract Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Can tritiated water-dilution space accurately predict total body water in chukar partridges

International Nuclear Information System (INIS)

Crum, B.G.; Williams, J.B.; Nagy, K.A.

1985-01-01

Total body water (TBW) volumes determined from the dilution space of injected tritiated water have consistently overestimated actual water volumes (determined by desiccation to constant mass) in reptiles and mammals, but results for birds are controversial. We investigated potential errors in both the dilution method and the desiccation method in an attempt to resolve this controversy. Tritiated water dilution yielded an accurate measurement of water mass in vitro. However, in vivo, this method yielded a 4.6% overestimate of the amount of water (3.1% of live body mass) in chukar partridges, apparently largely because of loss of tritium from body water to sites of dissociable hydrogens on body solids. An additional source of overestimation (approximately 2% of body mass) was loss of tritium to the solids in blood samples during distillation of blood to obtain pure water for tritium analysis. Measuring tritium activity in plasma samples avoided this problem but required measurement of, and correction for, the dry matter content in plasma. Desiccation to constant mass by lyophilization or oven-drying also overestimated the amount of water actually in the bodies of chukar partridges by 1.4% of body mass, because these values included water adsorbed onto the outside of feathers. When desiccating defeathered carcasses, oven-drying at 70 degrees C yielded TBW values identical to those obtained from lyophilization, but TBW was overestimated (0.5% of body mass) by drying at 100 degrees C due to loss of organic substances as well as water

A Methodology to Infer Crop Yield Response to Climate Variability and Change Using Long-Term Observations

Directory of Open Access Journals (Sweden)

Manfred A. Lange

2013-11-01

Full Text Available A new methodology to extract crop yield response to climate variability and change from long-term crop yield observations is presented in this study. In contrast to the existing first-difference approach (FDA, the proposed methodology considers that the difference in value between crop yields of two consecutive years reflects necessarily the contributions of climate and management conditions, especially at large spatial scales where both conditions may vary significantly from one year to the next. Our approach was applied to remove the effect of non-climatic factors on crop yield and, hence, to isolate the effect of the observed climate change between 1961 and 2006 on three widely crops grown in three Mediterranean countries—namely wheat, corn and potato—using national-level crop yield observations’ time-series. Obtained results show that the proposed methodology provides us with a ground basis to improve substantially our understanding of crop yield response to climate change at a scale that is relevant to large-scale estimations of agricultural production and to food security analyses; and therefore to reduce uncertainties in estimations of potential climate change effects on agricultural production. Furthermore, a comparison of outputs of our methodology and FDA outputs yielded a difference in terms of maize production in Egypt, for example, that exceeds the production of some neighbouring countries.

Assessing Coupling Dynamics from an Ensemble of Time Series

Directory of Open Access Journals (Sweden)

Germán Gómez-Herrero

2015-04-01

Full Text Available Finding interdependency relations between time series provides valuable knowledge about the processes that generated the signals. Information theory sets a natural framework for important classes of statistical dependencies. However, a reliable estimation from information-theoretic functionals is hampered when the dependency to be assessed is brief or evolves in time. Here, we show that these limitations can be partly alleviated when we have access to an ensemble of independent repetitions of the time series. In particular, we gear a data-efficient estimator of probability densities to make use of the full structure of trial-based measures. By doing so, we can obtain time-resolved estimates for a family of entropy combinations (including mutual information, transfer entropy and their conditional counterparts, which are more accurate than the simple average of individual estimates over trials. We show with simulated and real data generated by coupled electronic circuits that the proposed approach allows one to recover the time-resolved dynamics of the coupling between different subsystems.

Causal strength induction from time series data.

Science.gov (United States)

Soo, Kevin W; Rottman, Benjamin M

2018-04-01

One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Spectrally accurate contour dynamics

International Nuclear Information System (INIS)

Van Buskirk, R.D.; Marcus, P.S.

1994-01-01

We present an exponentially accurate boundary integral method for calculation the equilibria and dynamics of piece-wise constant distributions of potential vorticity. The method represents contours of potential vorticity as a spectral sum and solves the Biot-Savart equation for the velocity by spectrally evaluating a desingularized contour integral. We use the technique in both an initial-value code and a newton continuation method. Our methods are tested by comparing the numerical solutions with known analytic results, and it is shown that for the same amount of computational work our spectral methods are more accurate than other contour dynamics methods currently in use

Facile synthesis of the cyclohexane fragment of enacloxins, a series of antibiotics isolated from Frateuria sp. W-315.

Science.gov (United States)

Saito, Aki; Igarashi, Wataru; Furukawa, Hiroyuki; Yamada, Teiko; Kuwahara, Shigefumi; Kiyota, Hiromasa

2014-01-01

An efficient and good yield synthesis of the cyclohexane moiety of enacyloxins, a series of antibiotics isolated from Frateuria sp. W-315, was achieved from d-quinic acid using a successive Barton-McCombie deoxygenation.

Statistical inference for classification of RRIM clone series using near IR reflectance properties

Science.gov (United States)

Ismail, Faridatul Aima; Madzhi, Nina Korlina; Hashim, Hadzli; Abdullah, Noor Ezan; Khairuzzaman, Noor Aishah; Azmi, Azrie Faris Mohd; Sampian, Ahmad Faiz Mohd; Harun, Muhammad Hafiz

2015-08-01

RRIM clone is a rubber breeding series produced by RRIM (Rubber Research Institute of Malaysia) through "rubber breeding program" to improve latex yield and producing clones attractive to farmers. The objective of this work is to analyse measurement of optical sensing device on latex of selected clone series. The device using transmitting NIR properties and its reflectance is converted in terms of voltage. The obtained reflectance index value via voltage was analyzed using statistical technique in order to find out the discrimination among the clones. From the statistical results using error plots and one-way ANOVA test, there is an overwhelming evidence showing discrimination of RRIM 2002, RRIM 2007 and RRIM 3001 clone series with p value = 0.000. RRIM 2008 cannot be discriminated with RRIM 2014; however both of these groups are distinct from the other clones.

Analyzing a stochastic time series obeying a second-order differential equation.

Science.gov (United States)

Lehle, B; Peinke, J

2015-06-01

The stochastic properties of a Langevin-type Markov process can be extracted from a given time series by a Markov analysis. Also processes that obey a stochastically forced second-order differential equation can be analyzed this way by employing a particular embedding approach: To obtain a Markovian process in 2N dimensions from a non-Markovian signal in N dimensions, the system is described in a phase space that is extended by the temporal derivative of the signal. For a discrete time series, however, this derivative can only be calculated by a differencing scheme, which introduces an error. If the effects of this error are not accounted for, this leads to systematic errors in the estimation of the drift and diffusion functions of the process. In this paper we will analyze these errors and we will propose an approach that correctly accounts for them. This approach allows an accurate parameter estimation and, additionally, is able to cope with weak measurement noise, which may be superimposed to a given time series.

Prediction of winter wheat high yield from remote sensing based model: application in United States and Ukraine

Science.gov (United States)

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.

Particle mass yield in secondary organic aerosol formed by the dark ozonolysis of α-pinene

Directory of Open Access Journals (Sweden)

J. E. Shilling

2008-04-01

Full Text Available The yield of particle mass in secondary organic aerosol (SOA formed by dark ozonolysis was measured for 0.3–22.8 ppbv of reacted α-pinene. Most experiments were conducted using a continuous-flow chamber, allowing nearly constant SOA concentration and chemical composition for several days. For comparison, some experiments were also conducted in batch mode. Reaction conditions were 25°C, 40% RH, dry (NH₄SO₄ seed particles, and excess 1-butanol. The organic particle loading was independently measured by an aerosol mass spectrometer and a scanning mobility particle sizer, and the two measurements agreed well. The observations showed that SOA formation occurred for even the lowest reacted α-pinene concentration of 0.3 ppbv. The particle mass yield was 0.09 at 0.15 μg m⁻³, increasing to 0.27 at 40 μg m⁻³. Compared to some results reported in the literature, the yields were 80 to 100% larger for loadings above 2 μg m⁻³. At lower loadings, the yields had an offset of approximately +0.07 from those reported in the literature. To as low as 0.15 μm⁻³, the yield curve had no inflection point toward null yield, implying the formation of one or several products having vapor pressures below this value. These observations of increased yields, especially for low loadings, are potentially important for accurate prediction by chemical transport models of organic particle concentrations in the ambient atmosphere.

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

Science.gov (United States)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Yielding the yield-stress analysis: a study focused on the effects of elasticity on the settling of a single spherical particle in simple yield-stress fluids.

Science.gov (United States)

Fraggedakis, D; Dimakopoulos, Y; Tsamopoulos, J

2016-06-28

The sedimentation of a single particle in materials that exhibit simultaneously elastic, viscous and plastic behavior is examined in an effort to explain phenomena that contradict the nature of purely yield-stress materials. Such phenomena include the loss of the fore-and-aft symmetry with respect to an isolated settling particle under creeping flow conditions and the appearance of the "negative wake" behind it. Despite the fact that similar observations have been reported in studies involving viscoelastic fluids, researchers conjectured that thixotropy is responsible for these phenomena, as the aging of yield-stress materials is another common feature. By means of transient calculations, we study the effect of elasticity on both the fluidized and the solid phase. The latter is considered to behave as an ideal Hookean solid. The material properties of the model are determined under the isotropic kinematic hardening framework via Large Amplitude Oscillatory Shear (LAOS) measurements. In this way, we are able to predict accurately the unusual phenomena observed in experiments with simple yield-stress materials, irrespective of the appearance of slip on the particle surface. Viscoelasticity favors the formation of intense shear and extensional stresses downstream of the particle, significantly changing the entrapment mechanism in comparison to that observed in viscoplastic fluids. Therefore, the critical conditions under which the entrapment of the particle occurs deviate from the well-known criterion established theoretically by Beris et al. (1985) and verified experimentally by Tabuteau et al. (2007) for similar materials under conditions that elastic effects are negligible. Our predictions are in quantitative agreement with published experimental results by Holenberg et al. (2012) on the loss of the fore-aft symmetry and the formation of the negative wake in Carbopol with well-characterized rheology. Additionally, we propose simple expressions for the Stokes drag

A series solution for horizontal infiltration in an initially dry aquifer

Science.gov (United States)

Furtak-Cole, Eden; Telyakovskiy, Aleksey S.; Cooper, Clay A.

2018-06-01

The porous medium equation (PME) is a generalization of the traditional Boussinesq equation for hydraulic conductivity as a power law function of height. We analyze the horizontal recharge of an initially dry unconfined aquifer of semi-infinite extent, as would be found in an aquifer adjacent a rising river. If the water level can be modeled as a power law function of time, similarity variables can be introduced and the original problem can be reduced to a boundary value problem for a nonlinear ordinary differential equation. The position of the advancing front is not known ahead of time and must be found in the process of solution. We present an analytical solution in the form of a power series, with the coefficients of the series given by a recurrence relation. The analytical solution compares favorably with a highly accurate numerical solution, and only a small number of terms of the series are needed to achieve high accuracy in the scenarios considered here. We also conduct a series of physical experiments in an initially dry wedged Hele-Shaw cell, where flow is modeled by a special form of the PME. Our analytical solution closely matches the hydraulic head profiles in the Hele-Shaw cell experiment.

Bond yield curve construction

Directory of Open Access Journals (Sweden)

Kožul Nataša

2014-01-01

Full Text Available In the broadest sense, yield curve indicates the market's view of the evolution of interest rates over time. However, given that cost of borrowing it closely linked to creditworthiness (ability to repay, different yield curves will apply to different currencies, market sectors, or even individual issuers. As government borrowing is indicative of interest rate levels available to other market players in a particular country, and considering that bond issuance still remains the dominant form of sovereign debt, this paper describes yield curve construction using bonds. The relationship between zero-coupon yield, par yield and yield to maturity is given and their usage in determining curve discount factors is described. Their usage in deriving forward rates and pricing related derivative instruments is also discussed.

Typical Periods for Two-Stage Synthesis by Time-Series Aggregation with Bounded Error in Objective Function

Energy Technology Data Exchange (ETDEWEB)

Bahl, Björn; Söhler, Theo; Hennen, Maike; Bardow, André, E-mail: andre.bardow@ltt.rwth-aachen.de [Institute of Technical Thermodynamics, RWTH Aachen University, Aachen (Germany)

2018-01-08

Two-stage synthesis problems simultaneously consider here-and-now decisions (e.g., optimal investment) and wait-and-see decisions (e.g., optimal operation). The optimal synthesis of energy systems reveals such a two-stage character. The synthesis of energy systems involves multiple large time series such as energy demands and energy prices. Since problem size increases with the size of the time series, synthesis of energy systems leads to complex optimization problems. To reduce the problem size without loosing solution quality, we propose a method for time-series aggregation to identify typical periods. Typical periods retain the chronology of time steps, which enables modeling of energy systems, e.g., with storage units or start-up cost. The aim of the proposed method is to obtain few typical periods with few time steps per period, while accurately representing the objective function of the full time series, e.g., cost. Thus, we determine the error of time-series aggregation as the cost difference between operating the optimal design for the aggregated time series and for the full time series. Thereby, we rigorously bound the maximum performance loss of the optimal energy system design. In an initial step, the proposed method identifies the best length of typical periods by autocorrelation analysis. Subsequently, an adaptive procedure determines aggregated typical periods employing the clustering algorithm k-medoids, which groups similar periods into clusters and selects one representative period per cluster. Moreover, the number of time steps per period is aggregated by a novel clustering algorithm maintaining chronology of the time steps in the periods. The method is iteratively repeated until the error falls below a threshold value. A case study based on a real-world synthesis problem of an energy system shows that time-series aggregation from 8,760 time steps to 2 typical periods with each 2 time steps results in an error smaller than the optimality gap of

Simultaneous determination of radionuclides separable into natural decay series by use of time-interval analysis

International Nuclear Information System (INIS)

Hashimoto, Tetsuo; Sanada, Yukihisa; Uezu, Yasuhiro

2004-01-01

A delayed coincidence method, time-interval analysis (TIA), has been applied to successive α-α decay events on the millisecond time-scale. Such decay events are part of the 220 Rn→ 216 Po (T 1/2 145 ms) (Th-series) and 219 Rn→ 215 Po (T 1/2 1.78 ms) (Ac-series). By using TIA in addition to measurement of 226 Ra (U-series) from α-spectrometry by liquid scintillation counting (LSC), two natural decay series could be identified and separated. The TIA detection efficiency was improved by using the pulse-shape discrimination technique (PSD) to reject β-pulses, by solvent extraction of Ra combined with simple chemical separation, and by purging the scintillation solution with dry N 2 gas. The U- and Th-series together with the Ac-series were determined, respectively, from alpha spectra and TIA carried out immediately after Ra-extraction. Using the 221 Fr→ 217 At (T 1/2 32.3 ms) decay process as a tracer, overall yields were estimated from application of TIA to the 225 Ra (Np-decay series) at the time of maximum growth. The present method has proven useful for simultaneous determination of three radioactive decay series in environmental samples. (orig.)

Can phenological models predict tree phenology accurately under climate change conditions?

Science.gov (United States)

Chuine, Isabelle; Bonhomme, Marc; Legave, Jean Michel; García de Cortázar-Atauri, Inaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry

2014-05-01

or compromise dormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budburst dates only, with no information on the dormancy break date because this information is very scarce. We evaluated the efficiency of a set of process-based phenological models to accurately predict the dormancy break dates of four fruit trees. Our results show that models calibrated solely with flowering or budburst dates do not accurately predict the dormancy break date. Providing dormancy break date for the model parameterization results in much more accurate simulation of this latter, with however a higher error than that on flowering or bud break dates. But most importantly, we show also that models not calibrated with dormancy break dates can generate significant differences in forecasted flowering or bud break dates when using climate scenarios. Our results claim for the urgent need of massive measurements of dormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future.

Spectral Unmixing Analysis of Time Series Landsat 8 Images

Science.gov (United States)

Zhuo, R.; Xu, L.; Peng, J.; Chen, Y.

2018-05-01

Temporal analysis of Landsat 8 images opens up new opportunities in the unmixing procedure. Although spectral analysis of time series Landsat imagery has its own advantage, it has rarely been studied. Nevertheless, using the temporal information can provide improved unmixing performance when compared to independent image analyses. Moreover, different land cover types may demonstrate different temporal patterns, which can aid the discrimination of different natures. Therefore, this letter presents time series K-P-Means, a new solution to the problem of unmixing time series Landsat imagery. The proposed approach is to obtain the "purified" pixels in order to achieve optimal unmixing performance. The vertex component analysis (VCA) is used to extract endmembers for endmember initialization. First, nonnegative least square (NNLS) is used to estimate abundance maps by using the endmember. Then, the estimated endmember is the mean value of "purified" pixels, which is the residual of the mixed pixel after excluding the contribution of all nondominant endmembers. Assembling two main steps (abundance estimation and endmember update) into the iterative optimization framework generates the complete algorithm. Experiments using both simulated and real Landsat 8 images show that the proposed "joint unmixing" approach provides more accurate endmember and abundance estimation results compared with "separate unmixing" approach.

Predicting watershed post-fire sediment yield with the InVEST sediment retention model: Accuracy and uncertainties

Science.gov (United States)

Sankey, Joel B.; McVay, Jason C.; Kreitler, Jason R.; Hawbaker, Todd J.; Vaillant, Nicole; Lowe, Scott

2015-01-01

Increased sedimentation following wildland fire can negatively impact water supply and water quality. Understanding how changing fire frequency, extent, and location will affect watersheds and the ecosystem services they supply to communities is of great societal importance in the western USA and throughout the world. In this work we assess the utility of the InVEST (Integrated Valuation of Ecosystem Services and Tradeoffs) Sediment Retention Model to accurately characterize erosion and sedimentation of burned watersheds. InVEST was developed by the Natural Capital Project at Stanford University (Tallis et al., 2014) and is a suite of GIS-based implementations of common process models, engineered for high-end computing to allow the faster simulation of larger landscapes and incorporation into decision-making. The InVEST Sediment Retention Model is based on common soil erosion models (e.g., USLE – Universal Soil Loss Equation) and determines which areas of the landscape contribute the greatest sediment loads to a hydrological network and conversely evaluate the ecosystem service of sediment retention on a watershed basis. In this study, we evaluate the accuracy and uncertainties for InVEST predictions of increased sedimentation after fire, using measured postfire sediment yields available for many watersheds throughout the western USA from an existing, published large database. We show that the model can be parameterized in a relatively simple fashion to predict post-fire sediment yield with accuracy. Our ultimate goal is to use the model to accurately predict variability in post-fire sediment yield at a watershed scale as a function of future wildfire conditions.

Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions.

Science.gov (United States)

Kawai, Nobuyuki; He, Hongshen

2016-01-01

Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish) under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise). We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions.

Breaking Snake Camouflage: Humans Detect Snakes More Accurately than Other Animals under Less Discernible Visual Conditions.

