Identification of Microorganisms by High Resolution Tandem Mass Spectrometry with Accurate Statistical Significance

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Suffredini, Anthony F.; Sacks, David B.; Yu, Yi-Kuo

2016-02-01

Correct and rapid identification of microorganisms is the key to the success of many important applications in health and safety, including, but not limited to, infection treatment, food safety, and biodefense. With the advance of mass spectrometry (MS) technology, the speed of identification can be greatly improved. However, the increasing number of microbes sequenced is challenging correct microbial identification because of the large number of choices present. To properly disentangle candidate 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 peptidome profiles of microbes to better separate them and by designing an analysis method that yields accurate statistical significance. Here, we present an analysis pipeline that uses tandem MS (MS/MS) spectra for microbial identification or classification. We have demonstrated, using MS/MS data of 81 samples, each composed of a single known microorganism, that the proposed pipeline can correctly identify microorganisms at least at the genus and species levels. We have also shown that the proposed pipeline computes accurate statistical significances, i.e., E-values for identified peptides and unified E-values for identified microorganisms. The proposed analysis pipeline has been implemented in MiCId, a freely available software for Microorganism Classification and Identification. MiCId is available for download at http://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads.html.

Health significance and statistical uncertainty. The value of P-value.

PubMed

Consonni, Dario; Bertazzi, Pier Alberto

2017-10-27

The P-value is widely used as a summary statistics of scientific results. Unfortunately, there is a widespread tendency to dichotomize its value in "P<0.05" (defined as "statistically significant") and "P>0.05" ("statistically not significant"), with the former implying a "positive" result and the latter a "negative" one. To show the unsuitability of such an approach when evaluating the effects of environmental and occupational risk factors. We provide examples of distorted use of P-value and of the negative consequences for science and public health of such a black-and-white vision. The rigid interpretation of P-value as a dichotomy favors the confusion between health relevance and statistical significance, discourages thoughtful thinking, and distorts attention from what really matters, the health significance. A much better way to express and communicate scientific results involves reporting effect estimates (e.g., risks, risks ratios or risk differences) and their confidence intervals (CI), which summarize and convey both health significance and statistical uncertainty. Unfortunately, many researchers do not usually consider the whole interval of CI but only examine if it includes the null-value, therefore degrading this procedure to the same P-value dichotomy (statistical significance or not). In reporting statistical results of scientific research present effects estimates with their confidence intervals and do not qualify the P-value as "significant" or "not significant".

The questioned p value: clinical, practical and statistical significance.

PubMed

Jiménez-Paneque, Rosa

2016-09-09

The use of p-value and statistical significance have been questioned since the early 80s in the last century until today. Much has been discussed about it in the field of statistics and its applications, especially in Epidemiology and Public Health. As a matter of fact, the p-value and its equivalent, statistical significance, are difficult concepts to grasp for the many health professionals some way involved in research applied to their work areas. However, its meaning should be clear in intuitive terms although it is based on theoretical concepts of the field of Statistics. This paper attempts to present the p-value as a concept that applies to everyday life and therefore intuitively simple but whose proper use cannot be separated from theoretical and methodological elements of inherent complexity. The reasons behind the criticism received by the p-value and its isolated use are intuitively explained, mainly the need to demarcate statistical significance from clinical significance and some of the recommended remedies for these problems are approached as well. It finally refers to the current trend to vindicate the p-value appealing to the convenience of its use in certain situations and the recent statement of the American Statistical Association in this regard.

Implementing and testing theoretical fission fragment yields in a Hauser-Feshbach statistical decay framework

NASA Astrophysics Data System (ADS)

Jaffke, Patrick; Möller, Peter; Stetcu, Ionel; Talou, Patrick; Schmitt, Christelle

2018-03-01

We implement fission fragment yields, calculated using Brownian shape-motion on a macroscopic-microscopic potential energy surface in six dimensions, into the Hauser-Feshbach statistical decay code CGMF. This combination allows us to test the impact of utilizing theoretically-calculated fission fragment yields on the subsequent prompt neutron and γ-ray emission. We draw connections between the fragment yields and the total kinetic energy TKE of the fission fragments and demonstrate that the use of calculated yields can introduce a difference in the 〈TKE〉 and, thus, the prompt neutron multiplicity v, as compared with experimental fragment yields. We deduce the uncertainty on the 〈TKE〉 and v from this procedure and identify possible applications.

Tests of Statistical Significance Made Sound

ERIC Educational Resources Information Center

Haig, Brian D.

2017-01-01

This article considers the nature and place of tests of statistical significance (ToSS) in science, with particular reference to psychology. Despite the enormous amount of attention given to this topic, psychology's understanding of ToSS remains deficient. The major problem stems from a widespread and uncritical acceptance of null hypothesis…

Statistically significant relational data mining :

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

Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann

This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publicationsmore » that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.« less

Statistical Evaluations of Variations in Dairy Cows’ Milk Yields as a Precursor of Earthquakes

PubMed Central

Yamauchi, Hiroyuki; Hayakawa, Masashi; Asano, Tomokazu; Ohtani, Nobuyo; Ohta, Mitsuaki

2017-01-01

Simple Summary There are many reports of abnormal changes occurring in various natural systems prior to earthquakes. Unusual animal behavior is one of these abnormalities; however, there are few objective indicators and to date, reliability has remained uncertain. We found that milk yields of dairy cows decreased prior to an earthquake in our previous case study. In this study, we examined the reliability of decreases in milk yields as a precursor for earthquakes using long-term observation data. In the results, milk yields decreased approximately three weeks before earthquakes. We have come to the conclusion that dairy cow milk yields have applicability as an objectively observable unusual animal behavior prior to earthquakes, and dairy cows respond to some physical or chemical precursors of earthquakes. Abstract Previous studies have provided quantitative data regarding unusual animal behavior prior to earthquakes; however, few studies include long-term, observational data. Our previous study revealed that the milk yields of dairy cows decreased prior to an extremely large earthquake. To clarify whether the milk yields decrease prior to earthquakes, we examined the relationship between earthquakes of various magnitudes and daily milk yields. The observation period was one year. In the results, cross-correlation analyses revealed a significant negative correlation between earthquake occurrence and milk yields approximately three weeks beforehand. Approximately a week and a half beforehand, a positive correlation was revealed, and the correlation gradually receded to zero as the day of the earthquake approached. Future studies that use data from a longer observation period are needed because this study only considered ten earthquakes and therefore does not have strong statistical power. Additionally, we compared the milk yields with the subionospheric very low frequency/low frequency (VLF/LF) propagation data indicating ionospheric perturbations. The results showed

Précis of statistical significance: rationale, validity, and utility.

PubMed

Chow, S L

1998-04-01

The null-hypothesis significance-test procedure (NHSTP) is defended in the context of the theory-corroboration experiment, as well as the following contrasts: (a) substantive hypotheses versus statistical hypotheses, (b) theory corroboration versus statistical hypothesis testing, (c) theoretical inference versus statistical decision, (d) experiments versus nonexperimental studies, and (e) theory corroboration versus treatment assessment. The null hypothesis can be true because it is the hypothesis that errors are randomly distributed in data. Moreover, the null hypothesis is never used as a categorical proposition. Statistical significance means only that chance influences can be excluded as an explanation of data; it does not identify the nonchance factor responsible. The experimental conclusion is drawn with the inductive principle underlying the experimental design. A chain of deductive arguments gives rise to the theoretical conclusion via the experimental conclusion. The anomalous relationship between statistical significance and the effect size often used to criticize NHSTP is more apparent than real. The absolute size of the effect is not an index of evidential support for the substantive hypothesis. Nor is the effect size, by itself, informative as to the practical importance of the research result. Being a conditional probability, statistical power cannot be the a priori probability of statistical significance. The validity of statistical power is debatable because statistical significance is determined with a single sampling distribution of the test statistic based on H0, whereas it takes two distributions to represent statistical power or effect size. Sample size should not be determined in the mechanical manner envisaged in power analysis. It is inappropriate to criticize NHSTP for nonstatistical reasons. At the same time, neither effect size, nor confidence interval estimate, nor posterior probability can be used to exclude chance as an explanation of

The Use of Meta-Analytic Statistical Significance Testing

ERIC Educational Resources Information Center

Polanin, Joshua R.; Pigott, Terri D.

2015-01-01

Meta-analysis multiplicity, the concept of conducting multiple tests of statistical significance within one review, is an underdeveloped literature. We address this issue by considering how Type I errors can impact meta-analytic results, suggest how statistical power may be affected through the use of multiplicity corrections, and propose how…

Analysis of a large dataset of mycorrhiza inoculation field trials on potato shows highly significant increases in yield.

PubMed

Hijri, Mohamed

2016-04-01

An increasing human population requires more food production in nutrient-efficient systems in order to simultaneously meet global food needs while reducing the environmental footprint of agriculture. Arbuscular mycorrhizal fungi (AMF) have the potential to enhance crop yield, but their efficiency has yet to be demonstrated in large-scale crop production systems. This study reports an analysis of a dataset consisting of 231 field trials in which the same AMF inoculant (Rhizophagus irregularis DAOM 197198) was applied to potato over a 4-year period in North America and Europe under authentic field conditions. The inoculation was performed using a liquid suspension of AMF spores that was sprayed onto potato seed pieces, yielding a calculated 71 spores per seed piece. Statistical analysis showed a highly significant increase in marketable potato yield (ANOVA, P < 0.0001) for inoculated fields (42.2 tons/ha) compared with non-inoculated controls (38.3 tons/ha), irrespective of trial year. The average yield increase was 3.9 tons/ha, representing 9.5 % of total crop yield. Inoculation was profitable with a 0.67-tons/ha increase in yield, a threshold reached in almost 79 % of all trials. This finding clearly demonstrates the benefits of mycorrhizal-based inoculation on crop yield, using potato as a case study. Further improvements of these beneficial inoculants will help compensate for crop production deficits, both now and in the future.