Directory of Open Access Journals (Sweden)

Nobuyuki Kawai

Full Text Available Humans and non-human primates are extremely sensitive to snakes as exemplified by their ability to detect pictures of snakes more quickly than those of other animals. These findings are consistent with the Snake Detection Theory, which hypothesizes that as predators, snakes were a major source of evolutionary selection that favored expansion of the visual system of primates for rapid snake detection. Many snakes use camouflage to conceal themselves from both prey and their own predators, making it very challenging to detect them. If snakes have acted as a selective pressure on primate visual systems, they should be more easily detected than other animals under difficult visual conditions. Here we tested whether humans discerned images of snakes more accurately than those of non-threatening animals (e.g., birds, cats, or fish under conditions of less perceptual information by presenting a series of degraded images with the Random Image Structure Evolution technique (interpolation of random noise. We find that participants recognize mosaic images of snakes, which were regarded as functionally equivalent to camouflage, more accurately than those of other animals under dissolved conditions. The present study supports the Snake Detection Theory by showing that humans have a visual system that accurately recognizes snakes under less discernible visual conditions.

On Sums of Numerical Series and Fourier Series

Science.gov (United States)

Pavao, H. Germano; de Oliveira, E. Capelas

2008-01-01

We discuss a class of trigonometric functions whose corresponding Fourier series, on a conveniently chosen interval, can be used to calculate several numerical series. Particular cases are presented and two recent results involving numerical series are recovered. (Contains 1 note.)

Time Series Analysis, Modeling and Applications A Computational Intelligence Perspective

CERN Document Server

Chen, Shyi-Ming

2013-01-01

Temporal and spatiotemporal data form an inherent fabric of the society as we are faced with streams of data coming from numerous sensors, data feeds, recordings associated with numerous areas of application embracing physical and human-generated phenomena (environmental data, financial markets, Internet activities, etc.). A quest for a thorough analysis, interpretation, modeling and prediction of time series comes with an ongoing challenge for developing models that are both accurate and user-friendly (interpretable). The volume is aimed to exploit the conceptual and algorithmic framework of Computational Intelligence (CI) to form a cohesive and comprehensive environment for building models of time series. The contributions covered in the volume are fully reflective of the wealth of the CI technologies by bringing together ideas, algorithms, and numeric studies, which convincingly demonstrate their relevance, maturity and visible usefulness. It reflects upon the truly remarkable diversity of methodological a...

7755 EFFECT OF NPK FERTILIZER ON FRUIT YIELD AND YIELD ...

African Journals Online (AJOL)

Win7Ent

2013-06-03

Jun 3, 2013 ... peasant farmers in Nigeria. With the increased ... did not significantly (p=0.05) increase the fruit yield nor the seed yield. Key words: NPK fertilizer, Fruit ..... SAS (Statistical Analysis System) Version 9.1. SAS Institute Inc., Cary, ...

Modeling seasonal leptospirosis transmission and its association with rainfall and temperature in Thailand using time-series and ARIMAX analyses.

Science.gov (United States)

Chadsuthi, Sudarat; Modchang, Charin; Lenbury, Yongwimon; Iamsirithaworn, Sopon; Triampo, Wannapong

2012-07-01

To study the number of leptospirosis cases in relations to the seasonal pattern, and its association with climate factors. Time series analysis was used to study the time variations in the number of leptospirosis cases. The Autoregressive Integrated Moving Average (ARIMA) model was used in data curve fitting and predicting the next leptospirosis cases. We found that the amount of rainfall was correlated to leptospirosis cases in both regions of interest, namely the northern and northeastern region of Thailand, while the temperature played a role in the northeastern region only. The use of multivariate ARIMA (ARIMAX) model showed that factoring in rainfall (with an 8 months lag) yields the best model for the northern region while the model, which factors in rainfall (with a 10 months lag) and temperature (with an 8 months lag) was the best for the northeastern region. The models are able to show the trend in leptospirosis cases and closely fit the recorded data in both regions. The models can also be used to predict the next seasonal peak quite accurately. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

Infinite series

CERN Document Server

Hirschman, Isidore Isaac

2014-01-01

This text for advanced undergraduate and graduate students presents a rigorous approach that also emphasizes applications. Encompassing more than the usual amount of material on the problems of computation with series, the treatment offers many applications, including those related to the theory of special functions. Numerous problems appear throughout the book.The first chapter introduces the elementary theory of infinite series, followed by a relatively complete exposition of the basic properties of Taylor series and Fourier series. Additional subjects include series of functions and the app

Real coded genetic algorithm for fuzzy time series prediction

Science.gov (United States)

Jain, Shilpa; Bisht, Dinesh C. S.; Singh, Phool; Mathpal, Prakash C.

2017-10-01

Genetic Algorithm (GA) forms a subset of evolutionary computing, rapidly growing area of Artificial Intelligence (A.I.). Some variants of GA are binary GA, real GA, messy GA, micro GA, saw tooth GA, differential evolution GA. This research article presents a real coded GA for predicting enrollments of University of Alabama. Data of Alabama University is a fuzzy time series. Here, fuzzy logic is used to predict enrollments of Alabama University and genetic algorithm optimizes fuzzy intervals. Results are compared to other eminent author works and found satisfactory, and states that real coded GA are fast and accurate.

Response of Yield and Yield Components of Tef [Eragrostis Tef ...

African Journals Online (AJOL)

The partial budget analysis also indicates that applications of 46 kg. N ha-1 and 10 kg P ha-1 are ..... (1994) indicated that where the grain yield response is negative, yield reduction is primarily caused by a .... An Economic Training. Manual.

Accurate Quantitative Sensing of Intracellular pH based on Self-ratiometric Upconversion Luminescent Nanoprobe.

Science.gov (United States)

Li, Cuixia; Zuo, Jing; Zhang, Li; Chang, Yulei; Zhang, Youlin; Tu, Langping; Liu, Xiaomin; Xue, Bin; Li, Qiqing; Zhao, Huiying; Zhang, Hong; Kong, Xianggui

2016-12-09

Accurate quantitation of intracellular pH (pH i ) is of great importance in revealing the cellular activities and early warning of diseases. A series of fluorescence-based nano-bioprobes composed of different nanoparticles or/and dye pairs have already been developed for pH i sensing. Till now, biological auto-fluorescence background upon UV-Vis excitation and severe photo-bleaching of dyes are the two main factors impeding the accurate quantitative detection of pH i . Herein, we have developed a self-ratiometric luminescence nanoprobe based on förster resonant energy transfer (FRET) for probing pH i , in which pH-sensitive fluorescein isothiocyanate (FITC) and upconversion nanoparticles (UCNPs) were served as energy acceptor and donor, respectively. Under 980 nm excitation, upconversion emission bands at 475 nm and 645 nm of NaYF 4 :Yb 3+ , Tm 3+ UCNPs were used as pH i response and self-ratiometric reference signal, respectively. This direct quantitative sensing approach has circumvented the traditional software-based subsequent processing of images which may lead to relatively large uncertainty of the results. Due to efficient FRET and fluorescence background free, a highly-sensitive and accurate sensing has been achieved, featured by 3.56 per unit change in pH i value 3.0-7.0 with deviation less than 0.43. This approach shall facilitate the researches in pH i related areas and development of the intracellular drug delivery systems.

Calibration of the JET neutron yield monitors using the delayed neutron counting technique

International Nuclear Information System (INIS)

van Belle, P.; Jarvis, O.N.; Sadler, G.; de Leeuw, S.; D'Hondt, P.; Pillon, M.

1990-01-01

The time-resolved neutron yield is routinely measured on the JET tokamak using a set of fission chambers. At present, the preferred technique is to employ activation reactions to determine the neutron fluence at a well-chosen position and to relate the measured fluence to the total neutron emission by means of neutron transport calculations. The delayed neutron counting method is a particularly convenient method of performing the activation measurement and the fission cross sections are accurately known. This paper outlines the measurement technique as used on JET

(18)F-FDG uptake predicts diagnostic yield of transbronchial biopsy in peripheral lung cancer.

Science.gov (United States)

Umeda, Yukihiro; Demura, Yoshiki; Anzai, Masaki; Matsuoka, Hiroki; Araya, Tomoyuki; Nishitsuji, Masaru; Nishi, Koichi; Tsuchida, Tatsuro; Sumida, Yasuyuki; Morikawa, Miwa; Ameshima, Shingo; Ishizaki, Takeshi; Kasahara, Kazuo; Ishizuka, Tamotsu

2014-07-01

Recent advances in endobronchial ultrasonography with a guide sheath (EBUS-GS) have enabled better visualization of distal airways, while virtual bronchoscopic navigation (VBN) has been shown useful as a guide to navigate the bronchoscope. However, indications for utilizing VBN and EBUS-GS are not always clear. To clarify indications for a bronchoscopic examination using VBN and EBUS-GS, we evaluated factors that predict the diagnostic yield of a transbronchial biopsy (TBB) procedure for peripheral lung cancer (PLC) lesions. We retrospectively reviewed the charts of 194 patients with 201 PLC lesions (≤3cm mean diameter), and analyzed the association of diagnostic yield of TBB with [(18)F]-fluoro-2-deoxy-d-glucose ((18)F-FDG) positron emission tomography and chest computed tomography (CT) findings. The diagnostic yield of TBB using VBN and EBUS-GS was 66.7%. High maximum standardized uptake value (SUVmax), positive bronchus sign, and ground-glass opacity component shown on CT were all significant predictors of diagnostic yield, while multivariate analysis showed only high (18)F-FDG uptake (SUVmax ≥2.8) and positive bronchus sign as significant predictors. Diagnostic yield was higher for PLC lesions with high (18)F-FDG uptake (SUVmax ≥2.8) and positive bronchus sign (84.6%) than for those with SUVmax PLC lesions. (18)F-FDG uptake and bronchus sign may indicate for the accurate application of bronchoscopy with those modalities for diagnosing PLC. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Quantitative self-assembly prediction yields targeted nanomedicines

Science.gov (United States)

Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

2018-02-01

Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

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

Science.gov (United States)

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.

Correlation and path-cofficient analysis of seed yield and yield ...

African Journals Online (AJOL)

This study was undertaken in order to determine the association among yield components and their direct and indirect effects on the seed yield of confectionery sunflower. 36 confectionery sunflower populations originated from different regions of Northwest Iran were characterized using 11 agromorphological traits ...

Free ion yield observed in liquid isooctane irradiated by γ rays. Comparison with the Onsager theory

International Nuclear Information System (INIS)

Pardo, J; Franco, L; Gomez, F; Iglesias, A; Lobato, R; Mosquera, J; Pazos, A; Pena, J; Pombar, M; RodrIguez, A; Sendon, J

2004-01-01

We have analysed data on the free ion yield observed in liquid isooctane irradiated by 60 Co γ rays within the framework of the Onsager theory about initial recombination. Several distribution functions describing the electron thermalization distance have been used and compared with the experimental results: a delta function, a Gaussian-type function and an exponential function. A linear dependence between the free ion yield and the external electric field has been found at low-electric-field values (E ≤ 1.2 x 10 3 V mm -1 ) in excellent agreement with the Onsager theory. At higher electric field values, we obtain a solution in power series of the external field using the Onsager theory

Free ion yield observed in liquid isooctane irradiated by {gamma} rays. Comparison with the Onsager theory

Energy Technology Data Exchange (ETDEWEB)

Pardo, J [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Franco, L [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Gomez, F [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Iglesias, A [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Lobato, R [Hospital ClInico Universitario de Santiago, Santiago de Compostela (Spain); Mosquera, J [Hospital ClInico Universitario de Santiago, Santiago de Compostela (Spain); Pazos, A [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Pena, J [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Pombar, M [Hospital ClInico Universitario de Santiago, Santiago de Compostela (Spain); RodrIguez, A [Departamento de FIsica de PartIculas, Facultade de FIsica, 15782 Santiago de Compostela (Spain); Sendon, J [Hospital ClInico Universitario de Santiago, Santiago de Compostela (Spain)

2004-05-21

We have analysed data on the free ion yield observed in liquid isooctane irradiated by {sup 60}Co {gamma} rays within the framework of the Onsager theory about initial recombination. Several distribution functions describing the electron thermalization distance have been used and compared with the experimental results: a delta function, a Gaussian-type function and an exponential function. A linear dependence between the free ion yield and the external electric field has been found at low-electric-field values (E {<=} 1.2 x 10{sup 3} V mm{sup -1}) in excellent agreement with the Onsager theory. At higher electric field values, we obtain a solution in power series of the external field using the Onsager theory.

Charge yield for cobalt-60 and 10-keV x-ray irradiations of MOS devices

International Nuclear Information System (INIS)

Shaneyfelt, M.R.; Fleetwood, D.M.; Schwank, J.R.; Hughes, K.L.

1991-01-01

In this paper the radiation response of MOS devices exposed to 60 Co and low-energy (∼10 keV) x-ray irradiation is evaluated as a function of electric field during exposure. Improved charge yield estimates are obtained for 60 Co irradiations at fields below 1 MV/cm by matching voltage shifts due to oxide-trap and interface-trap charge to an E -0.55 electric field dependence. Combining these improved charge yield estimates and calculated dose enhancement factors, the relative response of x-ray to 60 Co irradiations is accurately predicted for oxide electric fields from 0.03 MV/cm to 5.0 MV/cm. The ability to predict the relative response of x-ray to 60 Co irradiations should speed acceptance of x-ray testers as a hardness assurance tool

Accurate and precise determination of critical properties from Gibbs ensemble Monte Carlo simulations

International Nuclear Information System (INIS)

Dinpajooh, Mohammadhasan; Bai, Peng; Allan, Douglas A.; Siepmann, J. Ilja

2015-01-01

Since the seminal paper by Panagiotopoulos [Mol. Phys. 61, 813 (1997)], the Gibbs ensemble Monte Carlo (GEMC) method has been the most popular particle-based simulation approach for the computation of vapor–liquid phase equilibria. However, the validity of GEMC simulations in the near-critical region has been questioned because rigorous finite-size scaling approaches cannot be applied to simulations with fluctuating volume. Valleau [Mol. Simul. 29, 627 (2003)] has argued that GEMC simulations would lead to a spurious overestimation of the critical temperature. More recently, Patel et al. [J. Chem. Phys. 134, 024101 (2011)] opined that the use of analytical tail corrections would be problematic in the near-critical region. To address these issues, we perform extensive GEMC simulations for Lennard-Jones particles in the near-critical region varying the system size, the overall system density, and the cutoff distance. For a system with N = 5500 particles, potential truncation at 8σ and analytical tail corrections, an extrapolation of GEMC simulation data at temperatures in the range from 1.27 to 1.305 yields T c = 1.3128 ± 0.0016, ρ c = 0.316 ± 0.004, and p c = 0.1274 ± 0.0013 in excellent agreement with the thermodynamic limit determined by Potoff and Panagiotopoulos [J. Chem. Phys. 109, 10914 (1998)] using grand canonical Monte Carlo simulations and finite-size scaling. Critical properties estimated using GEMC simulations with different overall system densities (0.296 ≤ ρ t ≤ 0.336) agree to within the statistical uncertainties. For simulations with tail corrections, data obtained using r cut = 3.5σ yield T c and p c that are higher by 0.2% and 1.4% than simulations with r cut = 5 and 8σ but still with overlapping 95% confidence intervals. In contrast, GEMC simulations with a truncated and shifted potential show that r cut = 8σ is insufficient to obtain accurate results. Additional GEMC simulations for hard-core square-well particles with various

EFFECT OF COMPOST FROM BY-PRODUCT OF THE FISHING INDUSTRY ON CROP YIELD AND MICROELEMENT CONTENT IN MAIZE

Directory of Open Access Journals (Sweden)

Maja Radziemska

2015-09-01

Full Text Available A pot experiment was conducted to compare the effects of compost from fish waste with mineral and manure fertilization on the yield and chemical composition of the overground parts of maize (Zea mays L.. The experiment comprised two series: I – composts at a dose of 1 g of compost per pot, and II – composts with 0.5 g of urea. The treatments were conducted on the following types of composts: compost 1: fish waste (80% d.m., sawdust (20% d.m.; compost 2: fish waste (80% d.m., straw (20% d.m.; compost 3: fish waste (80% d.m., bark (20% d.m.; compost 4: fish waste (79.3% d.m., sawdust (19.7% d.m., lignite (1% d.m.; compost 5: fish waste (79.3% d.m., straw (19.7% d.m.; lignite (1% d.m.; compost 6: fish waste (79.3% d.m., bark (19.7% d.m, lignite (1% d.m. The contents of Ni, Zn, Cr, Cu and Cd were determined in an air-acetylene flame using the flame atomic absorption spectrophotometric method. The average crop yield of the overground parts of maize in the series without additional mineral fertilization and with mineral N-fertilization was higher compared to objects without mineral N-fertilization. The highest crop yield was noted in the case of compost containing fish waste and straw with addition of lignite and with bark and lignite. The addition of lignite to the compost mass in the series with mineral N-fertilization had stronger influence on the content of cadmium, chromium, nickel and zinc in the overground parts of maize.

Soviet test yields

Science.gov (United States)

Vergino, Eileen S.

Soviet seismologists have published descriptions of 96 nuclear explosions conducted from 1961 through 1972 at the Semipalatinsk test site, in Kazakhstan, central Asia [Bocharov et al., 1989]. With the exception of releasing news about some of their peaceful nuclear explosions (PNEs) the Soviets have never before published such a body of information.To estimate the seismic yield of a nuclear explosion it is necessary to obtain a calibrated magnitude-yield relationship based on events with known yields and with a consistent set of seismic magnitudes. U.S. estimation of Soviet test yields has been done through application of relationships to the Soviet sites based on the U.S. experience at the Nevada Test Site (NTS), making some correction for differences due to attenuation and near-source coupling of seismic waves.

On a relationship between the geometry of cones on sputtered surfaces and the angular dependence of sputtered yields

International Nuclear Information System (INIS)

Chadderton, L.T.

1977-01-01

It is widely believed that the phenomenon responsible for the familiar peak in the angular dependence of sputtered yields also gives rise to characteristic semiangles α of conical protruberances on sputtered surfaces. It is shown that α corresponds to the process giving rise to the minimum rather than the maximum. No accurate measurements of the minimum have yet been made. (Auth.)

Quantifying the effect of heat stress on daily milk yield and monitoring dynamic changes using an adaptive dynamic model

NARCIS (Netherlands)

Andre, G.; Engel, B.; Berentsen, P.B.M.; Vellinga, T.V.; Oude Lansink, A.G.J.M.

2011-01-01

Automation and use of robots are increasingly being used within dairy farming and result in large amounts of real time data. This information provides a base for the new management concept of precision livestock farming. From 2003 to 2006, time series of herd mean daily milk yield were collected on

A four-stage hybrid model for hydrological time series forecasting.

Science.gov (United States)

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of 'denoising, decomposition and ensemble'. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models.