Common pitfalls in statistical analysis: “P” values, statistical significance and confidence intervals

PubMed Central

Ranganathan, Priya; Pramesh, C. S.; Buyse, Marc

2015-01-01

In the second part of a series on pitfalls in statistical analysis, we look at various ways in which a statistically significant study result can be expressed. We debunk some of the myths regarding the ‘P’ value, explain the importance of ‘confidence intervals’ and clarify the importance of including both values in a paper PMID:25878958

Multivariate Statistical Analysis of Cigarette Design Feature Influence on ISO TNCO Yields.

PubMed

Agnew-Heard, Kimberly A; Lancaster, Vicki A; Bravo, Roberto; Watson, Clifford; Walters, Matthew J; Holman, Matthew R

2016-06-20

The aim of this study is to explore how differences in cigarette physical design parameters influence tar, nicotine, and carbon monoxide (TNCO) yields in mainstream smoke (MSS) using the International Organization of Standardization (ISO) smoking regimen. Standardized smoking methods were used to evaluate 50 U.S. domestic brand cigarettes and a reference cigarette representing a range of TNCO yields in MSS collected from linear smoking machines using a nonintense smoking regimen. Multivariate statistical methods were used to form clusters of cigarettes based on their ISO TNCO yields and then to explore the relationship between the ISO generated TNCO yields and the nine cigarette physical design parameters between and within each cluster simultaneously. The ISO generated TNCO yields in MSS are 1.1-17.0 mg tar/cigarette, 0.1-2.2 mg nicotine/cigarette, and 1.6-17.3 mg CO/cigarette. Cluster analysis divided the 51 cigarettes into five discrete clusters based on their ISO TNCO yields. No one physical parameter dominated across all clusters. Predicting ISO machine generated TNCO yields based on these nine physical design parameters is complex due to the correlation among and between the nine physical design parameters and TNCO yields. From these analyses, it is estimated that approximately 20% of the variability in the ISO generated TNCO yields comes from other parameters (e.g., filter material, filter type, inclusion of expanded or reconstituted tobacco, and tobacco blend composition, along with differences in tobacco leaf origin and stalk positions and added ingredients). A future article will examine the influence of these physical design parameters on TNCO yields under a Canadian Intense (CI) smoking regimen. Together, these papers will provide a more robust picture of the design features that contribute to TNCO exposure across the range of real world smoking patterns.

Finding Statistically Significant Communities in Networks

PubMed Central

Lancichinetti, Andrea; Radicchi, Filippo; Ramasco, José J.; Fortunato, Santo

2011-01-01

Community structure is one of the main structural features of networks, revealing both their internal organization and the similarity of their elementary units. Despite the large variety of methods proposed to detect communities in graphs, there is a big need for multi-purpose techniques, able to handle different types of datasets and the subtleties of community structure. In this paper we present OSLOM (Order Statistics Local Optimization Method), the first method capable to detect clusters in networks accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics. It is based on the local optimization of a fitness function expressing the statistical significance of clusters with respect to random fluctuations, which is estimated with tools of Extreme and Order Statistics. OSLOM can be used alone or as a refinement procedure of partitions/covers delivered by other techniques. We have also implemented sequential algorithms combining OSLOM with other fast techniques, so that the community structure of very large networks can be uncovered. Our method has a comparable performance as the best existing algorithms on artificial benchmark graphs. Several applications on real networks are shown as well. OSLOM is implemented in a freely available software (http://www.oslom.org), and we believe it will be a valuable tool in the analysis of networks. PMID:21559480

Statistical analysis of corn yields responding to climate variability at various spatio-temporal resolutions

NASA Astrophysics Data System (ADS)

Jiang, H.; Lin, T.

2017-12-01

Rain-fed corn production systems are subject to sub-seasonal variations of precipitation and temperature during the growing season. As each growth phase has varied inherent physiological process, plants necessitate different optimal environmental conditions during each phase. However, this temporal heterogeneity towards climate variability alongside the lifecycle of crops is often simplified and fixed as constant responses in large scale statistical modeling analysis. To capture the time-variant growing requirements in large scale statistical analysis, we develop and compare statistical models at various spatial and temporal resolutions to quantify the relationship between corn yield and weather factors for 12 corn belt states from 1981 to 2016. The study compares three spatial resolutions (county, agricultural district, and state scale) and three temporal resolutions (crop growth phase, monthly, and growing season) to characterize the effects of spatial and temporal variability. Our results show that the agricultural district model together with growth phase resolution can explain 52% variations of corn yield caused by temperature and precipitation variability. It provides a practical model structure balancing the overfitting problem in county specific model and weak explanation power in state specific model. In US corn belt, precipitation has positive impact on corn yield in growing season except for vegetative stage while extreme heat attains highest sensitivity from silking to dough phase. The results show the northern counties in corn belt area are less interfered by extreme heat but are more vulnerable to water deficiency.

Statistical significance of combinatorial regulations

PubMed Central

Terada, Aika; Okada-Hatakeyama, Mariko; Tsuda, Koji; Sese, Jun

2013-01-01

More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the “limitless arity multiple-testing procedure” (LAMP) to count the exact number of testable combinations and calibrate the Bonferroni factor to the smallest possible value. LAMP lists significant combinations without any limit, whereas the family-wise error rate is rigorously controlled under the threshold. In the human breast cancer transcriptome, LAMP discovered statistically significant combinations of as many as eight binding motifs. This method may contribute to uncover pathways regulated in a coordinated fashion and find hidden associations in heterogeneous data. PMID:23882073

Assigning statistical significance to proteotypic peptides via database searches

PubMed Central

Alves, Gelio; Ogurtsov, Aleksey Y.; Yu, Yi-Kuo

2011-01-01

Querying MS/MS spectra against a database containing only proteotypic peptides reduces data analysis time due to reduction of database size. Despite the speed advantage, this search strategy is challenged by issues of statistical significance and coverage. The former requires separating systematically significant identifications from less confident identifications, while the latter arises when the underlying peptide is not present, due to single amino acid polymorphisms (SAPs) or post-translational modifications (PTMs), in the proteotypic peptide libraries searched. To address both issues simultaneously, we have extended RAId’s knowledge database to include proteotypic information, utilized RAId’s statistical strategy to assign statistical significance to proteotypic peptides, and modified RAId’s programs to allow for consideration of proteotypic information during database searches. The extended database alleviates the coverage problem since all annotated modifications, even those occurred within proteotypic peptides, may be considered. Taking into account the likelihoods of observation, the statistical strategy of RAId provides accurate E-value assignments regardless whether a candidate peptide is proteotypic or not. The advantage of including proteotypic information is evidenced by its superior retrieval performance when compared to regular database searches. PMID:21055489

Determining the Statistical Significance of Relative Weights

ERIC Educational Resources Information Center

Tonidandel, Scott; LeBreton, James M.; Johnson, Jeff W.

2009-01-01

Relative weight analysis is a procedure for estimating the relative importance of correlated predictors in a regression equation. Because the sampling distribution of relative weights is unknown, researchers using relative weight analysis are unable to make judgments regarding the statistical significance of the relative weights. J. W. Johnson…

How many spectral lines are statistically significant?

NASA Astrophysics Data System (ADS)

Freund, J.

When experimental line spectra are fitted with least squares techniques one frequently does not know whether n or n + 1 lines may be fitted safely. This paper shows how an F-test can be applied in order to determine the statistical significance of including an extra line into the fitting routine.

Advances in Testing the Statistical Significance of Mediation Effects

ERIC Educational Resources Information Center

Mallinckrodt, Brent; Abraham, W. Todd; Wei, Meifen; Russell, Daniel W.

2006-01-01

P. A. Frazier, A. P. Tix, and K. E. Barron (2004) highlighted a normal theory method popularized by R. M. Baron and D. A. Kenny (1986) for testing the statistical significance of indirect effects (i.e., mediator variables) in multiple regression contexts. However, simulation studies suggest that this method lacks statistical power relative to some…

Using a time-series statistical framework to quantify trends and abrupt change in US corn, soybean, and wheat yields from 1970-2016

NASA Astrophysics Data System (ADS)

Zhang, J.; Ives, A. R.; Turner, M. G.; Kucharik, C. J.

2017-12-01

Previous studies have identified global agricultural regions where "stagnation" of long-term crop yield increases has occurred. These studies have used a variety of simple statistical methods that often ignore important aspects of time series regression modeling. These methods can lead to differing and contradictory results, which creates uncertainty regarding food security given rapid global population growth. Here, we present a new statistical framework incorporating time series-based algorithms into standard regression models to quantify spatiotemporal yield trends of US maize, soybean, and winter wheat from 1970-2016. Our primary goal was to quantify spatial differences in yield trends for these three crops using USDA county level data. This information was used to identify regions experiencing the largest changes in the rate of yield increases over time, and to determine whether abrupt shifts in the rate of yield increases have occurred. Although crop yields continue to increase in most maize-, soybean-, and winter wheat-growing areas, yield increases have stagnated in some key agricultural regions during the most recent 15 to 16 years: some maize-growing areas, except for the northern Great Plains, have shown a significant trend towards smaller annual yield increases for maize; soybean has maintained an consistent long-term yield gains in the Northern Great Plains, the Midwest, and southeast US, but has experienced a shift to smaller annual increases in other regions; winter wheat maintained a moderate annual increase in eastern South Dakota and eastern US locations, but showed a decline in the magnitude of annual increases across the central Great Plains and western US regions. Our results suggest that there were abrupt shifts in the rate of annual yield increases in a variety of US regions among the three crops. The framework presented here can be broadly applied to additional yield trend analyses for different crops and regions of the Earth.