A Four-Stage Hybrid Model for Hydrological Time Series Forecasting

Science.gov (United States)

Di, Chongli; Yang, Xiaohua; Wang, Xiaochao

2014-01-01

Hydrological time series forecasting remains a difficult task due to its complicated nonlinear, non-stationary and multi-scale characteristics. To solve this difficulty and improve the prediction accuracy, a novel four-stage hybrid model is proposed for hydrological time series forecasting based on the principle of ‘denoising, decomposition and ensemble’. The proposed model has four stages, i.e., denoising, decomposition, components prediction and ensemble. In the denoising stage, the empirical mode decomposition (EMD) method is utilized to reduce the noises in the hydrological time series. Then, an improved method of EMD, the ensemble empirical mode decomposition (EEMD), is applied to decompose the denoised series into a number of intrinsic mode function (IMF) components and one residual component. Next, the radial basis function neural network (RBFNN) is adopted to predict the trend of all of the components obtained in the decomposition stage. In the final ensemble prediction stage, the forecasting results of all of the IMF and residual components obtained in the third stage are combined to generate the final prediction results, using a linear neural network (LNN) model. For illustration and verification, six hydrological cases with different characteristics are used to test the effectiveness of the proposed model. The proposed hybrid model performs better than conventional single models, the hybrid models without denoising or decomposition and the hybrid models based on other methods, such as the wavelet analysis (WA)-based hybrid models. In addition, the denoising and decomposition strategies decrease the complexity of the series and reduce the difficulties of the forecasting. With its effective denoising and accurate decomposition ability, high prediction precision and wide applicability, the new model is very promising for complex time series forecasting. This new forecast model is an extension of nonlinear prediction models. PMID:25111782

Accurate Evaluation of Quantum Integrals

Science.gov (United States)

Galant, D. C.; Goorvitch, D.; Witteborn, Fred C. (Technical Monitor)

1995-01-01

Combining an appropriate finite difference method with Richardson's extrapolation results in a simple, highly accurate numerical method for solving a Schrodinger's equation. Important results are that error estimates are provided, and that one can extrapolate expectation values rather than the wavefunctions to obtain highly accurate expectation values. We discuss the eigenvalues, the error growth in repeated Richardson's extrapolation, and show that the expectation values calculated on a crude mesh can be extrapolated to obtain expectation values of high accuracy.

Generating Converged Accurate Free Energy Surfaces for Chemical Reactions with a Force-Matched Semiempirical Model.

Science.gov (United States)

Kroonblawd, Matthew P; Pietrucci, Fabio; Saitta, Antonino Marco; Goldman, Nir

2018-04-10

We demonstrate the capability of creating robust density functional tight binding (DFTB) models for chemical reactivity in prebiotic mixtures through force matching to short time scale quantum free energy estimates. Molecular dynamics using density functional theory (DFT) is a highly accurate approach to generate free energy surfaces for chemical reactions, but the extreme computational cost often limits the time scales and range of thermodynamic states that can feasibly be studied. In contrast, DFTB is a semiempirical quantum method that affords up to a thousandfold reduction in cost and can recover DFT-level accuracy. Here, we show that a force-matched DFTB model for aqueous glycine condensation reactions yields free energy surfaces that are consistent with experimental observations of reaction energetics. Convergence analysis reveals that multiple nanoseconds of combined trajectory are needed to reach a steady-fluctuating free energy estimate for glycine condensation. Predictive accuracy of force-matched DFTB is demonstrated by direct comparison to DFT, with the two approaches yielding surfaces with large regions that differ by only a few kcal mol -1 .

Effects of phosphorus and zinc applications on the yields and yields ...

African Journals Online (AJOL)

Effects of phosphorus and zinc applications on the yields and yields components of sole early maturing maize ( Zea mays ) and bambaranut ( Vigna subterranean Thour. ) and in intercrop under southern guinea savannah ecology zone.

Can crop-climate models be accurate and precise? A case study for wheat production in Denmark

DEFF Research Database (Denmark)

Montesino San Martin, Manuel; Olesen, Jørgen E.; Porter, John Roy

2015-01-01

Crop models, used to make projections of climate change impacts, differ greatly in structural detail. Complexity of model structure has generic effects on uncertainty and error propagation in climate change impact assessments. We applied Bayesian calibration to three distinctly different empirical....... Yields predicted by the mechanistic model were generally more accurate than the empirical models for extrapolated conditions. This trend does not hold for all extrapolations; mechanistic and empirical models responded differently due to their sensitivities to distinct weather features. However, higher...... suitable for generic model ensembles for near-term agricultural impact assessments of climate change....

6 Grain Yield

African Journals Online (AJOL)

create a favourable environment for rice ... developing lines adaptable to many ... have stable, not too short crop duration with ..... Analysis of variance of the effect of site and season on maturity, grain yield and plant ..... and yield components.

Improved Satellite-based Crop Yield Mapping by Spatially Explicit Parameterization of Crop Phenology

Science.gov (United States)

Jin, Z.; Azzari, G.; Lobell, D. B.

2016-12-01

Field-scale mapping of crop yields with satellite data often relies on the use of crop simulation models. However, these approaches can be hampered by inaccuracies in the simulation of crop phenology. Here we present and test an approach to use dense time series of Landsat 7 and 8 acquisitions data to calibrate various parameters related to crop phenology simulation, such as leaf number and leaf appearance rates. These parameters are then mapped across the Midwestern United States for maize and soybean, and for two different simulation models. We then implement our recently developed Scalable satellite-based Crop Yield Mapper (SCYM) with simulations reflecting the improved phenology parameterizations, and compare to prior estimates based on default phenology routines. Our preliminary results show that the proposed method can effectively alleviate the underestimation of early-season LAI by the default Agricultural Production Systems sIMulator (APSIM), and that spatially explicit parameterization for the phenology model substantially improves the SCYM performance in capturing the spatiotemporal variation in maize and soybean yield. The scheme presented in our study thus preserves the scalability of SCYM, while significantly reducing its uncertainty.

Simple and accurate solution for convective-radiative fin with temperature dependent thermal conductivity using double optimal linearization

International Nuclear Information System (INIS)

Bouaziz, M.N.; Aziz, Abdul

2010-01-01

A novel concept of double optimal linearization is introduced and used to obtain a simple and accurate solution for the temperature distribution in a straight rectangular convective-radiative fin with temperature dependent thermal conductivity. The solution is built from the classical solution for a pure convection fin of constant thermal conductivity which appears in terms of hyperbolic functions. When compared with the direct numerical solution, the double optimally linearized solution is found to be accurate within 4% for a range of radiation-conduction and thermal conductivity parameters that are likely to be encountered in practice. The present solution is simple and offers superior accuracy compared with the fairly complex approximate solutions based on the homotopy perturbation method, variational iteration method, and the double series regular perturbation method. The fin efficiency expression resembles the classical result for the constant thermal conductivity convecting fin. The present results are easily usable by the practicing engineers in their thermal design and analysis work involving fins.

Empirical study of classification process for two-stage turbo air classifier in series

Science.gov (United States)

Yu, Yuan; Liu, Jiaxiang; Li, Gang

2013-05-01

The suitable process parameters for a two-stage turbo air classifier are important for obtaining the ultrafine powder that has a narrow particle-size distribution, however little has been published internationally on the classification process for the two-stage turbo air classifier in series. The influence of the process parameters of a two-stage turbo air classifier in series on classification performance is empirically studied by using aluminum oxide powders as the experimental material. The experimental results show the following: 1) When the rotor cage rotary speed of the first-stage classifier is increased from 2 300 r/min to 2 500 r/min with a constant rotor cage rotary speed of the second-stage classifier, classification precision is increased from 0.64 to 0.67. However, in this case, the final ultrafine powder yield is decreased from 79% to 74%, which means the classification precision and the final ultrafine powder yield can be regulated through adjusting the rotor cage rotary speed of the first-stage classifier. 2) When the rotor cage rotary speed of the second-stage classifier is increased from 2 500 r/min to 3 100 r/min with a constant rotor cage rotary speed of the first-stage classifier, the cut size is decreased from 13.16 μm to 8.76 μm, which means the cut size of the ultrafine powder can be regulated through adjusting the rotor cage rotary speed of the second-stage classifier. 3) When the feeding speed is increased from 35 kg/h to 50 kg/h, the "fish-hook" effect is strengthened, which makes the ultrafine powder yield decrease. 4) To weaken the "fish-hook" effect, the equalization of the two-stage wind speeds or the combination of a high first-stage wind speed with a low second-stage wind speed should be selected. This empirical study provides a criterion of process parameter configurations for a two-stage or multi-stage classifier in series, which offers a theoretical basis for practical production.

Empirical investigation on modeling solar radiation series with ARMA–GARCH models

International Nuclear Information System (INIS)

Sun, Huaiwei; Yan, Dong; Zhao, Na; Zhou, Jianzhong

2015-01-01

Highlights: • Apply 6 ARMA–GARCH(-M) models to model and forecast solar radiation. • The ARMA–GARCH(-M) models produce more accurate radiation forecasting than conventional methods. • Show that ARMA–GARCH-M models are more effective for forecasting solar radiation mean and volatility. • The ARMA–EGARCH-M is robust and the ARMA–sGARCH-M is very competitive. - Abstract: Simulation of radiation is one of the most important issues in solar utilization. Time series models are useful tools in the estimation and forecasting of solar radiation series and their changes. In this paper, the effectiveness of autoregressive moving average (ARMA) models with various generalized autoregressive conditional heteroskedasticity (GARCH) processes, namely ARMA–GARCH models are evaluated for their effectiveness in radiation series. Six different GARCH approaches, which contain three different ARMA–GARCH models and corresponded GARCH in mean (ARMA–GARCH-M) models, are applied in radiation data sets from two representative climate stations in China. Multiple evaluation metrics of modeling sufficiency are used for evaluating the performances of models. The results show that the ARMA–GARCH(-M) models are effective in radiation series estimation. Both in fitting and prediction of radiation series, the ARMA–GARCH(-M) models show better modeling sufficiency than traditional models, while ARMA–EGARCH-M models are robustness in two sites and the ARMA–sGARCH-M models appear very competitive. Comparisons of statistical diagnostics and model performance clearly show that the ARMA–GARCH-M models make the mean radiation equations become more sufficient. It is recommended the ARMA–GARCH(-M) models to be the preferred method to use in the modeling of solar radiation series

Tunneling effects in electromagnetic wave scattering by nonspherical particles: A comparison of the Debye series and physical-geometric optics approximations

Science.gov (United States)

Bi, Lei; Yang, Ping

2016-07-01

The accuracy of the physical-geometric optics (PG-O) approximation is examined for the simulation of electromagnetic scattering by nonspherical dielectric particles. This study seeks a better understanding of the tunneling effect on the phase matrix by employing the invariant imbedding method to rigorously compute the zeroth-order Debye series, from which the tunneling efficiency and the phase matrix corresponding to the diffraction and external reflection are obtained. The tunneling efficiency is shown to be a factor quantifying the relative importance of the tunneling effect over the Fraunhofer diffraction near the forward scattering direction. Due to the tunneling effect, different geometries with the same projected cross section might have different diffraction patterns, which are traditionally assumed to be identical according to the Babinet principle. For particles with a fixed orientation, the PG-O approximation yields the external reflection pattern with reasonable accuracy, but ordinarily fails to predict the locations of peaks and minima in the diffraction pattern. The larger the tunneling efficiency, the worse the PG-O accuracy is at scattering angles less than 90°. If the particles are assumed to be randomly oriented, the PG-O approximation yields the phase matrix close to the rigorous counterpart, primarily due to error cancellations in the orientation-average process. Furthermore, the PG-O approximation based on an electric field volume-integral equation is shown to usually be much more accurate than the Kirchhoff surface integral equation at side-scattering angles, particularly when the modulus of the complex refractive index is close to unity. Finally, tunneling efficiencies are tabulated for representative faceted particles.

Some aspects of the growth and yield of Gracilaria tikvahiae in culture

Energy Technology Data Exchange (ETDEWEB)

Lapointe, B E; Ryther, J H

1978-11-01

A series of outdoor, continuous-flow seawater cultures (50 l; 0.23 m/sup 2/) were used to investigate the effects of culture density (kg/m/sup 2/), nutrient loading (total nitrogen input/day) with both NH/sub 4//sup +/-N and NO/sub 3//sup -/-N, and turnover rate (flow rate/culture volume) on the growth and yield of Gracilaria tikvahiae. Although specific growth rates as high as 60% per day were recorded for Gracilaria at low densities (0.4 kg wet wt/m/sup 2/) in summer conditions, maximum year-round yields were obtained at densities of 2.0 to 3.0 kg wet wt/m/sup 2/. Above a minimal daily nitrogen loading, the yield of Gracilaria was independent of (1) nutrient concentration, (2) nitrogen loading, or (3) whether nitrogen was in the form of NH/sub 4//sup +/-N or NO/sub 3//sup -/-N, but was (4) highly dependent upon flow rate. The time weighted mean annual production during 1976--1977 was 34.8 g dry wt/m/sup 2/.day or 127 t/ha.yr based on 12-months continuous operation at near optimal densities and flow rates in the non-nutrient limited culture system.

EFFECT OF MOLECULAR WEIGHT ON THE YIELD BEHAVIOUR OF EPY EPOXY COMPOUND

Directory of Open Access Journals (Sweden)

Magdalena Urbaniak

2016-12-01

Full Text Available A series of epoxy networks with molecular weight between crosslinks (Mc ranging from 117 to 508 g/mol were investigated by employing as DSC and DMA methods and compression testing over a broad range of test temperatures (from 20 to 120 °C and strain rates (from 0.0208 to 20.8 min–1. Mechanical characteristics vs. testing temperature and strain rate developed in relation to working conditions of EPY compound applied for machine foundation chocks as well as effect of crosslinking on glass transition temperature (Tg presented in this paper let to find out the effect of molecular architecture composed chiefly by Mc on the thermal and mechanical properties that govern yield behaviour of the material. The investigations carried out in a.m. ranges of testing temperatures and strain rates showed that whichever change of Mc is related to the change in crosslink density causing relative shift in the Tg of the compound. However, a sensitivity of the polymer material on changes in strain rate falls down with growth of testing temperature. Obtained results prove that yielding in EPY compound can be examined in categories of the Eyring’s plastic flow model in which yielding is described.

Approaching system equilibrium with accurate or not accurate feedback information in a two-route system

Science.gov (United States)

Zhao, Xiao-mei; Xie, Dong-fan; Li, Qi

2015-02-01

With the development of intelligent transport system, advanced information feedback strategies have been developed to reduce traffic congestion and enhance the capacity. However, previous strategies provide accurate information to travelers and our simulation results show that accurate information brings negative effects, especially in delay case. Because travelers prefer to the best condition route with accurate information, and delayed information cannot reflect current traffic condition but past. Then travelers make wrong routing decisions, causing the decrease of the capacity and the increase of oscillations and the system deviating from the equilibrium. To avoid the negative effect, bounded rationality is taken into account by introducing a boundedly rational threshold BR. When difference between two routes is less than the BR, routes have equal probability to be chosen. The bounded rationality is helpful to improve the efficiency in terms of capacity, oscillation and the gap deviating from the system equilibrium.

Analog series-based scaffolds: computational design and exploration of a new type of molecular scaffolds for medicinal chemistry

Science.gov (United States)

Dimova, Dilyana; Stumpfe, Dagmar; Hu, Ye; Bajorath, Jürgen

2016-01-01

Aim: Computational design of and systematic search for a new type of molecular scaffolds termed analog series-based scaffolds. Materials & methods: From currently available bioactive compounds, analog series were systematically extracted, key compounds identified and new scaffolds isolated from them. Results: Using our computational approach, more than 12,000 scaffolds were extracted from bioactive compounds. Conclusion: A new scaffold definition is introduced and a computational methodology developed to systematically identify such scaffolds, yielding a large freely available scaffold knowledge base. PMID:28116132

Using normalized difference vegetation index (NDVI) to estimate sugarcane yield and yield components

Science.gov (United States)

Sugarcane (Saccharum spp.) yield and yield components are important traits for growers and scientists to evaluate and select cultivars. Collection of these yield data would be labor intensive and time consuming in the early selection stages of sugarcane breeding cultivar development programs with a ...

Fostering accurate HIV/AIDS knowledge among unmarried youths in Cameroon: do family environment and peers matter?

Science.gov (United States)

Tsala Dimbuene, Zacharie; Kuate Defo, Barthelemy

2011-05-19

The last three decades have seen a series of HIV interventions in sub-Saharan Africa. However, youths still have a mixture of correct and incorrect HIV/AIDS knowledge of transmission routes and prevention strategies. Previous studies have identified parents and peers as the most important socializing agents for youths. This paper assesses the relationships between family structure, family/peer communication about sexuality and accurate knowledge of transmission routes and prevention strategies. Data were drawn from the Cameroon Family Life and Health Survey (CFHS) conducted in 2002. The CFHS collected information on a representative sample of 4950 people aged 10 years and over nested within 1765 selected households from the 75 localities forming the administrative prefecture of Bandjoun, using detailed questionnaires about family, HIV/AIDS/STDs knowledge, sexual behaviors, contraception, health, media exposure, household assets and neighborhood characteristics. The survey cooperation rates were high (97%). For the purpose of this study, a sub-sample of 2028 unmarried youths aged 12-29 years was utilized. Overall, 42% of respondents reported accurate knowledge of documented HIV transmission routes whereas 21% of them had inaccurate knowledge such as AIDS can be transmitted through mosquito bites or casual contact with an infected person. Only 9% of respondents were knowledgeable about all HIV prevention strategies. Multivariate analyses showed that family structure, communication with parents/guardians and peers about sexual topics were significantly associated with accurate HIV knowledge. Additionally, age, education, sexual experience and migration had significant effects on accurate knowledge. Finally, living in poor households and disadvantaged neighborhoods significantly increased inaccurate knowledge of HIV transmission modes and prevention strategies. This paper evidenced the limited effects of HIV interventions/programmes in sub-Saharan Africa. Indeed, few

Potato yield and yield structure depending on irrigation

Directory of Open Access Journals (Sweden)

Milić Stanko

2010-01-01

Full Text Available In the agroclimatic conditions of the Vojvodina Province, the application of an economic water regime and modern technology is necessary for stable and intensive potato production. A two-year experiment on calcareous chernozem was carried out to determine how irrigation and different pre-irrigation soil moisture affect potato yield and distribution of tuber fraction in the potato yield. The block-design trial had four replicates and was adapted for sprinkler irrigation conditions. It included four treatments: irrigation with pre-irrigation moisture levels of 60 % of field water capacity (FC, irrigation with pre-irrigation moisture levels of 70 % (FC, irrigation with pre-irrigation moisture levels of 80% (FC, and a non-irrigated control treatment. Irrigation significantly increased the yield of potato, which increased from 37.27 % to 75.86 %. Under irrigation, the percentage of small fractions decreased in favour of the 55 mm one, or fractions above the 45-55 mm range. On average, irrigated treatments produced significantly more tubers than the conditions of natural water supply. .

Plateletpheresis efficiency and mathematical correction of software-derived platelet yield prediction: A linear regression and ROC modeling approach.