Assessment of statistical significance and clinical relevance.

PubMed

Kieser, Meinhard; Friede, Tim; Gondan, Matthias

2013-05-10

In drug development, it is well accepted that a successful study will demonstrate not only a statistically significant result but also a clinically relevant effect size. Whereas standard hypothesis tests are used to demonstrate the former, it is less clear how the latter should be established. In the first part of this paper, we consider the responder analysis approach and study the performance of locally optimal rank tests when the outcome distribution is a mixture of responder and non-responder distributions. We find that these tests are quite sensitive to their planning assumptions and have therefore not really any advantage over standard tests such as the t-test and the Wilcoxon-Mann-Whitney test, which perform overall well and can be recommended for applications. In the second part, we present a new approach to the assessment of clinical relevance based on the so-called relative effect (or probabilistic index) and derive appropriate sample size formulae for the design of studies aiming at demonstrating both a statistically significant and clinically relevant effect. Referring to recent studies in multiple sclerosis, we discuss potential issues in the application of this approach. Copyright © 2012 John Wiley & Sons, Ltd.

Increasing the statistical significance of entanglement detection in experiments.

PubMed

Jungnitsch, Bastian; Niekamp, Sönke; Kleinmann, Matthias; Gühne, Otfried; Lu, He; Gao, Wei-Bo; Chen, Yu-Ao; Chen, Zeng-Bing; Pan, Jian-Wei

2010-05-28

Entanglement is often verified by a violation of an inequality like a Bell inequality or an entanglement witness. Considerable effort has been devoted to the optimization of such inequalities in order to obtain a high violation. We demonstrate theoretically and experimentally that such an optimization does not necessarily lead to a better entanglement test, if the statistical error is taken into account. Theoretically, we show for different error models that reducing the violation of an inequality can improve the significance. Experimentally, we observe this phenomenon in a four-photon experiment, testing the Mermin and Ardehali inequality for different levels of noise. Furthermore, we provide a way to develop entanglement tests with high statistical significance.

Statistical Relations for Yield Degradation in Inertial Confinement Fusion

NASA Astrophysics Data System (ADS)

Woo, K. M.; Betti, R.; Patel, D.; Gopalaswamy, V.

2017-10-01

In inertial confinement fusion (ICF), the yield-over-clean (YOC) is a quantity commonly used to assess the performance of an implosion with respect to the degradation caused by asymmetries. The YOC also determines the Lawson parameter used to identify the onset of ignition and the level of alpha heating in ICF implosions. In this work, we show that the YOC is a unique function of the residual kinetic energy in the compressed shell (with respect to the 1-D case) regardless of the asymmetry spectrum. This result is derived using a simple model of the deceleration phase as well as through an extensive set of 3-D radiation-hydrodynamics simulations using the code DEC3D. The latter has been recently upgraded to include a 3-D spherical moving mesh, the HYPRE solver for 3-D radiation transport and piecewise-parabolic method for robust shock-capturing hydrodynamic simulations. DEC3D is used to build a synthetic single-mode database to study the behavior of yield degradation caused by Rayleigh-Taylor instabilities in the deceleration phase. The relation between YOC and residual kinetic energy is compared with the result in an adiabatic implosion model. The statistical expression of YOC is also applied to the ignition criterion in the presence of multidimensional nonuniformities. This material is based upon work supported by the Department of Energy National Nuclear Security Administration under Award Number DE-NA0001944.

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Mathematical and statistical analysis of the effect of boron on yield parameters of wheat

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

Rawashdeh, Hamzeh; Sala, Florin; Boldea, Marius

The main objective of this research is to investigate the effect of foliar applications of boron at different growth stages on yield and yield parameters of wheat. The contribution of boron in achieving yield parameters is described by second degree polynomial equations, with high statistical confidence (p<0.01; F theoretical < F calculated, according to ANOVA test, for Alfa = 0.05). Regression analysis, based on R{sup 2} values obtained, made it possible to evaluate the particular contribution of boron to the realization of yield parameters. This was lower for spike length (R{sup 2} = 0.812), thousand seeds weight (R{sup 2} =more » 0.850) and higher in the case of the number of spikelets (R{sup 2} = 0.936) and the number of seeds on a spike (R{sup 2} = 0.960). These results confirm that boron plays an important part in achieving the number of seeds on a spike in the case of wheat, as the contribution of this element to the process of flower fertilization is well-known. In regards to productivity elements, the contribution of macroelements to yield quantity is clear, the contribution of B alone being R{sup 2} = 0.868.« less

Statistical physics of the yielding transition in amorphous solids.

PubMed

Karmakar, Smarajit; Lerner, Edan; Procaccia, Itamar

2010-11-01

The art of making structural, polymeric, and metallic glasses is rapidly developing with many applications. A limitation is that under increasing external strain all amorphous solids (like their crystalline counterparts) have a finite yield stress which cannot be exceeded without effecting a plastic response which typically leads to mechanical failure. Understanding this is crucial for assessing the risk of failure of glassy materials under mechanical loads. Here we show that the statistics of the energy barriers ΔE that need to be surmounted changes from a probability distribution function that goes smoothly to zero as ΔE=0 to a pdf which is finite at ΔE=0 . This fundamental change implies a dramatic transition in the mechanical stability properties with respect to external strain. We derive exact results for the scaling exponents that characterize the magnitudes of average energy and stress drops in plastic events as a function of system size.

Estimation of the geochemical threshold and its statistical significance

USGS Publications Warehouse

Miesch, A.T.

1981-01-01

A statistic is proposed for estimating the geochemical threshold and its statistical significance, or it may be used to identify a group of extreme values that can be tested for significance by other means. The statistic is the maximum gap between adjacent values in an ordered array after each gap has been adjusted for the expected frequency. The values in the ordered array are geochemical values transformed by either ln(?? - ??) or ln(?? - ??) and then standardized so that the mean is zero and the variance is unity. The expected frequency is taken from a fitted normal curve with unit area. The midpoint of an adjusted gap that exceeds the corresponding critical value may be taken as an estimate of the geochemical threshold, and the associated probability indicates the likelihood that the threshold separates two geochemical populations. The adjusted gap test may fail to identify threshold values if the variation tends to be continuous from background values to the higher values that reflect mineralized ground. However, the test will serve to identify other anomalies that may be too subtle to have been noted by other means. ?? 1981.

Decadal power in land air temperatures: Is it statistically significant?

NASA Astrophysics Data System (ADS)

Thejll, Peter A.

2001-12-01

The geographical distribution and properties of the well-known 10-11 year signal in terrestrial temperature records is investigated. By analyzing the Global Historical Climate Network data for surface air temperatures we verify that the signal is strongest in North America and is similar in nature to that reported earlier by R. G. Currie. The decadal signal is statistically significant for individual stations, but it is not possible to show that the signal is statistically significant globally, using strict tests. In North America, during the twentieth century, the decadal variability in the solar activity cycle is associated with the decadal part of the North Atlantic Oscillation index series in such a way that both of these signals correspond to the same spatial pattern of cooling and warming. A method for testing statistical results with Monte Carlo trials on data fields with specified temporal structure and specific spatial correlation retained is presented.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Alves, Gelio; Wang, Guanghui; Ogurtsov, Aleksey Y.; Drake, Steven K.; Gucek, Marjan; Sacks, David B.; Yu, Yi-Kuo

2018-06-01

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.

Rapid Classification and Identification of Multiple Microorganisms with Accurate Statistical Significance via High-Resolution Tandem Mass Spectrometry.

PubMed

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.

Climate-based statistical regression models for crop yield forecasting of coffee in humid tropical Kerala, India

NASA Astrophysics Data System (ADS)

Jayakumar, M.; Rajavel, M.; Surendran, U.

2016-12-01

A study on the variability of coffee yield of both Coffea arabica and Coffea canephora as influenced by climate parameters (rainfall (RF), maximum temperature (Tmax), minimum temperature (Tmin), and mean relative humidity (RH)) was undertaken at Regional Coffee Research Station, Chundale, Wayanad, Kerala State, India. The result on the coffee yield data of 30 years (1980 to 2009) revealed that the yield of coffee is fluctuating with the variations in climatic parameters. Among the species, productivity was higher for C. canephora coffee than C. arabica in most of the years. Maximum yield of C. canephora (2040 kg ha-1) was recorded in 2003-2004 and there was declining trend of yield noticed in the recent years. Similarly, the maximum yield of C. arabica (1745 kg ha-1) was recorded in 1988-1989 and decreased yield was noticed in the subsequent years till 1997-1998 due to year to year variability in climate. The highest correlation coefficient was found between the yield of C. arabica coffee and maximum temperature during January (0.7) and between C. arabica coffee yield and RH during July (0.4). Yield of C. canephora coffee had highest correlation with maximum temperature, RH and rainfall during February. Statistical regression model between selected climatic parameters and yield of C. arabica and C. canephora coffee was developed to forecast the yield of coffee in Wayanad district in Kerala. The model was validated for years 2010, 2011, and 2012 with the coffee yield data obtained during the years and the prediction was found to be good.

Statistical Significance for Hierarchical Clustering

PubMed Central

Kimes, Patrick K.; Liu, Yufeng; Hayes, D. Neil; Marron, J. S.