Science.gov (United States)

Jaime-Pérez, José Carlos; Jiménez-Castillo, Raúl Alberto; Vázquez-Hernández, Karina Elizabeth; Salazar-Riojas, Rosario; Méndez-Ramírez, Nereida; Gómez-Almaguer, David

2017-10-01

Advances in automated cell separators have improved the efficiency of plateletpheresis and the possibility of obtaining double products (DP). We assessed cell processor accuracy of predicted platelet (PLT) yields with the goal of a better prediction of DP collections. This retrospective proof-of-concept study included 302 plateletpheresis procedures performed on a Trima Accel v6.0 at the apheresis unit of a hematology department. Donor variables, software predicted yield and actual PLT yield were statistically evaluated. Software prediction was optimized by linear regression analysis and its optimal cut-off to obtain a DP assessed by receiver operating characteristic curve (ROC) modeling. Three hundred and two plateletpheresis procedures were performed; in 271 (89.7%) occasions, donors were men and in 31 (10.3%) women. Pre-donation PLT count had the best direct correlation with actual PLT yield (r = 0.486. P Simple correction derived from linear regression analysis accurately corrected this underestimation and ROC analysis identified a precise cut-off to reliably predict a DP. © 2016 Wiley Periodicals, Inc.

Using Worldview Satellite Imagery to Map Yield in Avocado (Persea americana: A Case Study in Bundaberg, Australia

Directory of Open Access Journals (Sweden)

Andrew Robson

2017-11-01

Full Text Available Accurate pre-harvest estimation of avocado (Persea americana cv. Haas yield offers a range of benefits to industry and growers. Currently there is no commercial yield monitor available for avocado tree crops and the manual count method used for yield forecasting can be highly inaccurate. Remote sensing using satellite imagery offers a potential means to achieve accurate pre-harvest yield forecasting. This study evaluated the accuracies of high resolution WorldView (WV 2 and 3 satellite imagery and targeted field sampling for the pre-harvest prediction of total fruit weight (kg·tree−1 and average fruit size (g and for mapping the spatial distribution of these yield parameters across the orchard block. WV 2 satellite imagery was acquired over two avocado orchards during 2014, and WV3 imagery was acquired in 2016 and 2017 over these same two orchards plus an additional three orchards. Sample trees representing high, medium and low vigour zones were selected from normalised difference vegetation index (NDVI derived from the WV images and sampled for total fruit weight (kg·tree−1 and average fruit size (g per tree. For each sample tree, spectral reflectance data was extracted from the eight band multispectral WV imagery and 18 vegetation indices (VIs derived. Principal component analysis (PCA and non-linear regression analysis was applied to each of the derived VIs to determine the index with the strongest relationship to the measured total fruit weight and average fruit size. For all trees measured over the three year period (2014, 2016, and 2017 a consistent positive relationship was identified between the VI using near infrared band one and the red edge band (RENDVI1 to both total fruit weight (kg·tree−1 (R2 = 0.45, 0.28, and 0.29 respectively and average fruit size (g (R2 = 0.56, 0.37, and 0.29 respectively across all orchard blocks. Separate analysis of each orchard block produced higher R2 values as well as identifying different

Using artificial neural network and satellite data to predict rice yield in Bangladesh

Science.gov (United States)

Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix; Goldberg, Mitch

2015-09-01

Rice production in Bangladesh is a crucial part of the national economy and providing about 70 percent of an average citizen's total calorie intake. The demand for rice is constantly rising as the new populations are added in every year in Bangladesh. Due to the increase in population, the cultivation land decreases. In addition, Bangladesh is faced with production constraints such as drought, flooding, salinity, lack of irrigation facilities and lack of modern technology. To maintain self sufficiency in rice, Bangladesh will have to continue to expand rice production by increasing yield at a rate that is at least equal to the population growth until the demand of rice has stabilized. Accurate rice yield prediction is one of the most important challenges in managing supply and demand of rice as well as decision making processes. Artificial Neural Network (ANN) is used to construct a model to predict Aus rice yield in Bangladesh. Advanced Very High Resolution Radiometer (AVHRR)-based remote sensing satellite data vegetation health (VH) indices (Vegetation Condition Index (VCI) and Temperature Condition Index (TCI) are used as input variables and official statistics of Aus rice yield is used as target variable for ANN prediction model. The result obtained with ANN method is encouraging and the error of prediction is less than 10%. Therefore, prediction can play an important role in planning and storing of sufficient rice to face in any future uncertainty.

Learning a Weighted Sequence Model of the Nucleosome Core and Linker Yields More Accurate Predictions in Saccharomyces cerevisiae and Homo sapiens

Science.gov (United States)

Reynolds, Sheila M.; Bilmes, Jeff A.; Noble, William Stafford

2010-01-01

DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence—301 base pairs, centered at the position to be scored—with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the

Learning a weighted sequence model of the nucleosome core and linker yields more accurate predictions in Saccharomyces cerevisiae and Homo sapiens.

Directory of Open Access Journals (Sweden)

Sheila M Reynolds

2010-07-01

Full Text Available DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the

Learning a weighted sequence model of the nucleosome core and linker yields more accurate predictions in Saccharomyces cerevisiae and Homo sapiens.

Science.gov (United States)

Reynolds, Sheila M; Bilmes, Jeff A; Noble, William Stafford

2010-07-08

DNA in eukaryotes is packaged into a chromatin complex, the most basic element of which is the nucleosome. The precise positioning of the nucleosome cores allows for selective access to the DNA, and the mechanisms that control this positioning are important pieces of the gene expression puzzle. We describe a large-scale nucleosome pattern that jointly characterizes the nucleosome core and the adjacent linkers and is predominantly characterized by long-range oscillations in the mono, di- and tri-nucleotide content of the DNA sequence, and we show that this pattern can be used to predict nucleosome positions in both Homo sapiens and Saccharomyces cerevisiae more accurately than previously published methods. Surprisingly, in both H. sapiens and S. cerevisiae, the most informative individual features are the mono-nucleotide patterns, although the inclusion of di- and tri-nucleotide features results in improved performance. Our approach combines a much longer pattern than has been previously used to predict nucleosome positioning from sequence-301 base pairs, centered at the position to be scored-with a novel discriminative classification approach that selectively weights the contributions from each of the input features. The resulting scores are relatively insensitive to local AT-content and can be used to accurately discriminate putative dyad positions from adjacent linker regions without requiring an additional dynamic programming step and without the attendant edge effects and assumptions about linker length modeling and overall nucleosome density. Our approach produces the best dyad-linker classification results published to date in H. sapiens, and outperforms two recently published models on a large set of S. cerevisiae nucleosome positions. Our results suggest that in both genomes, a comparable and relatively small fraction of nucleosomes are well-positioned and that these positions are predictable based on sequence alone. We believe that the bulk of the

Generalized weighted ratio method for accurate turbidity measurement over a wide range.

Science.gov (United States)

Liu, Hongbo; Yang, Ping; Song, Hong; Guo, Yilu; Zhan, Shuyue; Huang, Hui; Wang, Hangzhou; Tao, Bangyi; Mu, Quanquan; Xu, Jing; Li, Dejun; Chen, Ying

2015-12-14

Turbidity measurement is important for water quality assessment, food safety, medicine, ocean monitoring, etc. In this paper, a method that accurately estimates the turbidity over a wide range is proposed, where the turbidity of the sample is represented as a weighted ratio of the scattered light intensities at a series of angles. An improvement in the accuracy is achieved by expanding the structure of the ratio function, thus adding more flexibility to the turbidity-intensity fitting. Experiments have been carried out with an 850 nm laser and a power meter fixed on a turntable to measure the light intensity at different angles. The results show that the relative estimation error of the proposed method is 0.58% on average for a four-angle intensity combination for all test samples with a turbidity ranging from 160 NTU to 4000 NTU.

Implicit time accurate simulation of unsteady flow

Science.gov (United States)

van Buuren, René; Kuerten, Hans; Geurts, Bernard J.

2001-03-01

Implicit time integration was studied in the context of unsteady shock-boundary layer interaction flow. With an explicit second-order Runge-Kutta scheme, a reference solution to compare with the implicit second-order Crank-Nicolson scheme was determined. The time step in the explicit scheme is restricted by both temporal accuracy as well as stability requirements, whereas in the A-stable implicit scheme, the time step has to obey temporal resolution requirements and numerical convergence conditions. The non-linear discrete equations for each time step are solved iteratively by adding a pseudo-time derivative. The quasi-Newton approach is adopted and the linear systems that arise are approximately solved with a symmetric block Gauss-Seidel solver. As a guiding principle for properly setting numerical time integration parameters that yield an efficient time accurate capturing of the solution, the global error caused by the temporal integration is compared with the error resulting from the spatial discretization. Focus is on the sensitivity of properties of the solution in relation to the time step. Numerical simulations show that the time step needed for acceptable accuracy can be considerably larger than the explicit stability time step; typical ratios range from 20 to 80. At large time steps, convergence problems that are closely related to a highly complex structure of the basins of attraction of the iterative method may occur. Copyright

Time-series prediction of shellfish farm closure: A comparison of alternatives

Directory of Open Access Journals (Sweden)

Ashfaqur Rahman

2014-08-01

Full Text Available Shellfish farms are closed for harvest when microbial pollutants are present. Such pollutants are typically present in rainfall runoff from various land uses in catchments. Experts currently use a number of observable parameters (river flow, rainfall, salinity as proxies to determine when to close farms. We have proposed using the short term historical rainfall data as a time-series prediction problem where we aim to predict the closure of shellfish farms based only on rainfall. Time-series event prediction consists of two steps: (i feature extraction, and (ii prediction. A number of data mining challenges exist for these scenarios: (i which feature extraction method best captures the rainfall pattern over successive days that leads to opening or closure of the farms?, (ii The farm closure events occur infrequently and this leads to a class imbalance problem; the question is what is the best way to deal with this problem? In this paper we have analysed and compared different combinations of balancing methods (under-sampling and over-sampling, feature extraction methods (cluster profile, curve fitting, Fourier Transform, Piecewise Aggregate Approximation, and Wavelet Transform and learning algorithms (neural network, support vector machine, k-nearest neighbour, decision tree, and Bayesian Network to predict closure events accurately considering the above data mining challenges. We have identified the best combination of techniques to accurately predict shellfish farm closure from rainfall, given the above data mining challenges.

Development of a method to accurately calculate the Dpb and quickly predict the strength of a chemical bond

International Nuclear Information System (INIS)

Du, Xia; Zhao, Dong-Xia; Yang, Zhong-Zhi

2013-01-01

Highlights: ► A method from new respect to characterize and measure the bond strength is proposed. ► We calculate the D pb of a series of various bonds to justify our approach. ► A quite good linear relationship of the D pb with the bond lengths for series of various bonds is shown. ► Take the prediction of strengths of C–H and N–H bonds for base pairs in DNA as a practical application of our method. - Abstract: A new approach to characterize and measure bond strength has been developed. First, we propose a method to accurately calculate the potential acting on an electron in a molecule (PAEM) at the saddle point along a chemical bond in situ, denoted by D pb . Then, a direct method to quickly evaluate bond strength is established. We choose some familiar molecules as models for benchmarking this method. As a practical application, the D pb of base pairs in DNA along C–H and N–H bonds are obtained for the first time. All results show that C 7 –H of A–T and C 8 –H of G–C are the relatively weak bonds that are the injured positions in DNA damage. The significance of this work is twofold: (i) A method is developed to calculate D pb of various sizable molecules in situ quickly and accurately; (ii) This work demonstrates the feasibility to quickly predict the bond strength in macromolecules

Comparing predicted yield and yield stability of willow and Miscanthus across Denmark

DEFF Research Database (Denmark)

Larsen, Søren; Jaiswal, Deepak; Bentsen, Niclas Scott

2016-01-01

was 12.1 Mg DM ha−1 yr−1 for willow and 10.2 Mg DM ha−1 yr−1 for Miscanthus. Coefficent of variation as a measure for yield stability was poorest on the sandy soils of northern and western Jutland and the year-to-year variation in yield was greatest on these soils. Willow was predicted to outyield...... Miscanthus on poor, sandy soils whereas Miscanthus was higher yielding on clay-rich soils. The major driver of yield in both crops was variation in soil moisture, with radiation and precipitation exerting less influence. This is the first time these two major feedstocks for northern Europe have been compared....... The semi-mechanistic crop model BioCro was used to simulate the production of both short rotation coppice (SRC) willow and Miscanthus across Denmark. Predictions were made from high spatial resolution soil data and weather records across this area for 1990-2010. The potential average, rain-fed mean yield...

Study of agronomic characteristics and advantage indices in intercropping of additive series of Chickpea (Cicer arietinum L. and Black Cumin (Nigella sativa L.

Directory of Open Access Journals (Sweden)

esmaeil rezaei-chiyaneh

2015-12-01

Full Text Available Study of agronomic characteristics and advantage indices in intercropping of additive series of Chickpea (Cicer arietinum L. and Black Cumin (Nigella sativa L. Abstract In order to evaluate quantitive and qualitive yield of Chickpea (Cicer arietinum L. and Black Cumin (Nigella sativa L. in intercropping of additive series, a field experiment was arranged in a randomized complete block design with three replications in West Azerbaijan province- city Nagadeh, Iran during growing reason of 2012-2013. Treatments included 100% Black Cumin + 10% Chickpea, 100% Black Cumin + 20% Chickpea, 100% Black Cumin + 30% Chickpea, 100% Black Cumin + 40% Chickpea and 100% Black Cumin + 50% Chickpea and sole cropping of Chickpea and Black Cumin. Different Planting Ratio had significant effect on studied traits of Chickpea and Black Cumin (exception Essential oil yield of Black Cumin. Yield and components yield in monoculture of each crop was more than other treatments. The highest grain yield and biological yield of chickpea were achieved in monoculture with 1105 and 14479 kg.ha-1, respectively. The results showed that the maximum seed yield and biological yield of Black Cumin were obtained at monoculture with 750 and 2310 kg.ha-1, respectively. The highest of percentage of grain protein (23% and essential oil percentage (1.47% were related to treatment 100% Black Cumin + 50% Chickpea, respectively. Based on this results, the highest land equivalent ratio (LER=1.74, actual yield loss (AYL=6.45 and intercropping advantage (IA=1.70 were obtained by treatment 100% Black Cumin + 10% Chickpea, respectively. Therefore, it seems that treatment 100% Black Cumin + 10% Chickpea is remarkably effective to increase the economic income and land use efficiency.

Effect of raw material on physical properties and yield of bio diesel

International Nuclear Information System (INIS)

Malik, S.R.; Khan, J.R.

2008-01-01

Production of bio diesel via trans-esterification method is under investigation as an alternative fuel. The prospects of using crude vegetable oil have not been investigated extensively which may be due to economic reasons. Used and unused vegetable oils have been considered for this purpose and a series of experimental results were reported. This study encircles similar prospect and compares the results. Various samples of refined and crude forms of Canola and Cottonseed Oils were tested. Viscosity, densities. Pour point, cloud point and yield of bio-diesels have been determined which may provide a useful data for further investigations. (author)

Magnetic Field Emission Comparison for Series-Parallel and Series-Series Wireless Power Transfer to Vehicles – PART 2/2

DEFF Research Database (Denmark)

Batra, Tushar; Schaltz, Erik

2014-01-01

Series-series and series-parallel topologies are the most favored topologies for design of wireless power transfer system for vehicle applications. The series-series topology has the advantage of reflecting only the resistive part on the primary side. On the other hand, the current source output...... characteristics of the series-parallel topology are more suited for the battery of the vehicle. This paper compares the two topologies in terms of magnetic emissions to the surroundings for the same input power, primary current, quality factor and inductors. Theoretical and simulation results show that the series...

Open-source Software for Demand Forecasting of Clinical Laboratory Test Volumes Using Time-series Analysis.

Science.gov (United States)

Mohammed, Emad A; Naugler, Christopher

2017-01-01

Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. This tool will allow anyone with historic test volume data to model future demand.

Open-source software for demand forecasting of clinical laboratory test volumes using time-series analysis

Directory of Open Access Journals (Sweden)

Emad A Mohammed

2017-01-01

Full Text Available Background: Demand forecasting is the area of predictive analytics devoted to predicting future volumes of services or consumables. Fair understanding and estimation of how demand will vary facilitates the optimal utilization of resources. In a medical laboratory, accurate forecasting of future demand, that is, test volumes, can increase efficiency and facilitate long-term laboratory planning. Importantly, in an era of utilization management initiatives, accurately predicted volumes compared to the realized test volumes can form a precise way to evaluate utilization management initiatives. Laboratory test volumes are often highly amenable to forecasting by time-series models; however, the statistical software needed to do this is generally either expensive or highly technical. Method: In this paper, we describe an open-source web-based software tool for time-series forecasting and explain how to use it as a demand forecasting tool in clinical laboratories to estimate test volumes. Results: This tool has three different models, that is, Holt-Winters multiplicative, Holt-Winters additive, and simple linear regression. Moreover, these models are ranked and the best one is highlighted. Conclusion: This tool will allow anyone with historic test volume data to model future demand.

Global evaluation of a semiempirical model for yield anomalies and application to within-season yield forecasting.

Science.gov (United States)

Schauberger, Bernhard; Gornott, Christoph; Wechsung, Frank

2017-11-01

Quantifying the influence of weather on yield variability is decisive for agricultural management under current and future climate anomalies. We extended an existing semiempirical modeling scheme that allows for such quantification. Yield anomalies, measured as interannual differences, were modeled for maize, soybeans, and wheat in the United States and 32 other main producer countries. We used two yield data sets, one derived from reported yields and the other from a global yield data set deduced from remote sensing. We assessed the capacity of the model to forecast yields within the growing season. In the United States, our model can explain at least two-thirds (63%-81%) of observed yield anomalies. Its out-of-sample performance (34%-55%) suggests a robust yield projection capacity when applied to unknown weather. Out-of-sample performance is lower when using remote sensing-derived yield data. The share of weather-driven yield fluctuation varies spatially, and estimated coefficients agree with expectations. Globally, the explained variance in yield anomalies based on the remote sensing data set is similar to the United States (71%-84%). But the out-of-sample performance is lower (15%-42%). The performance discrepancy is likely due to shortcomings of the remote sensing yield data as it diminishes when using reported yield anomalies instead. Our model allows for robust forecasting of yields up to 2 months before harvest for several main producer countries. An additional experiment suggests moderate yield losses under mean warming, assuming no major changes in temperature extremes. We conclude that our model can detect weather influences on yield anomalies and project yields with unknown weather. It requires only monthly input data and has a low computational demand. Its within-season yield forecasting capacity provides a basis for practical applications like local adaptation planning. Our study underlines high-quality yield monitoring and statistics as critical

High-performance carbon nanotube-implanted mesoporous carbon spheres for supercapacitors with low series resistance

Energy Technology Data Exchange (ETDEWEB)

Yi, Bin [College of Materials Science and Engineering, Hunan University, Changsha 410082 (China); Chen, Xiaohua, E-mail: hudacxh62@yahoo.com.cn [College of Materials Science and Engineering, Hunan University, Changsha 410082 (China); Guo, Kaimin [College of Physics and Electronic Science, Changsha University of Science and Technology (China); Xu, Longshan [Department of Mechanical Engineering, Xiamen University of Technology, Xiamen 361024 (China); Chen, Chuansheng [College of Physics and Electronic Science, Changsha University of Science and Technology (China); Yan, Haimei; Chen, Jianghua [College of Materials Science and Engineering, Hunan University, Changsha 410082 (China)

2011-11-15

Research highlights: {yields} CNTs-implanted porous carbon spheres are prepared by using gelatin as soft template. {yields} Homogeneously distributed CNTs form a well-develop network in carbon spheres. {yields} CNTs act as a reinforcing backbone assisting the formation of pore structure. {yields} CNTs improve electrical conductivity and specific capacitance of supercapacitor. -- Abstract: Carbon nanotube-implanted mesoporous carbon spheres were prepared by an easy polymerization-induced colloid aggregation method using gelatin as a soft template. Scanning electron microscopy, transmission electron microscopy and nitrogen adsorption-desorption measurements reveal that the materials are mesoporous carbon spheres, with a diameter of {approx}0.5-1.0 {mu}m, a specific surface area of 284 m{sup 2}/g and average pore size of 3.9 nm. Using the carbon nanotube-implanted mesoporous carbon spheres as electrode material for supercapacitors in an aqueous electrolyte solution, a low equivalent series resistance of 0.83 {Omega} cm{sup 2} and a maximum specific capacitance of 189 F/g with a measured power density of 8.7 kW/kg at energy density of 6.6 Wh/kg are obtained.

THE INFLUENCE OF FERTILIZATION ON YIELD AND YIELD COMPONENT FORMATION OF SOYBEAN VARIETIES

Directory of Open Access Journals (Sweden)

Eva CANDRÁKOVÁ

2009-03-01

Full Text Available In 2005 and 2006, the influence of fertilization was investigated on forming of yield components and yield of three soybean varieties in sugar beet growing area. Varieties Korada, Supra and OAC Vision were grown. Number of plants per m2, number of pods per plant, number of seeds in pod, thousand seeds weight, yield of seeds, yield of stems and harvest index were examined. Variants of fertilization: I. non-fertilized control, II. LAV 27 % (40 kg ha-1 net nutrient of N in growing stage of first pair of true leaves unfolded, III. Humix komplet (rate 8 l.ha-1 applied in growing stage of first pair of true leaves unfolded (4 l.ha-1 and in growing stage of first flower buds visible (4 l.ha-1, IV. Humix komplet in rate 8 l.ha-1 applied in growing stage of first pair of true leaves unfolded. The yields of seeds and stems were high significantly influenced by variety, fertilization and year. The significantly highest yield of seeds was achieved by Korada variety (4,04 t.ha-1. Varieties OAC Vision and Supra reached yields in interval 3,74-3,84 t.ha-1. Split rate of Humix komplet (III var significantly influenced yield of seeds and stems. The fertilization have increased weight of seeds in proportion to aboveground phyto-mass weight, what was expressed by harvest index.

Parkinsonian rest tremor can be detected accurately based on neuronal oscillations recorded from the subthalamic nucleus.

Science.gov (United States)

Hirschmann, J; Schoffelen, J M; Schnitzler, A; van Gerven, M A J

2017-10-01

To investigate the possibility of tremor detection based on deep brain activity. We re-analyzed recordings of local field potentials (LFPs) from the subthalamic nucleus in 10 PD patients (12 body sides) with spontaneously fluctuating rest tremor. Power in several frequency bands was estimated and used as input to Hidden Markov Models (HMMs) which classified short data segments as either tremor-free rest or rest tremor. HMMs were compared to direct threshold application to individual power features. Applying a threshold directly to band-limited power was insufficient for tremor detection (mean area under the curve [AUC] of receiver operating characteristic: 0.64, STD: 0.19). Multi-feature HMMs, in contrast, allowed for accurate detection (mean AUC: 0.82, STD: 0.15), using four power features obtained from a single contact pair. Within-patient training yielded better accuracy than across-patient training (0.84vs. 0.78, p=0.03), yet tremor could often be detected accurately with either approach. High frequency oscillations (>200Hz) were the best performing individual feature. LFP-based markers of tremor are robust enough to allow for accurate tremor detection in short data segments, provided that appropriate statistical models are used. LFP-based markers of tremor could be useful control signals for closed-loop deep brain stimulation. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

A comparison of various forecasting techniques applied to mean hourly wind speed time series

Energy Technology Data Exchange (ETDEWEB)

Sfetsos, A. [7 Pirsou Street, Athens (Greece)

2000-09-01

This paper presents a comparison of various forecasting approaches, using time series analysis, on mean hourly wind speed data. In addition to the traditional linear (ARMA) models and the commonly used feed forward and recurrent neural networks, other approaches are also examined including the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Neural Logic Networks. The developed models are evaluated for their ability to produce accurate and fast forecasts. (Author)

Time series analysis of gold production in Malaysia

Science.gov (United States)

Muda, Nora; Hoon, Lee Yuen

2012-05-01

Gold is a soft, malleable, bright yellow metallic element and unaffected by air or most reagents. It is highly valued as an asset or investment commodity and is extensively used in jewellery, industrial application, dentistry and medical applications. In Malaysia, gold mining is limited in several areas such as Pahang, Kelantan, Terengganu, Johor and Sarawak. The main purpose of this case study is to obtain a suitable model for the production of gold in Malaysia. The model can also be used to predict the data of Malaysia's gold production in the future. Box-Jenkins time series method was used to perform time series analysis with the following steps: identification, estimation, diagnostic checking and forecasting. In addition, the accuracy of prediction is tested using mean absolute percentage error (MAPE). From the analysis, the ARIMA (3,1,1) model was found to be the best fitted model with MAPE equals to 3.704%, indicating the prediction is very accurate. Hence, this model can be used for forecasting. This study is expected to help the private and public sectors to understand the gold production scenario and later plan the gold mining activities in Malaysia.

Measurement data of cesium 137 yields in primary coolant of an in-pile water loop in fission products release experiment

International Nuclear Information System (INIS)

Ishiwatari, Nasumi; Nagai, Hitoshi; Takeda, Tsuneo

1979-03-01

Series of fuel rods (UO 2 pellets sheathed with stainless steel) having an artificial pinhole were irradiated in the in-pile test section of water loop JMTR OWL-1. Presented are the results of measurements of cesium 137 yields in primary coolant of OWL-1 from 1975 to 1978. (author)

A Numerical Method for Calculating the Wave Drag of a Configuration from the Second Derivative of the Area Distribution of a Series of Equivalent Bodies of Revolution

Science.gov (United States)

Levy, Lionel L., Jr.; Yoshikawa, Kenneth K.

1959-01-01

A method based on linearized and slender-body theories, which is easily adapted to electronic-machine computing equipment, is developed for calculating the zero-lift wave drag of single- and multiple-component configurations from a knowledge of the second derivative of the area distribution of a series of equivalent bodies of revolution. The accuracy and computational time required of the method to calculate zero-lift wave drag is evaluated relative to another numerical method which employs the Tchebichef form of harmonic analysis of the area distribution of a series of equivalent bodies of revolution. The results of the evaluation indicate that the total zero-lift wave drag of a multiple-component configuration can generally be calculated most accurately as the sum of the zero-lift wave drag of each component alone plus the zero-lift interference wave drag between all pairs of components. The accuracy and computational time required of both methods to calculate total zero-lift wave drag at supersonic Mach numbers is comparable for airplane-type configurations. For systems of bodies of revolution both methods yield similar results with comparable accuracy; however, the present method only requires up to 60 percent of the computing time required of the harmonic-analysis method for two bodies of revolution and less time for a larger number of bodies.

Short-Term Change Detection in Wetlands Using Sentinel-1 Time Series

DEFF Research Database (Denmark)

Muro, Javier; Canty, Morton; Conradsen, Knut

2016-01-01

Automated monitoring systems that can capture wetlands’ high spatial and temporal variability are essential for their management. SAR-based change detection approaches offer a great opportunity to enhance our understanding of complex and dynamic ecosystems. We test a recently-developed time serie...... certain landscape changes are detected only by either the Landsat-based or the S1-omnibus method. The S1-omnibus method shows a great potential for an automated monitoring of short time changes and accurate delineation of areas of high variability and of slow and gradual changes....

Effects of application boron on yields, yield component and oil ...

African Journals Online (AJOL)

The study was conducted to investigate the effects of five boron (B) doses; 0, 2.5, 5.0, 7.5 and 10.0 kg B ha-1 in B-deficient calcareous soils on yield and some yield components of four sunflower genotypes. Genotypes have shown variations with respect to their responses to B applications. AS-615 and Coban had the ...

Determination of primary yields in the alpha radiolysis of alkaline water

International Nuclear Information System (INIS)

Auclair, Guy

2001-01-01

This work presents a fundamental study of the radiolysis of water within the framework of the management of nuclear waste. During their storage, the packages of cemented radioactive waste are likely to release molecular hydrogen. Indeed, interstitial water undergoes decomposition under irradiation. This phenomenon is called radiolysis. In order to envisage the impact of H 2 de-gasification on the security of the installations, it is necessary to determine the primary radiolytic yields in the cementing medium (characterised by a pH ranging between 12 and 14), which provides a basic simulations thus allowing us to obtain both the quantities of gas and the pressure in the pore. Such data is currently not available in the literature. Studies were undertaken with a beam of accelerated helium ions in order to reproduce the conditions of irradiation on solutions at pH = 13 in order to determine a first complete series of radiolytic yields.A more complete study was undertaken on the effects of LET and pH on the yield of molecular hydrogen. The results seem to show that the yield of this primary product is little influenced by pH. Such results were in good agreement with those obtained by Monte-Carlo simulations. These studies have shown that, contrary to γ irradiations, the irradiations with α-particles do not lead to the same characteristic times. The extrapolation of this data with respect to the problem of the packaging of nuclear waste is delicate due to the limited amount of results in the literature and also the chemical and physical complexity of the concretes. (author) [fr

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding.

Science.gov (United States)

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

Influence of Inter and Intra-rows Spacing on Yield and Yield ...

African Journals Online (AJOL)

Abyssinia

yield and yield components of fresh market(Bishola) and processing (Cochoro) tomato cultivars. ... row spacing had a significant effect on plan canopy width, above ground dry biomass, ... Poor varietal performance and management practices that includeinter and intra-row spacing ..... of assimilate export from the leaves.

Next generation hyper resolution wide swath and multi-channel optical payload for CBERS series

Science.gov (United States)

Wang, Weigang

2017-11-01

The China-Brazilian Earth Resources Satellite (CBERS) program, (also called ZY-1) the result of a space technology agreement between China and Brazil, was officially signed in 1988 after the first joint work report produced by National Institute for Space Research (INPE) and the Chinese Academy of Space Technology (CAST). During the 26 years of its existence, the program of cooperation between China and Brazil in space has achieved the successful launch of three satellites. It has become a unique example of cooperation in cutting edge technology between emerging nations. CBERS satellite is the first generation data-transferring remote sensing satellite developed by China. CBERS satellite data are widely applied to crop yield estimation, exploration of land and resources, urban planning, environmental protection and monitoring, disaster reduction, and other fields. CBERS series is just like Landsat series of USA and SPOT series of France.

Spectral Estimation of UV-Vis Absorbance Time Series for Water Quality Monitoring

Directory of Open Access Journals (Sweden)

Leonardo Plazas-Nossa

2017-05-01

Full Text Available Context: Signals recorded as multivariate time series by UV-Vis absorbance captors installed in urban sewer systems, can be non-stationary, yielding complications in the analysis of water quality monitoring. This work proposes to perform spectral estimation using the Box-Cox transformation and differentiation in order to obtain stationary multivariate time series in a wide sense. Additionally, Principal Component Analysis (PCA is applied to reduce their dimensionality. Method: Three different UV-Vis absorbance time series for different Colombian locations were studied: (i El-Salitre Wastewater Treatment Plant (WWTP in Bogotá; (ii Gibraltar Pumping Station (GPS in Bogotá; and (iii San-Fernando WWTP in Itagüí. Each UV-Vis absorbance time series had equal sample number (5705. The esti-mation of the spectral power density is obtained using the average of modified periodograms with rectangular window and an overlap of 50%, with the 20 most important harmonics from the Discrete Fourier Transform (DFT and Inverse Fast Fourier Transform (IFFT. Results: Absorbance time series dimensionality reduction using PCA, resulted in 6, 8 and 7 principal components for each study site respectively, altogether explaining more than 97% of their variability. Values of differences below 30% for the UV range were obtained for the three study sites, while for the visible range the maximum differences obtained were: (i 35% for El-Salitre WWTP; (ii 61% for GPS; and (iii 75% for San-Fernando WWTP. Conclusions: The Box-Cox transformation and the differentiation process applied to the UV-Vis absorbance time series for the study sites (El-Salitre, GPS and San-Fernando, allowed to reduce variance and to eliminate ten-dency of the time series. A pre-processing of UV-Vis absorbance time series is recommended to detect and remove outliers and then apply the proposed process for spectral estimation. Language: Spanish.

Recent Results from Lohengrin on Fission Yields and Related Decay Properties

Science.gov (United States)

Serot, O.; Amouroux, C.; Bidaud, A.; Capellan, N.; Chabod, S.; Ebran, A.; Faust, H.; Kessedjian, G.; Köester, U.; Letourneau, A.; Litaize, O.; Martin, F.; Materna, T.; Mathieu, L.; Panebianco, S.; Regis, J.-M.; Rudigier, M.; Sage, C.; Urban, W.

2014-05-01

The Lohengrin mass spectrometer is one of the 40 instruments built around the reactor of the Institute Laue-Langevin (France) which delivers a very intense thermal neutron flux. Usually, Lohengrin was combined with a high-resolution ionization chamber in order to obtain good nuclear charge discrimination within a mass line, yielding an accurate isotopic yield determination. Unfortunately, this experimental procedure can only be applied for fission products with a nuclear charge less than about 42, i.e. in the light fission fragment region. Since 2008, a large collaboration has started with the aim of studying various fission aspects, mainly in the heavy fragment region. For that, a new experimental setup which allows isotopic identification by γ-ray spectrometry has been developed and validated. This technique was applied on the 239Pu(nth,f) reaction where about 65 fission product yields were measured with an uncertainty that has been reduced on average by a factor of 2 compared with what was that previously available in nuclear data libraries. The same γ-ray spectrometric technique is currently being applied to the study of the 233U(nth,f) reaction. Our aim is to deduce charge and mass distributions of the fission products and to complete the experimental data that exist mainly for light fission fragments. The measurement of 41 mass yields from the 241Am(2nth,f) reaction has been also performed. In addition to these activities on fission yield measurements, various new nanosecond isomers were discovered. Their presence can be revealed from a strong deformed ionic charge distribution compared to a 'normal' Gaussian shape. Finally, a new neutron long-counter detector designed to have a detection efficiency independent of the detected neutron energy has been built. Combining this neutron device with a Germanium detector and a beta-ray detector array allowed us to measure the beta-delayed neutron emission probability Pn of some important fission products for reactor

Predicting Charging Time of Battery Electric Vehicles Based on Regression and Time-Series Methods: A Case Study of Beijing

Directory of Open Access Journals (Sweden)

Jun Bi

2018-04-01

Full Text Available Battery electric vehicles (BEVs reduce energy consumption and air pollution as compared with conventional vehicles. However, the limited driving range and potential long charging time of BEVs create new problems. Accurate charging time prediction of BEVs helps drivers determine travel plans and alleviate their range anxiety during trips. This study proposed a combined model for charging time prediction based on regression and time-series methods according to the actual data from BEVs operating in Beijing, China. After data analysis, a regression model was established by considering the charged amount for charging time prediction. Furthermore, a time-series method was adopted to calibrate the regression model, which significantly improved the fitting accuracy of the model. The parameters of the model were determined by using the actual data. Verification results confirmed the accuracy of the model and showed that the model errors were small. The proposed model can accurately depict the charging time characteristics of BEVs in Beijing.

Type Ia supernovae yielding distances with 3-4% precision

Energy Technology Data Exchange (ETDEWEB)

Kelly, Patrick L. [Univ. of California, Berkeley, CA (United States); Filippenko, Alexei V. [Univ. of California, Berkeley, CA (United States); Burke, David L. [SLAC National Accelerator Lab., Menlo Park, CA (United States); Hicken, Malcolm [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA (United States); Ganeshalingam, Mohan [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Zheng, Weikang [Univ. of California, Berkeley, CA (United States)

2015-01-26

The luminosities of Type Ia supernovae (SN), the thermonuclear explosions of white dwarf stars, vary systematically with their intrinsic color and light-curve decline rate. These relationships have been used to calibrate their luminosities to within ~0.14–0.20 mag from broadband optical light curves, yielding individual distances accurate to ~7–10%. Here we identify a subset of SN Ia that erupt in environments having high ultraviolet surface brightness and star-formation surface density. When we apply a steep model extinction law, these SN can be calibrated to within ~0.065–0.075 mag, corresponding to ~3–4% in distance — the best yet with SN Ia by a substantial margin. The small scatter suggests that variations in only one or two progenitor properties account for their light-curve-width/color/luminosity relation.

Phase Space Prediction of Chaotic Time Series with Nu-Support Vector Machine Regression

International Nuclear Information System (INIS)

Ye Meiying; Wang Xiaodong

2005-01-01

A new class of support vector machine, nu-support vector machine, is discussed which can handle both classification and regression. We focus on nu-support vector machine regression and use it for phase space prediction of chaotic time series. The effectiveness of the method is demonstrated by applying it to the Henon map. This study also compares nu-support vector machine with back propagation (BP) networks in order to better evaluate the performance of the proposed methods. The experimental results show that the nu-support vector machine regression obtains lower root mean squared error than the BP networks and provides an accurate chaotic time series prediction. These results can be attributable to the fact that nu-support vector machine implements the structural risk minimization principle and this leads to better generalization than the BP networks.

Secondary scintillation yield from GEM and THGEM gaseous electron multipliers for direct dark matter search

Science.gov (United States)

Monteiro, C. M. B.; Fernandes, L. M. P.; Veloso, J. F. C. A.; Oliveira, C. A. B.; dos Santos, J. M. F.

2012-07-01

The search for alternatives to PMTs as photosensors in optical TPCs for rare event detection has significantly increased in the last few years. In particular, in view of the next generation large volume detectors, the use of photosensors with lower natural radioactivity, such as large area APDs or GM-APDs, with the additional possibility of sparse surface coverage, triggered the intense study of secondary scintillation production in micropattern electron multipliers, such as GEMs and THGEMs, as alternatives to the commonly used uniform electric field region between two parallel meshes. The much higher scintillation output obtained from the electron avalanches in such microstructures presents an advantage in those situations. The accurate knowledge of the amount of such scintillation is important for correct detector simulation and optimization. It will also serve as a benchmark for software tools developed and/or under development for the calculation of the amount of such scintillation.The secondary scintillation yield, or electroluminescence yield, in the electron avalanches of GEMs and THGEMs operating in gaseous xenon and argon has been determined for different gas pressures. At 1 bar, THGEMs deliver electroluminescence yields that are more than one order of magnitude higher when compared to those achieved in GEMs and two orders of magnitude when compared to those achieved in a uniform field gap. The THGEM electroluminescence yield presents a faster decrease with pressure when comparing to the GEM electroluminescence yield, reaching similar values to what is achieved in GEMs for xenon pressures of 2.5 bar, but still one order of magnitude higher than that produced in a uniform field gap. Another exception is the GEM operating in argon, which presents an electroluminescence yield similar to that produced in a uniform electric field gap, while the THGEM achieves yields that are more than one order of magnitude higher.