2017-01-01

Summary Cluster analysis has proved to be an invaluable tool for the exploratory and unsupervised analysis of high dimensional datasets. Among methods for clustering, hierarchical approaches have enjoyed substantial popularity in genomics and other fields for their ability to simultaneously uncover multiple layers of clustering structure. A critical and challenging question in cluster analysis is whether the identified clusters represent important underlying structure or are artifacts of natural sampling variation. Few approaches have been proposed for addressing this problem in the context of hierarchical clustering, for which the problem is further complicated by the natural tree structure of the partition, and the multiplicity of tests required to parse the layers of nested clusters. In this paper, we propose a Monte Carlo based approach for testing statistical significance in hierarchical clustering which addresses these issues. The approach is implemented as a sequential testing procedure guaranteeing control of the family-wise error rate. Theoretical justification is provided for our approach, and its power to detect true clustering structure is illustrated through several simulation studies and applications to two cancer gene expression datasets. PMID:28099990

Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

DTIC Science & Technology

2016-04-26

REPORT TYPE Final 3. DATES COVERED (From - To) 15 Oct 2014 to 14 Jan 2015 4. TITLE AND SUBTITLE Detecting statistically significant clusters of...extend the work of Perry et al. [6] by developing a statistical framework that supports the detection of triangle motif-based clusters in complex...priori, the need for triangle motif-based clustering . 2. Developed an algorithm for clustering undirected networks, where the triangle con guration was

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

PubMed

Kramer, Karen L; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Your Chi-Square Test Is Statistically Significant: Now What?

ERIC Educational Resources Information Center

Sharpe, Donald

2015-01-01

Applied researchers have employed chi-square tests for more than one hundred years. This paper addresses the question of how one should follow a statistically significant chi-square test result in order to determine the source of that result. Four approaches were evaluated: calculating residuals, comparing cells, ransacking, and partitioning. Data…

Statistical Significance Testing in Second Language Research: Basic Problems and Suggestions for Reform

ERIC Educational Resources Information Center

Norris, John M.

2015-01-01

Traditions of statistical significance testing in second language (L2) quantitative research are strongly entrenched in how researchers design studies, select analyses, and interpret results. However, statistical significance tests using "p" values are commonly misinterpreted by researchers, reviewers, readers, and others, leading to…

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance

PubMed Central

Kramer, Karen L.; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children’s growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children’s monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children’s growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children’s growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children’s growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance. PMID:26938742

Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies

PubMed Central

Goodpaster, Aaron M.; Kennedy, Michael A.

2015-01-01

Currently, no standard metrics are used to quantify cluster separation in PCA or PLS-DA scores plots for metabonomics studies or to determine if cluster separation is statistically significant. Lack of such measures makes it virtually impossible to compare independent or inter-laboratory studies and can lead to confusion in the metabonomics literature when authors putatively identify metabolites distinguishing classes of samples based on visual and qualitative inspection of scores plots that exhibit marginal separation. While previous papers have addressed quantification of cluster separation in PCA scores plots, none have advocated routine use of a quantitative measure of separation that is supported by a standard and rigorous assessment of whether or not the cluster separation is statistically significant. Here quantification and statistical significance of separation of group centroids in PCA and PLS-DA scores plots are considered. The Mahalanobis distance is used to quantify the distance between group centroids, and the two-sample Hotelling's T2 test is computed for the data, related to an F-statistic, and then an F-test is applied to determine if the cluster separation is statistically significant. We demonstrate the value of this approach using four datasets containing various degrees of separation, ranging from groups that had no apparent visual cluster separation to groups that had no visual cluster overlap. Widespread adoption of such concrete metrics to quantify and evaluate the statistical significance of PCA and PLS-DA cluster separation would help standardize reporting of metabonomics data. PMID:26246647

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2010-06-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 80's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The r-largest annual maxima method provides more reliable predictions of the extreme values especially for small return periods (<100 years). Finally, the study statistically proves the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

NASA Astrophysics Data System (ADS)

Liu, Y.; Xiao, J.

2017-12-01

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of vegetation greening particularly afforestation on the hydrologic cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China's land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation greening and browning on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield or weakened the increase in water yield; vegetation browning reduced ET and increased water yield or weakened the decrease in water yield. At the large river basin and national scales, the greening trends had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the greenness changes on ET and water yield varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrologic cycle are needed to account for the feedbacks to the climate.

Social significance of community structure: Statistical view

NASA Astrophysics Data System (ADS)

Li, Hui-Jia; Daniels, Jasmine J.

2015-01-01

Community structure analysis is a powerful tool for social networks that can simplify their topological and functional analysis considerably. However, since community detection methods have random factors and real social networks obtained from complex systems always contain error edges, evaluating the significance of a partitioned community structure is an urgent and important question. In this paper, integrating the specific characteristics of real society, we present a framework to analyze the significance of a social community. The dynamics of social interactions are modeled by identifying social leaders and corresponding hierarchical structures. Instead of a direct comparison with the average outcome of a random model, we compute the similarity of a given node with the leader by the number of common neighbors. To determine the membership vector, an efficient community detection algorithm is proposed based on the position of the nodes and their corresponding leaders. Then, using a log-likelihood score, the tightness of the community can be derived. Based on the distribution of community tightness, we establish a connection between p -value theory and network analysis, and then we obtain a significance measure of statistical form . Finally, the framework is applied to both benchmark networks and real social networks. Experimental results show that our work can be used in many fields, such as determining the optimal number of communities, analyzing the social significance of a given community, comparing the performance among various algorithms, etc.

Statistical significance versus clinical relevance.

PubMed

van Rijn, Marieke H C; Bech, Anneke; Bouyer, Jean; van den Brand, Jan A J G

2017-04-01

In March this year, the American Statistical Association (ASA) posted a statement on the correct use of P-values, in response to a growing concern that the P-value is commonly misused and misinterpreted. We aim to translate these warnings given by the ASA into a language more easily understood by clinicians and researchers without a deep background in statistics. Moreover, we intend to illustrate the limitations of P-values, even when used and interpreted correctly, and bring more attention to the clinical relevance of study findings using two recently reported studies as examples. We argue that P-values are often misinterpreted. A common mistake is saying that P < 0.05 means that the null hypothesis is false, and P ≥0.05 means that the null hypothesis is true. The correct interpretation of a P-value of 0.05 is that if the null hypothesis were indeed true, a similar or more extreme result would occur 5% of the times upon repeating the study in a similar sample. In other words, the P-value informs about the likelihood of the data given the null hypothesis and not the other way around. A possible alternative related to the P-value is the confidence interval (CI). It provides more information on the magnitude of an effect and the imprecision with which that effect was estimated. However, there is no magic bullet to replace P-values and stop erroneous interpretation of scientific results. Scientists and readers alike should make themselves familiar with the correct, nuanced interpretation of statistical tests, P-values and CIs. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

High precision and high yield fabrication of dense nanoparticle arrays onto DNA origami at statistically independent binding sites

NASA Astrophysics Data System (ADS)

Takabayashi, Sadao; Klein, William P.; Onodera, Craig; Rapp, Blake; Flores-Estrada, Juan; Lindau, Elias; Snowball, Lejmarc; Sam, Joseph T.; Padilla, Jennifer E.; Lee, Jeunghoon; Knowlton, William B.; Graugnard, Elton; Yurke, Bernard; Kuang, Wan; Hughes, William L.

2014-10-01

High precision, high yield, and high density self-assembly of nanoparticles into arrays is essential for nanophotonics. Spatial deviations as small as a few nanometers can alter the properties of near-field coupled optical nanostructures. Several studies have reported assemblies of few nanoparticle structures with controlled spacing using DNA nanostructures with variable yield. Here, we report multi-tether design strategies and attachment yields for homo- and hetero-nanoparticle arrays templated by DNA origami nanotubes. Nanoparticle attachment yield via DNA hybridization is comparable with streptavidin-biotin binding. Independent of the number of binding sites, >97% site-occupation was achieved with four tethers and 99.2% site-occupation is theoretically possible with five tethers. The interparticle distance was within 2 nm of all design specifications and the nanoparticle spatial deviations decreased with interparticle spacing. Modified geometric, binomial, and trinomial distributions indicate that site-bridging, steric hindrance, and electrostatic repulsion were not dominant barriers to self-assembly and both tethers and binding sites were statistically independent at high particle densities.High precision, high yield, and high density self-assembly of nanoparticles into arrays is essential for nanophotonics. Spatial deviations as small as a few nanometers can alter the properties of near-field coupled optical nanostructures. Several studies have reported assemblies of few nanoparticle structures with controlled spacing using DNA nanostructures with variable yield. Here, we report multi-tether design strategies and attachment yields for homo- and hetero-nanoparticle arrays templated by DNA origami nanotubes. Nanoparticle attachment yield via DNA hybridization is comparable with streptavidin-biotin binding. Independent of the number of binding sites, >97% site-occupation was achieved with four tethers and 99.2% site-occupation is theoretically possible with five

Statistical trend analysis and extreme distribution of significant wave height from 1958 to 1999 - an application to the Italian Seas

NASA Astrophysics Data System (ADS)

Martucci, G.; Carniel, S.; Chiggiato, J.; Sclavo, M.; Lionello, P.; Galati, M. B.

2009-09-01

The study is a statistical analysis of sea states timeseries derived using the wave model WAM forced by the ERA-40 dataset in selected areas near the Italian coasts. For the period 1 January 1958 to 31 December 1999 the analysis yields: (i) the existence of a negative trend in the annual- and winter-averaged sea state heights; (ii) the existence of a turning-point in late 70's in the annual-averaged trend of sea state heights at a site in the Northern Adriatic Sea; (iii) the overall absence of a significant trend in the annual-averaged mean durations of sea states over thresholds; (iv) the assessment of the extreme values on a time-scale of thousand years. The analysis uses two methods to obtain samples of extremes from the independent sea states: the r-largest annual maxima and the peak-over-threshold. The two methods show statistical differences in retrieving the return values and more generally in describing the significant wave field. The study shows the existence of decadal negative trends in the significant wave heights and by this it conveys useful information on the wave climatology of the Italian seas during the second half of the 20th century.