Mapping Smallholder Wheat Yields and Sowing Dates Using Micro-Satellite Data

Directory of Open Access Journals (Sweden)

Meha Jain

2016-10-01

Full Text Available Remote sensing offers a low-cost method for developing spatially continuous crop production statistics across large areas and through time. Nevertheless, it has been difficult to characterize the production of individual smallholder farms, given that the land-holding size in most areas of South Asia (<2 ha is smaller than the spatial resolution of most freely available satellite imagery, like Landsat and MODIS. In addition, existing methods to map yield require field-level data to develop and parameterize predictive algorithms that translate satellite vegetation indices to yield, yet these data are costly or difficult to obtain in many smallholder systems. To overcome these challenges, this study explores two issues. First, we employ new high spatial (2 m and temporal (bi-weekly resolution micro-satellite SkySat data to map sowing dates and yields of smallholder wheat fields in Bihar, India in the 2014–2015 and 2015–2016 growing seasons. Second, we compare how well we predict sowing date and yield when using ground data, like crop cuts and self-reports, versus using crop models, which require no on-the-ground data, to develop and parameterize prediction models. Overall, sow dates were predicted well (R2 = 0.41 in 2014–2015 and R2 = 0.62 in 2015–2016, particularly when using models that were parameterized using self-report sow dates collected close to the time of planting and when using imagery that spanned the entire growing season. We were also able to map yields fairly well (R2 = 0.27 in 2014–2015 and R2 = 0.33 in 2015–2016, with crop cut parameterized models resulting in the highest accuracies. While less accurate, we were able to capture the large range in sow dates and yields across farms when using models parameterized with crop model data and these estimates were able to detect known relationships between management factors (e.g., sow date, fertilizer, and irrigation and yield. While these results are specific to our study

Status of fission yield measurements

International Nuclear Information System (INIS)

Maeck, W.J.

1979-01-01

Fission yield measurement and yield compilation activities in the major laboratories of the world are reviewed. In addition to a general review of the effort of each laboratory, a brief summary of yield measurement activities by fissioning nuclide is presented. A new fast reactor fission yield measurement program being conducted in the US is described

Linking the Negative Binomial and Logarithmic Series Distributions via their Associated Series

OpenAIRE

SADINLE, MAURICIO

2008-01-01

The negative binomial distribution is associated to the series obtained by taking derivatives of the logarithmic series. Conversely, the logarithmic series distribution is associated to the series found by integrating the series associated to the negative binomial distribution. The parameter of the number of failures of the negative binomial distribution is the number of derivatives needed to obtain the negative binomial series from the logarithmic series. The reasoning in this article could ...

Precise and accurate assay of pregnenolone and five other neurosteroids in monkey brain tissue by LC-MS/MS.

Science.gov (United States)

Dury, Alain Y; Ke, Yuyong; Labrie, Fernand

2016-09-01

A series of steroids present in the brain have been named "neurosteroids" following the possibility of their role in the central nervous system impairments such as anxiety disorders, depression, premenstrual dysphoric disorder (PMDD), addiction, or even neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. Study of their potential role requires a sensitive and accurate assay of their concentration in the monkey brain, the closest model to the human. We have thus developed a robust, precise and accurate liquid chromatography-tandem mass spectrometry method for the assay of pregnenolone, pregnanolone, epipregnanolone, allopregnanolone, epiallopregnanolone, and androsterone in the cynomolgus monkey brain. The extraction method includes a thorough sample cleanup using protein precipitation and phospholipid removal, followed by hexane liquid-liquid extraction and a Girard T ketone-specific derivatization. This method opens the possibility of investigating the potential implication of these six steroids in the most suitable animal model for neurosteroid-related research. Copyright © 2016 Elsevier Inc. All rights reserved.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

Science.gov (United States)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y; Drake, Steven K; Gucek, Marjan; Sacks, David B; Yu, Yi-Kuo

2018-06-05

Rapid and accurate identification and classification of microorganisms is of paramount importance to public health and safety. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is complicating correct microbial identification even in a simple sample due to the large number of candidates present. To properly untwine candidate microbes in samples containing one or more microbes, one needs to go beyond apparent morphology or simple "fingerprinting"; to correctly prioritize the candidate microbes, one needs to have accurate statistical significance in microbial identification. We meet these challenges by using peptide-centric representations of microbes to better separate them and by augmenting our earlier analysis method that yields accurate statistical significance. Here, we present an updated analysis workflow that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using 226 MS/MS publicly available data files (each containing from 2500 to nearly 100,000 MS/MS spectra) and 4000 additional MS/MS data files, that the updated workflow can correctly identify multiple microbes at the genus and often the species level for samples containing more than one microbe. We have also shown that the proposed workflow computes accurate statistical significances, i.e., E values for identified peptides and unified E values for identified microbes. Our updated analysis workflow MiCId, a freely available software for Microorganism Classification and Identification, is available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html . Graphical Abstract ᅟ.

Duality in a Supersymmetric Gauge Theory From a Perturbative Viewpoint

DEFF Research Database (Denmark)

Ryttov, Thomas A.; Shrock, Robert

2018-01-01

points of the renormalization group emerge in scheme-independent series expansions in the electric and magnetic theories. We further demonstrate that truncations of these series expansions to modest order yield very accurate approximations to these quantities and suggest possible implications......We study duality in N ¼ 1 supersymmetric QCD in the non-Abelian Coulomb phase, order-by-order in scheme-independent series expansions. Using exact results, we show how the dimensions of various fundamental and composite chiral superfields, and the quantities a, c, a=c, and b at superconformal fixed...

Nonlinear Prediction Model for Hydrologic Time Series Based on Wavelet Decomposition

Science.gov (United States)

Kwon, H.; Khalil, A.; Brown, C.; Lall, U.; Ahn, H.; Moon, Y.

2005-12-01

Traditionally forecasting and characterizations of hydrologic systems is performed utilizing many techniques. Stochastic linear methods such as AR and ARIMA and nonlinear ones such as statistical learning theory based tools have been extensively used. The common difficulty to all methods is the determination of sufficient and necessary information and predictors for a successful prediction. Relationships between hydrologic variables are often highly nonlinear and interrelated across the temporal scale. A new hybrid approach is proposed for the simulation of hydrologic time series combining both the wavelet transform and the nonlinear model. The present model employs some merits of wavelet transform and nonlinear time series model. The Wavelet Transform is adopted to decompose a hydrologic nonlinear process into a set of mono-component signals, which are simulated by nonlinear model. The hybrid methodology is formulated in a manner to improve the accuracy of a long term forecasting. The proposed hybrid model yields much better results in terms of capturing and reproducing the time-frequency properties of the system at hand. Prediction results are promising when compared to traditional univariate time series models. An application of the plausibility of the proposed methodology is provided and the results conclude that wavelet based time series model can be utilized for simulating and forecasting of hydrologic variable reasonably well. This will ultimately serve the purpose of integrated water resources planning and management.

Grain yield losses in yellow-rusted durum wheat estimated using digital and conventional parameters under field conditions

Directory of Open Access Journals (Sweden)

Omar Vergara-Diaz

2015-06-01

Full Text Available The biotrophic fungus Puccinia striiformis f. sp. tritici is the causal agent of the yellow rust in wheat. Between the years 2010–2013 a new strain of this pathogen (Warrior/Ambition, against which the present cultivated wheat varieties have no resistance, appeared and spread rapidly. It threatens cereal production in most of Europe. The search for sources of resistance to this strain is proposed as the most efficient and safe solution to ensure high grain production. This will be helped by the development of high performance and low cost techniques for field phenotyping. In this study we analyzed vegetation indices in the Red, Green, Blue (RGB images of crop canopies under field conditions. We evaluated their accuracy in predicting grain yield and assessing disease severity in comparison to other field measurements including the Normalized Difference Vegetation Index (NDVI, leaf chlorophyll content, stomatal conductance, and canopy temperature. We also discuss yield components and agronomic parameters in relation to grain yield and disease severity. RGB-based indices proved to be accurate predictors of grain yield and grain yield losses associated with yellow rust (R2 = 0.581 and R2 = 0.536, respectively, far surpassing the predictive ability of NDVI (R2 = 0.118 and R2 = 0.128, respectively. In comparison to potential yield, we found the presence of disease to be correlated with reductions in the number of grains per spike, grains per square meter, kernel weight and harvest index. Grain yield losses in the presence of yellow rust were also greater in later heading varieties. The combination of RGB-based indices and days to heading together explained 70.9% of the variability in grain yield and 62.7% of the yield losses.

Magnetic Field Emission Comparison for Series-Parallel and Series-Series Wireless Power Transfer to Vehicles – PART 1/2

DEFF Research Database (Denmark)

Batra, Tushar; Schaltz, Erik

2014-01-01

Resonant circuits of wireless power transfer system can be designed in four possible ways by placing the primary and secondary capacitor in a series or parallel order with respect to the corresponding inductor. The two topologies series-parallel and series-series under investigation have been...... already compared in terms of their output behavior (current or voltage source) and reflection of the secondary impedance on the primary side. In this paper it is shown that for the same power rating series-parallel topology emits lesser magnetic fields to the surroundings than its series...

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).

Science.gov (United States)

Liu, Xiaojun; Ferguson, Richard B; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-03-24

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI = ( 1 + e - 15.2829 × ( R A G D D i - 0.1944 ) ) - 1 - ( 1 + e - 11.6517 × ( R A G D D i - 1.0267 ) ) - 1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status.

Systematic staging design applied to the fixed-bed reactor series for methanol and one-step methanol/dimethyl ether synthesis

International Nuclear Information System (INIS)

Manenti, Flavio; Leon-Garzon, Andres R.; Ravaghi-Ardebili, Zohreh; Pirola, Carlo

2014-01-01

This work investigates possible design advances in the series of fixed-bed reactors for methanol and dimethyl ether synthesis. Specifically, the systematic staging design proposed by Hillestad [1] is applied to the water-cooled and gas-cooled series of reactors of Lurgi's technology. The procedure leads to new design and operating conditions with respect to the current best industrial practice, with relevant benefits in terms of process yield, energy saving, and net income. The overall mathematical model for the process simulation and optimization is reported in the work together with dedicated sensitivity analysis studies. - Highlights: • Systematic staging design is applied to methanol and methanol/DME synthesis. • New configurations for the synthesis reactor network are proposed and assessed. • Comparison with the industrial best practice is provided. • Energy-process optimization is performed to improve the overall yield of the process

Simulation of winter wheat yield and its variability in different climates of Europe: A comparison of eight crop growth models

DEFF Research Database (Denmark)

Palosuo, Taru; Kersebaum, Kurt Christian; Angulo, Carlos

2011-01-01

observations at all sites and in all years, and none could unequivocally be labelled robust and accurate in terms of yield prediction across different environments and crop cultivars with only minimum calibration. The best performance regarding yield estimation was for DAISY and DSSAT, for which the RMSE...... and WOFOST furnished high total above-ground biomass estimates, whereas CROPSYST, DSSAT and FASSET provided low total above-ground estimates. Consequently, DSSAT and FASSET produced very high harvest index values, followed by HERMES and WOFOST. APES and DAISY, on the other hand, returned low harvest index...... of grain yield estimates provided by the models for all sites and years reflects substantial uncertainties in model estimates achieved with only minimum calibration. Mean predictions from the eight models, on the other hand, were in good agreement with measured data. This applies to both results across all...

Measurements of fission yields

International Nuclear Information System (INIS)

Denschlag, H.O.

2000-01-01

After some historical introductory remarks on the discovery of nuclear fission and early fission yield determinations, the present status of knowledge on fission yields is briefly reviewed. Practical and fundamental reasons motivating the pursuit of fission yield measurements in the coming century are pointed out. Recent results and novel techniques are described that promise to provide new interesting insights into the fission process during the next century. (author)

Stable isotope time series and dentin increments elucidate Pleistocene proboscidean paleobiology

Science.gov (United States)

Fisher, Daniel; Rountrey, Adam; Smith, Kathlyn; Fox, David

2010-05-01

Investigations of stable isotope composition of mineralized tissues have added greatly to our knowledge of past climates and dietary behaviors of organisms, even when they are implemented through 'bulk sampling', in which a single assay yields a single, time-averaged value. Likewise, the practice of 'sclerochronology', which documents periodic structural increments comprising a growth record for accretionary tissues, offers insights into rates of growth and age data at a scale of temporal resolution permitted by the nature of structural increments. We combine both of these approaches to analyze dental tissues of late Pleistocene proboscideans. Tusk dentin typically preserves a record of accretionary growth consisting of histologically distinct increments on daily, approximately weekly, and yearly time scales. Working on polished transverse or longitudinal sections, we mill out a succession of temporally controlled dentin samples bounded by clear structural increments with a known position in the sequence of tusk growth. We further subject each sample (or an aliquot thereof) to multiple compositional analyses - most frequently to assess δ18O and δ13C of hydroxyapatite carbonate, and δ13C and δ15N of collagen. This yields, for each animal and each series of years investigated, a set of parallel compositional time series with a temporal resolution of 1-2 months (or finer if we need additional precision). Patterns in variation of thickness of periodic sub-annual increments yield insight into intra-annual and inter-annual variation of tusk growth rate. This is informative even by itself, but it is still more valuable when coupled with compositional time series. Further, the controls on different stable isotope systems are sufficiently different that the data ensemble yields 'much more than the sum of its parts.' By assessing how compositions and growth rates covary, we monitor with greater confidence changes in local climate, diet, behavior, and health status. We

Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration

Science.gov (United States)

Scott, James R.; Martini, Michael C.

2011-01-01

A variable-order, variable-step Taylor series integration algorithm was implemented in NASA Glenn's SNAP (Spacecraft N-body Analysis Program) code. SNAP is a high-fidelity trajectory propagation program that can propagate the trajectory of a spacecraft about virtually any body in the solar system. The Taylor series algorithm's very high order accuracy and excellent stability properties lead to large reductions in computer time relative to the code's existing 8th order Runge-Kutta scheme. Head-to-head comparison on near-Earth, lunar, Mars, and Europa missions showed that Taylor series integration is 15.8 times faster than Runge- Kutta on average, and is more accurate. These speedups were obtained for calculations involving central body, other body, thrust, and drag forces. Similar speedups have been obtained for calculations that include J2 spherical harmonic for central body gravitation. The algorithm includes a step size selection method that directly calculates the step size and never requires a repeat step. High-order Taylor series integration algorithms have been shown to provide major reductions in computer time over conventional integration methods in numerous scientific applications. The objective here was to directly implement Taylor series integration in an existing trajectory analysis code and demonstrate that large reductions in computer time (order of magnitude) could be achieved while simultaneously maintaining high accuracy. This software greatly accelerates the calculation of spacecraft trajectories. At each time level, the spacecraft position, velocity, and mass are expanded in a high-order Taylor series whose coefficients are obtained through efficient differentiation arithmetic. This makes it possible to take very large time steps at minimal cost, resulting in large savings in computer time. The Taylor series algorithm is implemented primarily through three subroutines: (1) a driver routine that automatically introduces auxiliary variables and

Effect of sulfur and iron fertilizers on yield, yield components and ...

African Journals Online (AJOL)

Jane

2011-06-13

Jun 13, 2011 ... per plant. Interaction between water stress and combination of iron and sulfur fertilizers had significant .... Results of analysis of variance (ANOVA) of water stress (W), sulfur (B) and iron (C), and their interaction with gain yield, yield components and ... the soil structure and it increased the usefulness of other.

Effect of water stress on yield and yield components of sunflower ...

African Journals Online (AJOL)

A field experiment during year 2009 was conducted in the research station of the University of Tehran, College of Abouraihan in Pakdasht region, Iran. The study was aimed to investigate the effect of water stress on seed yield, yield component and some quantitative traits of four sunflower hybrids namely Azargol, Alstar, ...

Path coefficient and correlation of yield and yield associated traits in candidate bread wheat (triticum aestivum l)lines

International Nuclear Information System (INIS)

Muhammad, T.; Haider, S.; Qureshi, M. J.; Shah, G. S.; Zamir, R.

2005-01-01

Yield and yield contributing traits were studied in candidate bread wheat lines to find out the genetic contribution of the different characters towards grain yield at NIFA, Peshawar during 2001-02. All the characteristics studied differed significantly from each other. Days to heading showed negative and significant correlation with harvest index and grain yield but was negative and non-significant with the biological yield. Days to maturity were negatively correlated at both genotypic and phenotypic levels with biological yield; harvest index and grain yield and level of correlations were significant with harvest index and grain yield. Plant height showed negative genotypic and phenotypic correlation with harvest index and grain yield. Biological yield had positive and significant genotypic and phenotypic correlations with harvest index and grain yield. Harvest index had positive and highly significant genotypic and phenotypic correlation with grain yield. Genotypic and phenotypic correlation coefficients revealed that important characters influencing grain yield are harvest index and biological yield. Path analysis showed the importance in order of harvest index, biological yield, plant height, days to maturity and days to heading with grain yield. (author)

A better understanding of long-range temporal dependence of traffic flow time series

Science.gov (United States)

Feng, Shuo; Wang, Xingmin; Sun, Haowei; Zhang, Yi; Li, Li

2018-02-01

Long-range temporal dependence is an important research perspective for modelling of traffic flow time series. Various methods have been proposed to depict the long-range temporal dependence, including autocorrelation function analysis, spectral analysis and fractal analysis. However, few researches have studied the daily temporal dependence (i.e. the similarity between different daily traffic flow time series), which can help us better understand the long-range temporal dependence, such as the origin of crossover phenomenon. Moreover, considering both types of dependence contributes to establishing more accurate model and depicting the properties of traffic flow time series. In this paper, we study the properties of daily temporal dependence by simple average method and Principal Component Analysis (PCA) based method. Meanwhile, we also study the long-range temporal dependence by Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA). The results show that both the daily and long-range temporal dependence exert considerable influence on the traffic flow series. The DFA results reveal that the daily temporal dependence creates crossover phenomenon when estimating the Hurst exponent which depicts the long-range temporal dependence. Furthermore, through the comparison of the DFA test, PCA-based method turns out to be a better method to extract the daily temporal dependence especially when the difference between days is significant.

Summation of series

CERN Document Server

Jolley, LB W

2004-01-01

Over 1,100 common series, all grouped for easy reference. Arranged by category, these series include arithmetical and geometrical progressions, powers and products of natural numbers, figurate and polygonal numbers, inverse natural numbers, exponential and logarithmic series, binomials, simple inverse products, factorials, trigonometrical and hyperbolic expansions, and additional series. 1961 edition.