Statistical Significance and Effect Size: Two Sides of a Coin.

ERIC Educational Resources Information Center

Fan, Xitao

This paper suggests that statistical significance testing and effect size are two sides of the same coin; they complement each other, but do not substitute for one another. Good research practice requires that both should be taken into consideration to make sound quantitative decisions. A Monte Carlo simulation experiment was conducted, and a…

Publication of statistically significant research findings in prosthodontics & implant dentistry in the context of other dental specialties.

PubMed

Papageorgiou, Spyridon N; Kloukos, Dimitrios; Petridis, Haralampos; Pandis, Nikolaos

2015-10-01

To assess the hypothesis that there is excessive reporting of statistically significant studies published in prosthodontic and implantology journals, which could indicate selective publication. The last 30 issues of 9 journals in prosthodontics and implant dentistry were hand-searched for articles with statistical analyses. The percentages of significant and non-significant results were tabulated by parameter of interest. Univariable/multivariable logistic regression analyses were applied to identify possible predictors of reporting statistically significance findings. The results of this study were compared with similar studies in dentistry with random-effects meta-analyses. From the 2323 included studies 71% of them reported statistically significant results, with the significant results ranging from 47% to 86%. Multivariable modeling identified that geographical area and involvement of statistician were predictors of statistically significant results. Compared to interventional studies, the odds that in vitro and observational studies would report statistically significant results was increased by 1.20 times (OR: 2.20, 95% CI: 1.66-2.92) and 0.35 times (OR: 1.35, 95% CI: 1.05-1.73), respectively. The probability of statistically significant results from randomized controlled trials was significantly lower compared to various study designs (difference: 30%, 95% CI: 11-49%). Likewise the probability of statistically significant results in prosthodontics and implant dentistry was lower compared to other dental specialties, but this result did not reach statistical significant (P>0.05). The majority of studies identified in the fields of prosthodontics and implant dentistry presented statistically significant results. The same trend existed in publications of other specialties in dentistry. Copyright © 2015 Elsevier Ltd. All rights reserved.

Significant Statistics: Viewed with a Contextual Lens

ERIC Educational Resources Information Center

Tait-McCutcheon, Sandi

2010-01-01

This paper examines the pedagogical and organisational changes three lead teachers made to their statistics teaching and learning programs. The lead teachers posed the research question: What would the effect of contextually integrating statistical investigations and literacies into other curriculum areas be on student achievement? By finding the…

Soil mulching significantly enhances yields and water and nitrogen use efficiencies of maize and wheat: a meta-analysis

PubMed Central

Qin, Wei; Hu, Chunsheng; Oenema, Oene

2015-01-01

Global crop yields are limited by water and nutrient availability. Soil mulching (with plastic or straw) reduces evaporation, modifies soil temperature and thereby affects crop yields. Reported effects of mulching are sometimes contradictory, likely due to differences in climatic conditions, soil characteristics, crop species, and also water and nitrogen (N) input levels. Here we report on a meta-analysis of the effects of mulching on wheat and maize, using 1310 yield observations from 74 studies conducted in 19 countries. Our results indicate that mulching significantly increased yields, WUE (yield per unit water) and NUE (yield per unit N) by up to 60%, compared with no-mulching. Effects were larger for maize than wheat, and larger for plastic mulching than straw mulching. Interestingly, plastic mulching performed better at relatively low temperature while straw mulching showed the opposite trend. Effects of mulching also tended to decrease with increasing water input. Mulching effects were not related to soil organic matter content. In conclusion, soil mulching can significantly increase maize and wheat yields, WUE and NUE, and thereby may contribute to closing the yield gap between attainable and actual yields, especially in dryland and low nutrient input agriculture. The management of soil mulching requires site-specific knowledge. PMID:26586114

Soil mulching significantly enhances yields and water and nitrogen use efficiencies of maize and wheat: a meta-analysis.

PubMed

Qin, Wei; Hu, Chunsheng; Oenema, Oene

2015-11-20

Global crop yields are limited by water and nutrient availability. Soil mulching (with plastic or straw) reduces evaporation, modifies soil temperature and thereby affects crop yields. Reported effects of mulching are sometimes contradictory, likely due to differences in climatic conditions, soil characteristics, crop species, and also water and nitrogen (N) input levels. Here we report on a meta-analysis of the effects of mulching on wheat and maize, using 1310 yield observations from 74 studies conducted in 19 countries. Our results indicate that mulching significantly increased yields, WUE (yield per unit water) and NUE (yield per unit N) by up to 60%, compared with no-mulching. Effects were larger for maize than wheat, and larger for plastic mulching than straw mulching. Interestingly, plastic mulching performed better at relatively low temperature while straw mulching showed the opposite trend. Effects of mulching also tended to decrease with increasing water input. Mulching effects were not related to soil organic matter content. In conclusion, soil mulching can significantly increase maize and wheat yields, WUE and NUE, and thereby may contribute to closing the yield gap between attainable and actual yields, especially in dryland and low nutrient input agriculture. The management of soil mulching requires site-specific knowledge.

Soil mulching significantly enhances yields and water and nitrogen use efficiencies of maize and wheat: a meta-analysis

NASA Astrophysics Data System (ADS)

Qin, Wei; Hu, Chunsheng; Oenema, Oene

2015-11-01

Global crop yields are limited by water and nutrient availability. Soil mulching (with plastic or straw) reduces evaporation, modifies soil temperature and thereby affects crop yields. Reported effects of mulching are sometimes contradictory, likely due to differences in climatic conditions, soil characteristics, crop species, and also water and nitrogen (N) input levels. Here we report on a meta-analysis of the effects of mulching on wheat and maize, using 1310 yield observations from 74 studies conducted in 19 countries. Our results indicate that mulching significantly increased yields, WUE (yield per unit water) and NUE (yield per unit N) by up to 60%, compared with no-mulching. Effects were larger for maize than wheat, and larger for plastic mulching than straw mulching. Interestingly, plastic mulching performed better at relatively low temperature while straw mulching showed the opposite trend. Effects of mulching also tended to decrease with increasing water input. Mulching effects were not related to soil organic matter content. In conclusion, soil mulching can significantly increase maize and wheat yields, WUE and NUE, and thereby may contribute to closing the yield gap between attainable and actual yields, especially in dryland and low nutrient input agriculture. The management of soil mulching requires site-specific knowledge.

"What If" Analyses: Ways to Interpret Statistical Significance Test Results Using EXCEL or "R"

ERIC Educational Resources Information Center

Ozturk, Elif

2012-01-01

The present paper aims to review two motivations to conduct "what if" analyses using Excel and "R" to understand the statistical significance tests through the sample size context. "What if" analyses can be used to teach students what statistical significance tests really do and in applied research either prospectively to estimate what sample size…

Statistical significance of the rich-club phenomenon in complex networks

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2008-04-01

We propose that the rich-club phenomenon in complex networks should be defined in the spirit of bootstrapping, in which a null model is adopted to assess the statistical significance of the rich-club detected. Our method can serve as a definition of the rich-club phenomenon and is applied to analyze three real networks and three model networks. The results show significant improvement compared with previously reported results. We report a dilemma with an exceptional example, showing that there does not exist an omnipotent definition for the rich-club phenomenon.

Using the bootstrap to establish statistical significance for relative validity comparisons among patient-reported outcome measures

PubMed Central

2013-01-01

Background Relative validity (RV), a ratio of ANOVA F-statistics, is often used to compare the validity of patient-reported outcome (PRO) measures. We used the bootstrap to establish the statistical significance of the RV and to identify key factors affecting its significance. Methods Based on responses from 453 chronic kidney disease (CKD) patients to 16 CKD-specific and generic PRO measures, RVs were computed to determine how well each measure discriminated across clinically-defined groups of patients compared to the most discriminating (reference) measure. Statistical significance of RV was quantified by the 95% bootstrap confidence interval. Simulations examined the effects of sample size, denominator F-statistic, correlation between comparator and reference measures, and number of bootstrap replicates. Results The statistical significance of the RV increased as the magnitude of denominator F-statistic increased or as the correlation between comparator and reference measures increased. A denominator F-statistic of 57 conveyed sufficient power (80%) to detect an RV of 0.6 for two measures correlated at r = 0.7. Larger denominator F-statistics or higher correlations provided greater power. Larger sample size with a fixed denominator F-statistic or more bootstrap replicates (beyond 500) had minimal impact. Conclusions The bootstrap is valuable for establishing the statistical significance of RV estimates. A reasonably large denominator F-statistic (F > 57) is required for adequate power when using the RV to compare the validity of measures with small or moderate correlations (r < 0.7). Substantially greater power can be achieved when comparing measures of a very high correlation (r > 0.9). PMID:23721463

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

NASA Astrophysics Data System (ADS)

Liu, Yibo; Xiao, Jingfeng; Ju, Weimin; Xu, Ke; Zhou, Yanlian; Zhao, Yuntai

2016-09-01

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China’s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation ‘greening’ and ‘browning’ on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate.

Fostering Students' Statistical Literacy through Significant Learning Experience

ERIC Educational Resources Information Center

Krishnan, Saras

2015-01-01

A major objective of statistics education is to develop students' statistical literacy that enables them to be educated users of data in context. Teaching statistics in today's educational settings is not an easy feat because teachers have a huge task in keeping up with the demands of the new generation of learners. The present day students have…

Distinguishing between statistical significance and practical/clinical meaningfulness using statistical inference.