Time series analysis of the behavior of brazilian natural rubber

Directory of Open Access Journals (Sweden)

Antônio Donizette de Oliveira

2009-03-01

Full Text Available The natural rubber is a non-wood product obtained of the coagulation of some lattices of forest species, being Hevea brasiliensis the main one. Native from the Amazon Region, this species was already known by the Indians before the discovery of America. The natural rubber became a product globally valued due to its multiple applications in the economy, being its almost perfect substitute the synthetic rubber derived from the petroleum. Similarly to what happens with other countless products the forecast of future prices of the natural rubber has been object of many studies. The use of models of forecast of univariate timeseries stands out as the more accurate and useful to reduce the uncertainty in the economic decision making process. This studyanalyzed the historical series of prices of the Brazilian natural rubber (R$/kg, in the Jan/99 - Jun/2006 period, in order tocharacterize the rubber price behavior in the domestic market; estimated a model for the time series of monthly natural rubberprices; and foresaw the domestic prices of the natural rubber, in the Jul/2006 - Jun/2007 period, based on the estimated models.The studied models were the ones belonging to the ARIMA family. The main results were: the domestic market of the natural rubberis expanding due to the growth of the world economy; among the adjusted models, the ARIMA (1,1,1 model provided the bestadjustment of the time series of prices of the natural rubber (R$/kg; the prognosis accomplished for the series supplied statistically adequate fittings.

Measurement of neutron yield by 62 MeV proton beam on a thick beryllium target

Energy Technology Data Exchange (ETDEWEB)

Osipenko, M., E-mail: osipenko@ge.infn.it [INFN, sezione di Genova, 16146 Genova (Italy); Ripani, M. [INFN, sezione di Genova, 16146 Genova (Italy); Alba, R. [INFN, Laboratori Nazionali del Sud, 95123 Catania (Italy); Ricco, G. [INFN, sezione di Genova, 16146 Genova (Italy); Schillaci, M. [INFN, Laboratori Nazionali del Sud, 95123 Catania (Italy); Barbagallo, M. [INFN, sezione di Bari, 70126 Bari (Italy); Boccaccio, P. [INFN, Laboratori Nazionali di Legnaro, 35020 Legnaro (Italy); Celentano, A. [Dipartimento di Fisica dell' Università di Genova, 16146 Genova (Italy); Colonna, N. [INFN, sezione di Bari, 70126 Bari (Italy); Cosentino, L.; Del Zoppo, A.; Di Pietro, A. [INFN, Laboratori Nazionali del Sud, 95123 Catania (Italy); Esposito, J. [INFN, Laboratori Nazionali di Legnaro, 35020 Legnaro (Italy); Figuera, P.; Finocchiaro, P. [INFN, Laboratori Nazionali del Sud, 95123 Catania (Italy); Kostyukov, A. [Moscow State University, Moscow 119992 (Russian Federation); Maiolino, C.; Santonocito, D.; Scuderi, V. [INFN, Laboratori Nazionali del Sud, 95123 Catania (Italy); Viberti, C.M. [Dipartimento di Fisica dell' Università di Genova, 16146 Genova (Italy)

2013-09-21

The design of a low-power prototype of neutron amplifier recently proposed within the INFN-E project indicated the need for more accurate data on the neutron yield produced by a proton beam with energy of about 70 MeV impinging on a thick beryllium target. Such measurement was performed at the LNS superconducting cyclotron, covering a wide angular range from 0° to 150° and a complete neutron energy interval from thermal to beam energy. Neutrons with energy above 0.5 MeV were measured by liquid scintillators exploiting their time of flight to determine the kinetic energy. For lower energy neutrons, down to thermal energy, a {sup 3}He detector was used. The obtained data are in good agreement with previous measurements at 0° using 66 MeV proton beam, covering neutron energies >10MeV, as well as with measurements at few selected angles using protons of 46, 55 and 113 MeV energy. The present results extend the neutron yield data in the 60–70 MeV beam energy range. A comparison of measured yields to MCNP, FLUKA and Geant4 Monte Carlo simulations was performed.

Estimation of yield and water requirements of maize crops combining high spatial and temporal resolution images with a simple crop model, in the perspective of the Sentinel-2 mission

Science.gov (United States)

Battude, Marjorie; Bitar, Ahmad Al; Brut, Aurore; Cros, Jérôme; Dejoux, Jean-François; Huc, Mireille; Marais Sicre, Claire; Tallec, Tiphaine; Demarez, Valérie

2016-04-01

Water resources are under increasing pressure as a result of global change and of a raising competition among the different users (agriculture, industry, urban). It is therefore important to develop tools able to estimate accurately crop water requirements in order to optimize irrigation while maintaining acceptable production. In this context, remote sensing is a valuable tool to monitor vegetation development and water demand. This work aims at developing a robust and generic methodology mainly based on high resolution remote sensing data to provide accurate estimates of maize yield and water needs at the watershed scale. Evapotranspiration (ETR) and dry aboveground biomass (DAM) of maize crops were modeled using time series of GAI images used to drive a simple agro-meteorological crop model (SAFYE, Duchemin et al., 2005). This model is based on a leaf partitioning function (Maas, 1993) for the simulation of crop biomass and on the FAO-56 methodology for the ETR simulation. The model also contains a module to simulate irrigation. This study takes advantage of the SPOT4 and SPOT5 Take5 experiments initiated by CNES (http://www.cesbio.ups-tlse.fr/multitemp/). They provide optical images over the watershed from February to May 2013 and from April to August 2015 respectively, with a temporal and spatial resolution similar to future images from the Sentinel-2 and VENμS missions. This dataset was completed with LandSat8 and Deimos1 images in order to cover the whole growing season while reducing the gaps in remote sensing time series. Radiometric, geometric and atmospheric corrections were achieved by the THEIA land data center, and the KALIDEOS processing chain. The temporal dynamics of the green area index (GAI) plays a key role in soil-plant-atmosphere interactions and in biomass accumulation process. Consistent seasonal dynamics of the remotely sensed GAI was estimated by applying a radiative transfer model based on artificial neural networks (BVNET, Baret

Influence of Machine-Derived Smoke Yields on Biomarker of Exposure (BOE Levels in Cigarette Smokers*

Directory of Open Access Journals (Sweden)

Scherer Gerhard

2015-01-01

Full Text Available Individual uptake of tobacco smoke constituents by smoking is highly variable in cigarette smokers and cannot be predicted by smoking behaviour variables and machine-derived smoke yields. It is well established that uptake of smoke constituents is best described by a series of bio-markers of exposure (BOEs such as metabolites of nico-tine, tobacco-specific nitrosamines (TSNAs, polycyclic aromatic hydrocarbons (PAHs, aromatic amines, benzene, 1,3-butadiene, acrolein, hydrogen cyanide, 2,5-dimethyl-furan and other smoke constituents.

Seed yield and some yield components of sesame as affected by ...

African Journals Online (AJOL)

In order to study the effect of different irrigation, N and superabsorbent levels on yield and yield components of sesame, a field experiment was conducted in Khosf Region, Birjand, Iran in 2009 as a split-split plot design based on a randomized complete block design. The treatments included irrigation interval at three levels ...

Comparing the performance of 11 crop simulation models in predicting yield response to nitrogen fertilization

DEFF Research Database (Denmark)

Salo, T J; Palosuo, T; Kersebaum, K C

2016-01-01

Eleven widely used crop simulation models (APSIM, CERES, CROPSYST, COUP, DAISY, EPIC, FASSET, HERMES, MONICA, STICS and WOFOST) were tested using spring barley (Hordeum vulgare L.) data set under varying nitrogen (N) fertilizer rates from three experimental years in the boreal climate of Jokioinen......, Finland. This is the largest standardized crop model inter-comparison under different levels of N supply to date. The models were calibrated using data from 2002 and 2008, of which 2008 included six N rates ranging from 0 to 150 kg N/ha. Calibration data consisted of weather, soil, phenology, leaf area...... ranged from 170 to 870 kg/ha. During the test year 2009, most models failed to accurately reproduce the observed low yield without N fertilizer as well as the steep yield response to N applications. The multi-model predictions were closer to observations than most single-model predictions, but multi...

a Landsat Time-Series Stacks Model for Detection of Cropland Change

Science.gov (United States)

Chen, J.; Chen, J.; Zhang, J.

2017-09-01

Global, timely, accurate and cost-effective cropland monitoring with a fine spatial resolution will dramatically improve our understanding of the effects of agriculture on greenhouse gases emissions, food safety, and human health. Time-series remote sensing imagery have been shown particularly potential to describe land cover dynamics. The traditional change detection techniques are often not capable of detecting land cover changes within time series that are severely influenced by seasonal difference, which are more likely to generate pseuso changes. Here,we introduced and tested LTSM ( Landsat time-series stacks model), an improved Continuous Change Detection and Classification (CCDC) proposed previously approach to extract spectral trajectories of land surface change using a dense Landsat time-series stacks (LTS). The method is expected to eliminate pseudo changes caused by phenology driven by seasonal patterns. The main idea of the method is that using all available Landsat 8 images within a year, LTSM consisting of two term harmonic function are estimated iteratively for each pixel in each spectral band .LTSM can defines change area by differencing the predicted and observed Landsat images. The LTSM approach was compared with change vector analysis (CVA) method. The results indicated that the LTSM method correctly detected the "true change" without overestimating the "false" one, while CVA pointed out "true change" pixels with a large number of "false changes". The detection of change areas achieved an overall accuracy of 92.37 %, with a kappa coefficient of 0.676.

Mapping Cropland and Crop-type Distribution Using Time Series MODIS Data

Science.gov (United States)

Lu, D.; Chen, Y.; Moran, E. F.; Batistella, M.; Luo, L.; Pokhrel, Y.; Deb, K.

2016-12-01

Mapping regional and global cropland distribution has attracted great attention in the past decade, but the separation of crop types is challenging due to the spectral confusion and cloud cover problems during the growing season in Brazil. The objective of this study is to develop a new approach to identify crop types (including soybean, cotton, maize) and planting patterns (soybean-maize, soybean-cotton, and single crop) in Mato Grosso, Goias and Tocantins States, Brazil. The time series moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) (MOD13Q1) in 2015/2016 were used in this research and field survey data were collected in May 2016. The major steps include: (1) reconstruct time series NDVI data contaminated by noise and clouds using the temporal interpolation algorithm; (2) identify the best periods and develop temporal indices and phenology parameters to distinguish cropland from other land cover types based on time series NDVI data; (3) develop a crop temporal difference index (CTDI) to extract crop types and patterns using time series NDVI data. This research shows that (1) the cropland occupied approximately 16.85% of total land in these three states; (2) soybean-maize and soybean-cotton were two major crop patterns which occupied 54.80% and 19.30% of total cropland area. This research indicates that the proposed approach is promising for accurately and rapidly mapping cropland and crop-type distribution in these three states of Brazil.

Statistical tools for analysis and modeling of cosmic populations and astronomical time series: CUDAHM and TSE

Science.gov (United States)

Loredo, Thomas; Budavari, Tamas; Scargle, Jeffrey D.

2018-01-01

This presentation provides an overview of open-source software packages addressing two challenging classes of astrostatistics problems. (1) CUDAHM is a C++ framework for hierarchical Bayesian modeling of cosmic populations, leveraging graphics processing units (GPUs) to enable applying this computationally challenging paradigm to large datasets. CUDAHM is motivated by measurement error problems in astronomy, where density estimation and linear and nonlinear regression must be addressed for populations of thousands to millions of objects whose features are measured with possibly complex uncertainties, potentially including selection effects. An example calculation demonstrates accurate GPU-accelerated luminosity function estimation for simulated populations of $10^6$ objects in about two hours using a single NVIDIA Tesla K40c GPU. (2) Time Series Explorer (TSE) is a collection of software in Python and MATLAB for exploratory analysis and statistical modeling of astronomical time series. It comprises a library of stand-alone functions and classes, as well as an application environment for interactive exploration of times series data. The presentation will summarize key capabilities of this emerging project, including new algorithms for analysis of irregularly-sampled time series.

Measurement of mass and isotopic fission yields for heavy fission products with the LOHENGRIN mass spectrometer

International Nuclear Information System (INIS)

Bail, A.

2009-05-01

In spite of the huge amount of fission yield data available in different libraries, more accurate values are still needed for nuclear energy applications and to improve our understanding of the fission process. Thus measurements of fission yields were performed at the mass spectrometer Lohengrin at the Institut Laue-Langevin in Grenoble, France. The mass separator Lohengrin is situated at the research reactor of the institute and permits the placement of an actinide layer in a high thermal neutron flux. It separates fragments according to their atomic mass, kinetic energy and ionic charge state by the action of magnetic and electric fields. Coupled to a high resolution ionization chamber the experiment was used to investigate the mass and isotopic yields of the light mass region. Almost all fission yields of isotopes from Th to Cf have been measured at Lohengrin with this method. To complete and improve the nuclear data libraries, these measurements have been extended in this work to the heavy mass region for the reactions 235 U(n th ,f), 239 Pu(n th ,f) and 241 Pu(n th ,f). For these higher masses an isotopic separation is no longer possible. So, a new method was undertaken with the reaction 239 Pu(n th ,f) to determine the isotopic yields by spectrometry. These experiments have allowed to reduce considerably the uncertainties. Moreover the ionic charge state and kinetic energy distributions were specifically studied and have shown, among others, nanosecond isomers for some masses. (author)

Influences of nitrogen and potassium top dressing on yield and yield ...

African Journals Online (AJOL)

STORAGESEVER

2010-05-03

May 3, 2010 ... (K) top dressing on grain yield and yield components of rice (Oryza sativa cv. Tarrom) and to ... positive reciprocal effect on crops, and was an important approach in ..... dressing fertilization (Figures 2a, b and c), but nitrogen levels of upper fully .... (Brassica napus L.)–rice (Oryza sativa L.) rotation. Plant Soil ...

Inheritance of grain yield and its correlation with yield components in ...

African Journals Online (AJOL)

SAM

2014-03-19

Mar 19, 2014 ... average yield of wheat in China is 4.75 t ha-1, which is low compared to other .... Analysis of variance for combining ability for grain yield plant-1. Source of variation ..... Hayman BI (1954). The theory and analysis of diallel crosses. .... Analysis and prospect of China wheat market in 2011. Food and Oil.

The study of coastal groundwater depth and salinity variation using time-series analysis

International Nuclear Information System (INIS)

Tularam, G.A.; Keeler, H.P.

2006-01-01

A time-series approach is applied to study and model tidal intrusion into coastal aquifers. The authors examine the effect of tidal behaviour on groundwater level and salinity intrusion for the coastal Brisbane region using auto-correlation and spectral analyses. The results show a close relationship between tidal behaviour, groundwater depth and salinity levels for the Brisbane coast. The known effect can be quantified and incorporated into new models in order to more accurately map salinity intrusion into coastal groundwater table

Flood Frequency Analysis For Partial Duration Series In Ganjiang River Basin

Science.gov (United States)

zhangli, Sun; xiufang, Zhu; yaozhong, Pan

2016-04-01

Accurate estimation of flood frequency is key to effective, nationwide flood damage abatement programs. The partial duration series (PDS) method is widely used in hydrologic studies because it considers all events above a certain threshold level as compared to the annual maximum series (AMS) method, which considers only the annual maximum value. However, the PDS has a drawback in that it is difficult to define the thresholds and maintain an independent and identical distribution of the partial duration time series; this drawback is discussed in this paper. The Ganjiang River is the seventh largest tributary of the Yangtze River, the longest river in China. The Ganjiang River covers a drainage area of 81,258 km2 at the Wanzhou hydrologic station as the basin outlet. In this work, 56 years of daily flow data (1954-2009) from the Wanzhou station were used to analyze flood frequency, and the Pearson-III model was employed as the hydrologic probability distribution. Generally, three tasks were accomplished: (1) the threshold of PDS by percentile rank of daily runoff was obtained; (2) trend analysis of the flow series was conducted using PDS; and (3) flood frequency analysis was conducted for partial duration flow series. The results showed a slight upward trend of the annual runoff in the Ganjiang River basin. The maximum flow with a 0.01 exceedance probability (corresponding to a 100-year flood peak under stationary conditions) was 20,000 m3/s, while that with a 0.1 exceedance probability was 15,000 m3/s. These results will serve as a guide to hydrological engineering planning, design, and management for policymakers and decision makers associated with hydrology.

Simulated vs. empirical weather responsiveness of crop yields: US evidence and implications for the agricultural impacts of climate change

Science.gov (United States)

Mistry, Malcolm N.; Wing, Ian Sue; De Cian, Enrica

2017-07-01

Global gridded crop models (GGCMs) are the workhorse of assessments of the agricultural impacts of climate change. Yet the changes in crop yields projected by different models in response to the same meteorological forcing can differ substantially. Through an inter-method comparison, we provide a first glimpse into the origins and implications of this divergence—both among GGCMs and between GGCMs and historical observations. We examine yields of rainfed maize, wheat, and soybeans simulated by six GGCMs as part of the Inter-Sectoral Impact Model Intercomparison Project-Fast Track (ISIMIP-FT) exercise, comparing 1981-2004 hindcast yields over the coterminous United States (US) against US Department of Agriculture (USDA) time series for about 1000 counties. Leveraging the empirical climate change impacts literature, we estimate reduced-form econometric models of crop yield responses to temperature and precipitation exposures for both GGCMs and observations. We find that up to 60% of the variance in both simulated and observed yields is attributable to weather variation. A majority of the GGCMs have difficulty reproducing the observed distribution of percentage yield anomalies, and exhibit aggregate responses that show yields to be more weather-sensitive than in the observational record over the predominant range of temperature and precipitation conditions. This disparity is largely attributable to heterogeneity in GGCMs’ responses, as opposed to uncertainty in historical weather forcings, and is responsible for widely divergent impacts of climate on future crop yields.

Supplemental exogenous NPK application alters biochemical processes to improve yield and drought tolerance in wheat (Triticum aestivum L.).

Science.gov (United States)

Shabbir, Rana Nauman; Waraich, E A; Ali, H; Nawaz, F; Ashraf, M Y; Ahmad, R; Awan, M I; Ahmad, S; Irfan, M; Hussain, S; Ahmad, Z

2016-02-01

The recent food security issues, combined with the threats from climate change, demand future farming systems to be more precise and accurate to fulfill the ever increasing global food requirements. The role of nutrients such as nitrogen (N), phosphorous (P), and potassium (K) in stimulating plant growth and development is well established; however, little is known about their function, if applied in combination, in improving crop yields under environmental stresses like drought. The aim of this study was to evaluate the effects of combined foliar spray of supplemental NPK (NPKc) on physiological and biochemical mechanisms that enhance the drought tolerance potential of wheat for improved yield. Foliar NPKc markedly influenced the accumulation of osmoprotectants and activity of both nitrogen assimilation and antioxidant enzymes. It significantly improved the concentration of proline (66 %), total soluble sugars (37 %), and total soluble proteins (10 %) and enhanced the activity of nitrate reductase, nitrite reductase, catalase, and peroxidase by 47, 45, 19, and 8 %, respectively, with respect to no spray under water-deficit conditions which, in turn, improve the yield and yield components. The accumulation of osmolytes and activity of antioxidant machinery were more pronounced in drought tolerant (Bhakkar-02) than sensitive genotype (Shafaq-06).

Effect of Biofertilizers on the Yield and Yield Components of Black Cumin (Nigella sativa L.

Directory of Open Access Journals (Sweden)

S Khorramdel

2011-02-01

Full Text Available Abstract Application of biological fertilizers is one of the most important methods for plant nutrition in ecological agriculture. In order to investigate the effect of biofertilizers on yield and yield components of black cumin (Nigella sativa L., a field experiment was arranged in a randomized complete block design with three replications during 2007 growing season at the Agricultural Research Station of Ferdowsi University of Mashhad. Treatments included: (A Azotobacter paspali, (B Azospirillum brasilense, (C the fungus of Glomus intraradaices, C+A, C+B, A+B, A+B+C, and control without no biofertilizers. In all treatments except control, the amounts of 15 mg of each biofertilizer were applied to 110 g of seeds. Results indicated that application of biofertilizers enhanced yield and yield components and decreased percentage of hollow capsules. Plant performance was better with application of Azospirillum plus mycorrhiza and a mixture of Azotobacter, Azospirillum and mycorrhiza in terms of yield determining criteria. The maximum and minimum amounts of seed yield were recorded in the B+C treatment with 41.4 gm-2, and control with 24.1 gm-2, respectively. There was no significant correlation between number of capsules per plant and seed yield, but the positive and significant correlation between number of branches per plant, number of seeds per capsule, 1000-seed weight and seed yield was observed. This study showed that application of suitable biofertilizers could increase yield and yield components of black cumin. Keywords: Biofertilizer, Ecological agriculture, Medicinal plants, Plant growth promoting rhizobacteria

Fostering accurate HIV/AIDS knowledge among unmarried youths in Cameroon: Do family environment and peers matter?

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Kuate Defo Barthelemy

2011-05-01

Full Text Available Abstract Background The last three decades have seen a series of HIV interventions in sub-Saharan Africa. However, youths still have a mixture of correct and incorrect HIV/AIDS knowledge of transmission routes and prevention strategies. Previous studies have identified parents and peers as the most important socializing agents for youths. This paper assesses the relationships between family structure, family/peer communication about sexuality and accurate knowledge of transmission routes and prevention strategies. Methods Data were drawn from the Cameroon Family Life and Health Survey (CFHS conducted in 2002. The CFHS collected information on a representative sample of 4 950 people aged 10 years and over nested within 1 765 selected households from the 75 localities forming the administrative prefecture of Bandjoun, using detailed questionnaires about family, HIV/AIDS/STDs knowledge, sexual behaviors, contraception, health, media exposure, household assets and neighborhood characteristics. The survey cooperation rates were high (97%. For the purpose of this study, a sub-sample of 2 028 unmarried youths aged 12 - 29 years was utilized. Results Overall, 42% of respondents reported accurate knowledge of documented HIV transmission routes whereas 21% of them had inaccurate knowledge such as AIDS can be transmitted through mosquito bites or casual contact with an infected person. Only 9% of respondents were knowledgeable about all HIV prevention strategies. Multivariate analyses showed that family structure, communication with parents/guardians and peers about sexual topics were significantly associated with accurate HIV knowledge. Additionally, age, education, sexual experience and migration had significant effects on accurate knowledge. Finally, living in poor households and disadvantaged neighborhoods significantly increased inaccurate knowledge of HIV transmission modes and prevention strategies. Conclusions This paper evidenced the limited

Biofuels from pyrolysis in perspective: trade-offs between energy yields and soil-carbon additions.

Science.gov (United States)

Woolf, Dominic; Lehmann, Johannes; Fisher, Elizabeth M; Angenent, Largus T

2014-06-03

Coproduction of biofuels with biochar (the carbon-rich solid formed during biomass pyrolysis) can provide carbon-negative bioenergy if the biochar is sequestered in soil, where it can improve fertility and thus simultaneously address issues of food security, soil degradation, energy production, and climate change. However, increasing biochar production entails a reduction in bioenergy obtainable per unit biomass feedstock. Quantification of this trade-off for specific biochar-biofuel pathways has been hampered by lack of an accurate-yet-simple model for predicting yields, product compositions, and energy balances from biomass slow pyrolysis. An empirical model of biomass slow pyrolysis was developed and applied to several pathways for biochar coproduction with gaseous and liquid biofuels. Here, we show that biochar production reduces liquid biofuel yield by at least 21 GJ Mg(-1) C (biofuel energy sacrificed per unit mass of biochar C), with methanol synthesis giving this lowest energy penalty. For gaseous-biofuel production, the minimum energy penalty for biochar production is 33 GJ Mg(-1) C. These substitution rates correspond to a wide range of Pareto-optimal system configurations, implying considerable latitude to choose pyrolysis conditions to optimize for desired biochar properties or to modulate energy versus biochar yields in response to fluctuating price differentials for the two commodities.

Systematics of Fission-Product Yields

International Nuclear Information System (INIS)

Wahl, A.C.

2002-01-01

Empirical equations representing systematics of fission-product yields have been derived from experimental data. The systematics give some insight into nuclear-structure effects on yields, and the equations allow estimation of yields from fission of any nuclide with atomic number Z F = 90 thru 98, mass number A F = 230 thru 252, and precursor excitation energy (projectile kinetic plus binding energies) PE = 0 thru ∼200 MeV--the ranges of these quantities for the fissioning nuclei investigated. Calculations can be made with the computer program CYFP. Estimates of uncertainties in the yield estimates are given by equations, also in CYFP, and range from ∼ 15% for the highest yield values to several orders of magnitude for very small yield values. A summation method is used to calculate weighted average parameter values for fast-neutron (∼ fission spectrum) induced fission reactions

Systematics of Fission-Product Yields

Energy Technology Data Exchange (ETDEWEB)

A.C. Wahl

2002-05-01

Empirical equations representing systematics of fission-product yields have been derived from experimental data. The systematics give some insight into nuclear-structure effects on yields, and the equations allow estimation of yields from fission of any nuclide with atomic number Z{sub F} = 90 thru 98, mass number A{sub F} = 230 thru 252, and precursor excitation energy (projectile kinetic plus binding energies) PE = 0 thru {approx}200 MeV--the ranges of these quantities for the fissioning nuclei investigated. Calculations can be made with the computer program CYFP. Estimates of uncertainties in the yield estimates are given by equations, also in CYFP, and range from {approx} 15% for the highest yield values to several orders of magnitude for very small yield values. A summation method is used to calculate weighted average parameter values for fast-neutron ({approx} fission spectrum) induced fission reactions.

Locational variation in green fodder yield, dry matter yield, and forage quality of sorghum

International Nuclear Information System (INIS)

Hussain, A.; Khan, S.; Mohammad, D.

2007-01-01

The present study was designed to find out the variations in for- age yield and quality of sorghum as affected by different environments. The three agroecological zones viz., Agricultural Research Institute (ARI), Sariab, Quetta, Ayub Agricultural Research Institute (AARI), Faisalabad and National Agricultural Research Centre (NARC), Islamabad were selected on the basis of different physiography, geology, temperature, and climate and water availability. Crude protein contents, varied from 6.98 to 8.02 percent, crude fibre contents from 30.84 to 31.68 percent, green fodder yield from 38.91 to 50.64 t/ha and dry matter yield from 8.92 to 10.17 t/ha at the three diverse locations. Maximum crude protein and crude fibre contents were obtained at NARC, Islamabad and AARI, Faisalabad. Maximum green fodder and dry matter yields were also observed at NARC, Islamabad and AARI, Faisalabad. It was also noted that the same genotypes showed differential response when planted under the diverse environments for green fodder yield, dry matter yield, crude protein and crude fibre contents. Therefore, it was concluded that these differences in forage yield and quality traits under diverse environments were due to differences in soil types, soil fertility, temperature, rain- fall and other climatic conditions. (author)

Quantitative Genetic Analysis for Yield and Yield Components in Boro Rice (Oryza sativa L.

Directory of Open Access Journals (Sweden)

Supriyo CHAKRABORTY

2010-03-01

Full Text Available Twenty-nine genotypes of boro rice (Oryza sativa L. were grown in a randomized block design with three replications in plots of 4m x 1m with a crop geometry of 20 cm x 20 cm between November-April, in Regional Agricultural Research Station, Nagaon, India. Quantitative data were collected on five randomly selected plants of each genotype per replication for yield/plant, and six other yield components, namely plant height, panicles/plant, panicle length, effective grains/panicle, 100 grain weight and harvest index. Mean values of the characters for each genotype were used for analysis of variance and covariance to obtain information on genotypic and phenotypic correlation along with coheritability between two characters. Path analyses were carried out to estimate the direct and indirect effects of boro rice�s yield components. The objective of the study was to identify the characters that mostly influence the yield for increasing boro rice productivity through breeding program. Correlation analysis revealed significant positive genotypic correlation of yield/plant with plant height (0.21, panicles/plant (0.53, panicle length (0.53, effective grains/panicle (0.57 and harvest index (0.86. Path analysis based on genotypic correlation coefficients elucidated high positive direct effect of harvest index (0.8631, panicle length (0.2560 and 100 grain weight (0.1632 on yield/plant with a residual effect of 0.33. Plant height and panicles/plant recorded high positive indirect effect on yield/plant via harvest index whereas effective grains/panicle on yield/plant via harvest index and panicle length. Results of the present study suggested that five component characters, namely harvest index, effective grains/plant, panicle length, panicles/plant and plant height influenced the yield of boro rice. A genotype with higher magnitude of these component characters could be either selected from the existing genotypes or evolved by breeding program for genetic

Effect of fertilizer application on yield of oil palm

Directory of Open Access Journals (Sweden)

Eksomtramage, T.

2001-11-01

Full Text Available The effects of fertilizer application rates on leaf nutrient contents and yield of oil palm were investigated at the Agricultural and Technological College Plantation in Trang province during May 1998 - June 2001. A five-year-old oil palm plantation, planted on the Na Tham soil series (Fine loamy, mixed, isohyperthermic Oxic Plinthudults with spacing 9x9x9 m, was selected for study. A randomized complete block designwith three replications with 20 palms/replication was used. The treatments included six different rates of fertilizer application. The rates of fertilizer were as follows: T1 (farmer practice, T2 (40% of application rate in T4, T3 (70% of application rate in T4, T4 (urea 2,750 g/plant; triple super phosphate 1,500 g/plant; potassium chloride 4,000 g/plant; kieserite 1,000 g/plant; borate 80 g/plant, T5 (130% of application rate in T4 and T6 (170% of application rate in T4. The high leaf nutrient contents of N, P and K at the range of 2.6-2.8%, 0.16-0.18% and 1.13-1.18%, respectively, were found in the high nutrient application rate treatments (T5, T6. However, the amounts of leaf Ca and Mg in T5 and T6 decreased from 0.75-0.80% and 0.33- 0.37% at the beginning of experiment to 0.65-0.70% and 0.22-0.24%, respectively, at the end of the experiment. Small increases of leaf sulphur and boron up to about 0.20-0.22% and 16-19 mg/kg were also found in the high rate of fertilizer treatments. Accumulated fresh fruit bunch yield (FFB increased according to increasing rate of fertilizer application. Accumulated FFB yield of 268.4 kg/plant in the low fertilizer rate (T1 (farmer practice and 278.8 kg/plant in T2 were found compared with the highest yield of 370.2 kg/plant in the highest fertilizer application treatment (T6 for the 3 years experiment. Regarding the economic return, the medium rate of fertilizer application (T3 which achieved an accumulated FFB yield of 338.0 kg/ plant gave the highest profit with the VCR (Value: Cost ratio of 2.53.

An Accurate Full-flexion Anterolateral Portal for Needle Placement in the Knee Joint With Dry Osteoarthritis.

Science.gov (United States)

Hussein, Mohamed

2017-07-01

Accurate delivery of an injection into the intra-articular space of the knee is achieved in only two thirds of knees when using the standard anterolateral portal. The use of a modified full-flexion anterolateral portal provides a highly accurate, less painful, and more effective method for reproducible intra-articular injection without the need for ultrasonographic or fluoroscopic guidance in patients with dry osteoarthritis of the knee. The accuracy of needle placement was assessed in a prospective series of 140 consecutive injections in patients with symptomatic degenerative knee arthritis without clinical knee effusion. Procedural pain was determined using the Numerical Rating Scale. The accuracy rates of needle placement were confirmed with fluoroscopic imaging to document the dispersion pattern of injected contrast material. Using the standard anterolateral portal, 52 of 70 injections were confirmed to have been placed in the intra-articular space on the first attempt (accuracy rate, 74.2%). Using the modified full-flexion anterolateral portal, 68 of 70 injections were placed in the intra-articular space on the first attempt (accuracy rate, 97.1%; P = 0.000). This study revealed that using the modified full-flexion anterolateral portal for injections into the knee joint resulted in more accurate and less painful injections than those performed by the same orthopaedic surgeon using the standard anterolateral portal. In addition, the technique offered therapeutic delivery into the joint without the need for fluoroscopic confirmation. Therapeutic Level II.

Characterization of echoes: A Dyson-series representation of individual pulses

Science.gov (United States)

Correia, Miguel R.; Cardoso, Vitor

2018-04-01

The ability to detect and scrutinize gravitational waves from the merger and coalescence of compact binaries opens up the possibility to perform tests of fundamental physics. One such test concerns the dark nature of compact objects: are they really black holes? It was recently pointed out that the absence of horizons—while keeping the external geometry very close to that of General Relativity—would manifest itself in a series of echoes in gravitational wave signals. The observation of echoes by LIGO/Virgo or upcoming facilities would likely inform us on quantum gravity effects or unseen types of matter. Detection of such signals is in principle feasible with relatively simple tools but would benefit enormously from accurate templates. Here we analytically individualize each echo waveform and show that it can be written as a Dyson series, for arbitrary effective potential and boundary conditions. We further apply the formalism to explicitly determine the echoes of a simple toy model: the Dirac delta potential. Our results allow to read off a few known features of echoes and may find application in the modeling for data analysis.

Using time series structural characteristics to analyze grain prices in food insecure countries

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Davenport, Frank; Funk, Chris

2015-01-01

Two components of food security monitoring are accurate forecasts of local grain prices and the ability to identify unusual price behavior. We evaluated a method that can both facilitate forecasts of cross-country grain price data and identify dissimilarities in price behavior across multiple markets. This method, characteristic based clustering (CBC), identifies similarities in multiple time series based on structural characteristics in the data. Here, we conducted a simulation experiment to determine if CBC can be used to improve the accuracy of maize price forecasts. We then compared forecast accuracies among clustered and non-clustered price series over a rolling time horizon. We found that the accuracy of forecasts on clusters of time series were equal to or worse than forecasts based on individual time series. However, in the following experiment we found that CBC was still useful for price analysis. We used the clusters to explore the similarity of price behavior among Kenyan maize markets. We found that price behavior in the isolated markets of Mandera and Marsabit has become increasingly dissimilar from markets in other Kenyan cities, and that these dissimilarities could not be explained solely by geographic distance. The structural isolation of Mandera and Marsabit that we find in this paper is supported by field studies on food security and market integration in Kenya. Our results suggest that a market with a unique price series (as measured by structural characteristics that differ from neighboring markets) may lack market integration and food security.

Chlorophyll fluorescence imaging accurately quantifies freezing damage and cold acclimation responses in Arabidopsis leaves

Directory of Open Access Journals (Sweden)

Hincha Dirk K

2008-05-01

Full Text Available Abstract Background Freezing tolerance is an important factor in the geographical distribution of plants and strongly influences crop yield. Many plants increase their freezing tolerance during exposure to low, nonfreezing temperatures in a process termed cold acclimation. There is considerable natural variation in the cold acclimation capacity of Arabidopsis that has been used to study the molecular basis of this trait. Accurate methods for the quantitation of freezing damage in leaves that include spatial information about the distribution of damage and the possibility to screen large populations of plants are necessary, but currently not available. In addition, currently used standard methods such as electrolyte leakage assays are very laborious and therefore not easily applicable for large-scale screening purposes. Results We have performed freezing experiments with the Arabidopsis accessions C24 and Tenela, which differ strongly in their freezing tolerance, both before and after cold acclimation. Freezing tolerance of detached leaves was investigated using the well established electrolyte leakage assay as a reference. Chlorophyll fluorescence imaging was used as an alternative method that provides spatial resolution of freezing damage over the leaf area. With both methods, LT50 values (i.e. temperature where 50% damage occurred could be derived as quantitative measures of leaf freezing tolerance. Both methods revealed the expected differences between acclimated and nonacclimated plants and between the two accessions and LT50 values were tightly correlated. However, electrolyte leakage assays consistently yielded higher LT50 values than chlorophyll fluorescence imaging. This was to a large part due to the incubation of leaves for electrolyte leakage measurements in distilled water, which apparently led to secondary damage, while this pre-incubation was not necessary for the chlorophyll fluorescence measurements. Conclusion Chlorophyll

Accurate episomal HIV 2-LTR circles quantification using optimized DNA isolation and droplet digital PCR.

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Malatinkova, Eva; Kiselinova, Maja; Bonczkowski, Pawel; Trypsteen, Wim; Messiaen, Peter; Vermeire, Jolien; Verhasselt, Bruno; Vervisch, Karen; Vandekerckhove, Linos; De Spiegelaere, Ward

2014-01-01

In HIV-infected patients on combination antiretroviral therapy (cART), the detection of episomal HIV 2-LTR circles is a potential marker for ongoing viral replication. Quantification of 2-LTR circles is based on quantitative PCR or more recently on digital PCR assessment, but is hampered due to its low abundance. Sample pre-PCR processing is a critical step for 2-LTR circles quantification, which has not yet been sufficiently evaluated in patient derived samples. We compared two sample processing procedures to more accurately quantify 2-LTR circles using droplet digital PCR (ddPCR). Episomal HIV 2-LTR circles were either isolated by genomic DNA isolation or by a modified plasmid DNA isolation, to separate the small episomal circular DNA from chromosomal DNA. This was performed in a dilution series of HIV-infected cells and HIV-1 infected patient derived samples (n=59). Samples for the plasmid DNA isolation method were spiked with an internal control plasmid. Genomic DNA isolation enables robust 2-LTR circles quantification. However, in the lower ranges of detection, PCR inhibition caused by high genomic DNA load substantially limits the amount of sample input and this impacts sensitivity and accuracy. Moreover, total genomic DNA isolation resulted in a lower recovery of 2-LTR templates per isolate, further reducing its sensitivity. The modified plasmid DNA isolation with a spiked reference for normalization was more accurate in these low ranges compared to genomic DNA isolation. A linear correlation of both methods was observed in the dilution series (R2=0.974) and in the patient derived samples with 2-LTR numbers above 10 copies per million peripheral blood mononuclear cells (PBMCs), (R2=0.671). Furthermore, Bland-Altman analysis revealed an average agreement between the methods within the 27 samples in which 2-LTR circles were detectable with both methods (bias: 0.3875±1.2657 log10). 2-LTR circles quantification in HIV-infected patients proved to be more