PubMed

Wilkinson, Michael

2014-03-01

Decisions about support for predictions of theories in light of data are made using statistical inference. The dominant approach in sport and exercise science is the Neyman-Pearson (N-P) significance-testing approach. When applied correctly it provides a reliable procedure for making dichotomous decisions for accepting or rejecting zero-effect null hypotheses with known and controlled long-run error rates. Type I and type II error rates must be specified in advance and the latter controlled by conducting an a priori sample size calculation. The N-P approach does not provide the probability of hypotheses or indicate the strength of support for hypotheses in light of data, yet many scientists believe it does. Outcomes of analyses allow conclusions only about the existence of non-zero effects, and provide no information about the likely size of true effects or their practical/clinical value. Bayesian inference can show how much support data provide for different hypotheses, and how personal convictions should be altered in light of data, but the approach is complicated by formulating probability distributions about prior subjective estimates of population effects. A pragmatic solution is magnitude-based inference, which allows scientists to estimate the true magnitude of population effects and how likely they are to exceed an effect magnitude of practical/clinical importance, thereby integrating elements of subjective Bayesian-style thinking. While this approach is gaining acceptance, progress might be hastened if scientists appreciate the shortcomings of traditional N-P null hypothesis significance testing.

Statistics Refresher for Molecular Imaging Technologists, Part 2: Accuracy of Interpretation, Significance, and Variance.

PubMed

Farrell, Mary Beth

2018-06-01

This article is the second part of a continuing education series reviewing basic statistics that nuclear medicine and molecular imaging technologists should understand. In this article, the statistics for evaluating interpretation accuracy, significance, and variance are discussed. Throughout the article, actual statistics are pulled from the published literature. We begin by explaining 2 methods for quantifying interpretive accuracy: interreader and intrareader reliability. Agreement among readers can be expressed simply as a percentage. However, the Cohen κ-statistic is a more robust measure of agreement that accounts for chance. The higher the κ-statistic is, the higher is the agreement between readers. When 3 or more readers are being compared, the Fleiss κ-statistic is used. Significance testing determines whether the difference between 2 conditions or interventions is meaningful. Statistical significance is usually expressed using a number called a probability ( P ) value. Calculation of P value is beyond the scope of this review. However, knowing how to interpret P values is important for understanding the scientific literature. Generally, a P value of less than 0.05 is considered significant and indicates that the results of the experiment are due to more than just chance. Variance, standard deviation (SD), confidence interval, and standard error (SE) explain the dispersion of data around a mean of a sample drawn from a population. SD is commonly reported in the literature. A small SD indicates that there is not much variation in the sample data. Many biologic measurements fall into what is referred to as a normal distribution taking the shape of a bell curve. In a normal distribution, 68% of the data will fall within 1 SD, 95% will fall within 2 SDs, and 99.7% will fall within 3 SDs. Confidence interval defines the range of possible values within which the population parameter is likely to lie and gives an idea of the precision of the statistic being

Economic impacts of climate change on agriculture: a comparison of process-based and statistical yield models

NASA Astrophysics Data System (ADS)

Moore, Frances C.; Baldos, Uris Lantz C.; Hertel, Thomas

2017-06-01

A large number of studies have been published examining the implications of climate change for agricultural productivity that, broadly speaking, can be divided into process-based modeling and statistical approaches. Despite a general perception that results from these methods differ substantially, there have been few direct comparisons. Here we use a data-base of yield impact studies compiled for the IPCC Fifth Assessment Report (Porter et al 2014) to systematically compare results from process-based and empirical studies. Controlling for differences in representation of CO2 fertilization between the two methods, we find little evidence for differences in the yield response to warming. The magnitude of CO2 fertilization is instead a much larger source of uncertainty. Based on this set of impact results, we find a very limited potential for on-farm adaptation to reduce yield impacts. We use the Global Trade Analysis Project (GTAP) global economic model to estimate welfare consequences of yield changes and find negligible welfare changes for warming of 1 °C-2 °C if CO2 fertilization is included and large negative effects on welfare without CO2. Uncertainty bounds on welfare changes are highly asymmetric, showing substantial probability of large declines in welfare for warming of 2 °C-3 °C even including the CO2 fertilization effect.

Using the Bootstrap Method for a Statistical Significance Test of Differences between Summary Histograms

NASA Technical Reports Server (NTRS)

Xu, Kuan-Man

2006-01-01

A new method is proposed to compare statistical differences between summary histograms, which are the histograms summed over a large ensemble of individual histograms. It consists of choosing a distance statistic for measuring the difference between summary histograms and using a bootstrap procedure to calculate the statistical significance level. Bootstrapping is an approach to statistical inference that makes few assumptions about the underlying probability distribution that describes the data. Three distance statistics are compared in this study. They are the Euclidean distance, the Jeffries-Matusita distance and the Kuiper distance. The data used in testing the bootstrap method are satellite measurements of cloud systems called cloud objects. Each cloud object is defined as a contiguous region/patch composed of individual footprints or fields of view. A histogram of measured values over footprints is generated for each parameter of each cloud object and then summary histograms are accumulated over all individual histograms in a given cloud-object size category. The results of statistical hypothesis tests using all three distances as test statistics are generally similar, indicating the validity of the proposed method. The Euclidean distance is determined to be most suitable after comparing the statistical tests of several parameters with distinct probability distributions among three cloud-object size categories. Impacts on the statistical significance levels resulting from differences in the total lengths of satellite footprint data between two size categories are also discussed.

Using statistical model to simulate the impact of climate change on maize yield with climate and crop uncertainties

NASA Astrophysics Data System (ADS)

Zhang, Yi; Zhao, Yanxia; Wang, Chunyi; Chen, Sining

2017-11-01

Assessment of the impact of climate change on crop productions with considering uncertainties is essential for properly identifying and decision-making agricultural practices that are sustainable. In this study, we employed 24 climate projections consisting of the combinations of eight GCMs and three emission scenarios representing the climate projections uncertainty, and two crop statistical models with 100 sets of parameters in each model representing parameter uncertainty within the crop models. The goal of this study was to evaluate the impact of climate change on maize ( Zea mays L.) yield at three locations (Benxi, Changling, and Hailun) across Northeast China (NEC) in periods 2010-2039 and 2040-2069, taking 1976-2005 as the baseline period. The multi-models ensembles method is an effective way to deal with the uncertainties. The results of ensemble simulations showed that maize yield reductions were less than 5 % in both future periods relative to the baseline. To further understand the contributions of individual sources of uncertainty, such as climate projections and crop model parameters, in ensemble yield simulations, variance decomposition was performed. The results indicated that the uncertainty from climate projections was much larger than that contributed by crop model parameters. Increased ensemble yield variance revealed the increasing uncertainty in the yield simulation in the future periods.

Experimental programme on absolute fission fragment yields with the lohengrin spectrometer: New optical and statistical methodologies

NASA Astrophysics Data System (ADS)

Abdelaziz, Chebboubi; Grégoire, Kessedjian; Olivier, Serot; Sylvain, Julien-Laferriere; Christophe, Sage; Florence, Martin; Olivier, Méplan; David, Bernard; Olivier, Litaize; Aurélien, Blanc; Herbert, Faust; Paolo, Mutti; Ulli, Köster; Alain, Letourneau; Thomas, Materna; Michal, Rapala

2017-09-01

The study of fission yields has a major impact on the characterization and understanding of the fission process and is mandatory for reactor applications. In the past with the LOHENGRIN spectrometer of the ILL, priority has been given for the studies in the light fission fragment mass range. The LPSC in collaboration with ILL and CEA has developed a measurement program on symmetric and heavy mass fission fragment distributions. The combination of measurements with ionisation chamber and Ge detectors is necessary to describe precisely the heavy fission fragment region in mass and charge. Recently, new measurements of fission yields and kinetic energy distributions are has been made on the 233U(nth,f) reaction. The focus of this work has been on the new optical and statistical methodology and the self-normalization of the data to provide new absolute measurements, independently of any libraries, and the associated experimental covariance matrix.

Simulating the exoplanet yield of a space-based mid-infrared interferometer based on Kepler statistics

NASA Astrophysics Data System (ADS)

Kammerer, Jens; Quanz, Sascha P.

2018-01-01

Aims: We predict the exoplanet yield of a space-based mid-infrared nulling interferometer using Monte Carlo simulations. We quantify the number and properties of detectable exoplanets and identify those target stars that have the highest or most complete detection rate. We investigate how changes in the underlying technical assumptions and uncertainties in the underlying planet population impact the scientific return. Methods: We simulated 2000 exoplanetary systems, based on planet occurrence statistics from Kepler with randomly orientated orbits and uniformly distributed albedos around each of 326 nearby (d< 20 pc) stars. Assuming thermal equilibrium and blackbody emission, together with the limiting spatial resolution and sensitivity of our simulated instrument in the three specific bands 5.6, 10.0, and 15.0 μm, we quantified the number of detectable exoplanets as a function of their radii and equilibrium temperatures. Results: Approximately exoplanets, with radii 0.5 REarth ≤ Rp ≤ 6 REarth, were detected in at least one band and half were detected in all three bands during 0.52 years of mission time assuming throughputs 3.5 times worse than those for the James Webb Space Telescope and 40% overheads. Accounting for stellar leakage and (unknown) exozodiacal light, the discovery phase of the mission very likely requires 2-3 years in total. The uncertainties in planet yield are dominated by uncertainties in the underlying planet population, but the distribution of the Bond albedos also has a significant impact. Roughly 50% of the detected planets orbit M stars, which also have the highest planet yield per star; the other 50% orbit FGK stars, which show a higher completeness in the detectability. Roughly 85 planets could be habitable (0.5 REarth ≤ Rp ≤ 1.75 REarth and 200 K ≤ Teq ≤ 450 K) and are prime targets for spectroscopic observations in a second mission phase. Comparing these results to those of a large optical/near-infrared telescope, we find

Strategies for Testing Statistical and Practical Significance in Detecting DIF with Logistic Regression Models

ERIC Educational Resources Information Center

Fidalgo, Angel M.; Alavi, Seyed Mohammad; Amirian, Seyed Mohammad Reza

2014-01-01

This study examines three controversial aspects in differential item functioning (DIF) detection by logistic regression (LR) models: first, the relative effectiveness of different analytical strategies for detecting DIF; second, the suitability of the Wald statistic for determining the statistical significance of the parameters of interest; and…

Global Agriculture Yields and Conflict under Future Climate

NASA Astrophysics Data System (ADS)

Rising, J.; Cane, M. A.

2013-12-01

Aspects of climate have been shown to correlate significantly with conflict. We investigate a possible pathway for these effects through changes in agriculture yields, as predicted by field crop models (FAO's AquaCrop and DSSAT). Using satellite and station weather data, and surveyed data for soil and management, we simulate major crop yields across all countries between 1961 and 2008, and compare these to FAO and USDA reported yields. Correlations vary by country and by crop, from approximately .8 to -.5. Some of this range in crop model performance is explained by crop varieties, data quality, and other natural, economic, and political features. We also quantify the ability of AquaCrop and DSSAT to simulate yields under past cycles of ENSO as a proxy for their performance under changes in climate. We then describe two statistical models which relate crop yields to conflict events from the UCDP/PRIO Armed Conflict dataset. The first relates several preceding years of predicted yields of the major grain in each country to any conflict involving that country. The second uses the GREG ethnic group maps to identify differences in predicted yields between neighboring regions. By using variation in predicted yields to explain conflict, rather than actual yields, we can identify the exogenous effects of weather on conflict. Finally, we apply precipitation and temperature time-series under IPCC's A1B scenario to the statistical models. This allows us to estimate the scale of the impact of future yields on future conflict. Centroids of the major growing regions for each country's primary crop, based on USDA FAS consumption. Correlations between simulated yields and reported yields, for AquaCrop and DSSAT, under the assumption that no irrigation, fertilization, or pest control is used. Reported yields are the average of FAO yields and USDA FAS yields, where both are available.

A Priori Estimation of Organic Reaction Yields

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

Emami, Fateme S.; Vahid, Amir; Wylie, Elizabeth K.

2015-07-21

A thermodynamically guided calculation of free energies of substrate and product molecules allows for the estimation of the yields of organic reactions. The non-ideality of the system and the solvent effects are taken into account through the activity coefficients calculated at the molecular level by perturbed-chain statistical associating fluid theory (PC-SAFT). The model is iteratively trained using a diverse set of reactions with yields that have been reported previously. This trained model can then estimate a priori the yields of reactions not included in the training set with an accuracy of ca. ±15 %. This ability has the potential tomore » translate into significant economic savings through the selection and then execution of only those reactions that can proceed in good yields.« less

Clinical relevance vs. statistical significance: Using neck outcomes in patients with temporomandibular disorders as an example.

PubMed

Armijo-Olivo, Susan; Warren, Sharon; Fuentes, Jorge; Magee, David J

2011-12-01

Statistical significance has been used extensively to evaluate the results of research studies. Nevertheless, it offers only limited information to clinicians. The assessment of clinical relevance can facilitate the interpretation of the research results into clinical practice. The objective of this study was to explore different methods to evaluate the clinical relevance of the results using a cross-sectional study as an example comparing different neck outcomes between subjects with temporomandibular disorders and healthy controls. Subjects were compared for head and cervical posture, maximal cervical muscle strength, endurance of the cervical flexor and extensor muscles, and electromyographic activity of the cervical flexor muscles during the CranioCervical Flexion Test (CCFT). The evaluation of clinical relevance of the results was performed based on the effect size (ES), minimal important difference (MID), and clinical judgement. The results of this study show that it is possible to have statistical significance without having clinical relevance, to have both statistical significance and clinical relevance, to have clinical relevance without having statistical significance, or to have neither statistical significance nor clinical relevance. The evaluation of clinical relevance in clinical research is crucial to simplify the transfer of knowledge from research into practice. Clinical researchers should present the clinical relevance of their results. Copyright © 2011 Elsevier Ltd. All rights reserved.

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

PubMed

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

1991-01-01

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

Commercially sterilized mussel meats (Mytilus chilensis): a study on process yield.

PubMed

Almonacid, S; Bustamante, J; Simpson, R; Urtubia, A; Pinto, M; Teixeira, A

2012-06-01

The processing steps most responsible for yield loss in the manufacture of canned mussel meats are the thermal treatments of precooking to remove meats from shells, and thermal processing (retorting) to render the final canned product commercially sterile for long-term shelf stability. The objective of this study was to investigate and evaluate the impact of different combinations of process variables on the ultimate drained weight in the final mussel product (Mytilu chilensis), while verifying that any differences found were statistically and economically significant. The process variables selected for this study were precooking time, brine salt concentration, and retort temperature. Results indicated 2 combinations of process variables producing the widest difference in final drained weight, designated best combination and worst combination with 35% and 29% yield, respectively. Significance of this difference was determined by employing a Bootstrap methodology, which assumes an empirical distribution of statistical error. A difference of nearly 6 percentage points in total yield was found. This represents a 20% increase in annual sales from the same quantity of raw material, in addition to increase in yield, the conditions for the best process included a retort process time 65% shorter than that for the worst process, this difference in yield could have significant economic impact, important to the mussel canning industry. © 2012 Institute of Food Technologists®

The role of climatic variables in winter cereal yields: a retrospective analysis.

PubMed

Luo, Qunying; Wen, Li

2015-02-01

This study examined the effects of observed climate including [CO2] on winter cereal [winter wheat (Triticum aestivum), barley (Hordeum vulgare) and oat (Avena sativa)] yields by adopting robust statistical analysis/modelling approaches (i.e. autoregressive fractionally integrated moving average, generalised addition model) based on long time series of historical climate data and cereal yield data at three locations (Moree, Dubbo and Wagga Wagga) in New South Wales, Australia. Research results show that (1) growing season rainfall was significantly, positively and non-linearly correlated with crop yield at all locations considered; (2) [CO2] was significantly, positively and non-linearly correlated with crop yields in all cases except wheat and barley yields at Wagga Wagga; (3) growing season maximum temperature was significantly, negatively and non-linearly correlated with crop yields at Dubbo and Moree (except for barley); and (4) radiation was only significantly correlated with oat yield at Wagga Wagga. This information will help to identify appropriate management adaptation options in dealing with the risk and in taking the opportunities of climate change.

Building a statistical emulator for prediction of crop yield response to climate change: a global gridded panel data set approach

NASA Astrophysics Data System (ADS)

Mistry, Malcolm; De Cian, Enrica; Wing, Ian Sue

2015-04-01

There is widespread concern that trends and variability in weather induced by climate change will detrimentally affect global agricultural productivity and food supplies. Reliable quantification of the risks of negative impacts at regional and global scales is a critical research need, which has so far been met by forcing state-of-the-art global gridded crop models with outputs of global climate model (GCM) simulations in exercises such as the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP)-Fastrack. Notwithstanding such progress, it remains challenging to use these simulation-based projections to assess agricultural risk because their gridded fields of crop yields are fundamentally denominated as discrete combinations of warming scenarios, GCMs and crop models, and not as model-specific or model-averaged yield response functions of meteorological shifts, which may have their own independent probability of occurrence. By contrast, the empirical climate economics literature has adeptly represented agricultural responses to meteorological variables as reduced-form statistical response surfaces which identify the crop productivity impacts of additional exposure to different intervals of temperature and precipitation [cf Schlenker and Roberts, 2009]. This raises several important questions: (1) what do the equivalent reduced-form statistical response surfaces look like for crop model outputs, (2) do they exhibit systematic variation over space (e.g., crop suitability zones) or across crop models with different characteristics, (3) how do they compare to estimates based on historical observations, and (4) what are the implications for the characterization of climate risks? We address these questions by estimating statistical yield response functions for four major crops (maize, rice, wheat and soybeans) over the historical period (1971-2004) as well as future climate change scenarios (2005-2099) using ISIMIP-Fastrack data for five GCMs and seven crop models

The fragility of statistically significant findings from randomized trials in head and neck surgery.

PubMed

Noel, Christopher W; McMullen, Caitlin; Yao, Christopher; Monteiro, Eric; Goldstein, David P; Eskander, Antoine; de Almeida, John R

2018-04-23

The Fragility Index (FI) is a novel tool for evaluating the robustness of statistically significant findings in a randomized control trial (RCT). It measures the number of events upon which statistical significance depends. We sought to calculate the FI scores for RCTs in the head and neck cancer literature where surgery was a primary intervention. Potential articles were identified in PubMed (MEDLINE), Embase, and Cochrane without publication date restrictions. Two reviewers independently screened eligible RCTs reporting at least one dichotomous and statistically significant outcome. The data from each trial were extracted and the FI scores were calculated. Associations between trial characteristics and FI were determined. In total, 27 articles were identified. The median sample size was 67.5 (interquartile range [IQR] = 42-143) and the median number of events per trial was 8 (IQR = 2.25-18.25). The median FI score was 1 (IQR = 0-2.5), meaning that changing one patient from a nonevent to an event in the treatment arm would change the result to a statistically nonsignificant result, or P > .05. The FI score was less than the number of patients lost to follow-up in 71% of cases. The FI score was found to be moderately correlated with P value (ρ = -0.52, P = .007) and with journal impact factor (ρ = 0.49, P = .009) on univariable analysis. On multivariable analysis, only the P value was found to be a predictor of FI score (P = .001). Randomized trials in the head and neck cancer literature where surgery is a primary modality are relatively nonrobust statistically with low FI scores. Laryngoscope, 2018. © 2018 The American Laryngological, Rhinological and Otological Society, Inc.

Reporting of statistically significant results at ClinicalTrials.gov for completed superiority randomized controlled trials.

PubMed

Dechartres, Agnes; Bond, Elizabeth G; Scheer, Jordan; Riveros, Carolina; Atal, Ignacio; Ravaud, Philippe

2016-11-30

Publication bias and other reporting bias have been well documented for journal articles, but no study has evaluated the nature of results posted at ClinicalTrials.gov. We aimed to assess how many randomized controlled trials (RCTs) with results posted at ClinicalTrials.gov report statistically significant results and whether the proportion of trials with significant results differs when no treatment effect estimate or p-value is posted. We searched ClinicalTrials.gov in June 2015 for all studies with results posted. We included completed RCTs with a superiority hypothesis and considered results for the first primary outcome with results posted. For each trial, we assessed whether a treatment effect estimate and/or p-value was reported at ClinicalTrials.gov and if yes, whether results were statistically significant. If no treatment effect estimate or p-value was reported, we calculated the treatment effect and corresponding p-value using results per arm posted at ClinicalTrials.gov when sufficient data were reported. From the 17,536 studies with results posted at ClinicalTrials.gov, we identified 2823 completed phase 3 or 4 randomized trials with a superiority hypothesis. Of these, 1400 (50%) reported a treatment effect estimate and/or p-value. Results were statistically significant for 844 trials (60%), with a median p-value of 0.01 (Q1-Q3: 0.001-0.26). For the 1423 trials with no treatment effect estimate or p-value posted, we could calculate the treatment effect and corresponding p-value using results reported per arm for 929 (65%). For 494 trials (35%), p-values could not be calculated mainly because of insufficient reporting, censored data, or repeated measurements over time. For the 929 trials we could calculate p-values, we found statistically significant results for 342 (37%), with a median p-value of 0.19 (Q1-Q3: 0.005-0.59). Half of the trials with results posted at ClinicalTrials.gov reported a treatment effect estimate and/or p-value, with significant

Larch Litter Removal Has No Significant Effect On Runoff

Treesearch

Richard S. Startz; David N. Tolsted

1974-01-01

Runoff was measured on paired litter-removed, litter-left plots in an 11-year-old European larch plantation. On five of the six pairs of plots, the plot with the litter left intact yielded more runoff. however, the differences were neither statistically nor hydrologically significant.

Statistical significance of task related deep brain EEG dynamic changes in the time-frequency domain.

PubMed

Chládek, J; Brázdil, M; Halámek, J; Plešinger, F; Jurák, P

2013-01-01

We present an off-line analysis procedure for exploring brain activity recorded from intra-cerebral electroencephalographic data (SEEG). The objective is to determine the statistical differences between different types of stimulations in the time-frequency domain. The procedure is based on computing relative signal power change and subsequent statistical analysis. An example of characteristic statistically significant event-related de/synchronization (ERD/ERS) detected across different frequency bands following different oddball stimuli is presented. The method is used for off-line functional classification of different brain areas.

Intensive inpatient treatment for bulimia nervosa: Statistical and clinical significance of symptom changes.

PubMed

Diedrich, Alice; Schlegl, Sandra; Greetfeld, Martin; Fumi, Markus; Voderholzer, Ulrich

2018-03-01

This study examines the statistical and clinical significance of symptom changes during an intensive inpatient treatment program with a strong psychotherapeutic focus for individuals with severe bulimia nervosa. 295 consecutively admitted bulimic patients were administered the Structured Interview for Anorexic and Bulimic Syndromes-Self-Rating (SIAB-S), the Eating Disorder Inventory-2 (EDI-2), the Brief Symptom Inventory (BSI), and the Beck Depression Inventory-II (BDI-II) at treatment intake and discharge. Results indicated statistically significant symptom reductions with large effect sizes regarding severity of binge eating and compensatory behavior (SIAB-S), overall eating disorder symptom severity (EDI-2), overall psychopathology (BSI), and depressive symptom severity (BDI-II) even when controlling for antidepressant medication. The majority of patients showed either reliable (EDI-2: 33.7%, BSI: 34.8%, BDI-II: 18.1%) or even clinically significant symptom changes (EDI-2: 43.2%, BSI: 33.9%, BDI-II: 56.9%). Patients with clinically significant improvement were less distressed at intake and less likely to suffer from a comorbid borderline personality disorder when compared with those who did not improve to a clinically significant extent. Findings indicate that intensive psychotherapeutic inpatient treatment may be effective in about 75% of severely affected bulimic patients. For the remaining non-responding patients, inpatient treatment might be improved through an even stronger focus on the reduction of comorbid borderline personality traits.

Brazilian Soybean Yields and Yield Gaps Vary with Farm Size

NASA Astrophysics Data System (ADS)

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.

Multivariate Statistical Models for Predicting Sediment Yields from Southern California Watersheds

USGS Publications Warehouse

Gartner, Joseph E.; Cannon, Susan H.; Helsel, Dennis R.; Bandurraga, Mark

2009-01-01

Debris-retention basins in Southern California are frequently used to protect communities and infrastructure from the hazards of flooding and debris flow. Empirical models that predict sediment yields are used to determine the size of the basins. Such models have been developed using analyses of records of the amount of material removed from debris retention basins, associated rainfall amounts, measures of watershed characteristics, and wildfire extent and history. In this study we used multiple linear regression methods to develop two updated empirical models to predict sediment yields for watersheds located in Southern California. The models are based on both new and existing measures of volume of sediment removed from debris retention basins, measures of watershed morphology, and characterization of burn severity distributions for watersheds located in Ventura, Los Angeles, and San Bernardino Counties. The first model presented reflects conditions in watersheds located throughout the Transverse Ranges of Southern California and is based on volumes of sediment measured following single storm events with known rainfall conditions. The second model presented is specific to conditions in Ventura County watersheds and was developed using volumes of sediment measured following multiple storm events. To relate sediment volumes to triggering storm rainfall, a rainfall threshold was developed to identify storms likely to have caused sediment deposition. A measured volume of sediment deposited by numerous storms was parsed among the threshold-exceeding storms based on relative storm rainfall totals. The predictive strength of the two models developed here, and of previously-published models, was evaluated using a test dataset consisting of 65 volumes of sediment yields measured in Southern California. The evaluation indicated that the model developed using information from single storm events in the Transverse Ranges best predicted sediment yields for watersheds in San

Using the Descriptive Bootstrap to Evaluate Result Replicability (Because Statistical Significance Doesn't)

ERIC Educational Resources Information Center

Spinella, Sarah

2011-01-01

As result replicability is essential to science and difficult to achieve through external replicability, the present paper notes the insufficiency of null hypothesis statistical significance testing (NHSST) and explains the bootstrap as a plausible alternative, with a heuristic example to illustrate the bootstrap method. The bootstrap relies on…

In situ earthworm breeding in orchards significantly improves the growth, quality and yield of papaya (Carica papaya L.)

PubMed Central

Xiang, Huimin; Guo, Lei; Zhao, Benliang

2016-01-01

The aim of this study was to compare the effects of four fertilizer applications—control (C), chemical fertilizer (F), compost (O), and in situ earthworm breeding (E)—on the growth, quality and yield of papaya (Carica papaya L.). In this study, 5 g plant−1 urea (CH4N2O, %N = 46.3%) and 100 g plant−1 microelement fertilizer was applied to each treatment. The fertilizer applications of these four treatments are different from each other. The results showed that the E treatment had the highest growth parameters over the whole growth period. At 127 days after transplantation, the order of plant heights from greatest to smallest was E > F > O > C, and the stem diameters were E > F > O > C, with significant differences between all treatments. Soluble-solid, sugar, vitamin C, and protein content significantly increased in the E treatment. In addition, the total acid and the electrical conductivity of the fruit significantly decreased in the E treatment. Fruit firmness clearly increased in the O treatment, and decreased in the F treatment. The fresh individual fruit weights, fruit numbers, and total yields were greatly improved in the F and E treatments, and the total yield of the E treatment was higher than that in the F treatment. In conclusion, the in situ earthworm breeding treatment performed better than conventional compost and chemical fertilizer treatments. Furthermore, in situ earthworm breeding may be a potential organic fertilizer application in orchards because it not only improves the fruit quality and yield but also reduces the amount of organic wastes from agriculture as a result of the activities of earthworms. PMID:27994969

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

NASA Astrophysics Data System (ADS)

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.

Cloud-based solution to identify statistically significant MS peaks differentiating sample categories.

PubMed

Ji, Jun; Ling, Jeffrey; Jiang, Helen; Wen, Qiaojun; Whitin, John C; Tian, Lu; Cohen, Harvey J; Ling, Xuefeng B

2013-03-23

Mass spectrometry (MS) has evolved to become the primary high throughput tool for proteomics based biomarker discovery. Until now, multiple challenges in protein MS data analysis remain: large-scale and complex data set management; MS peak identification, indexing; and high dimensional peak differential analysis with the concurrent statistical tests based false discovery rate (FDR). "Turnkey" solutions are needed for biomarker investigations to rapidly process MS data sets to identify statistically significant peaks for subsequent validation. Here we present an efficient and effective solution, which provides experimental biologists easy access to "cloud" computing capabilities to analyze MS data. The web portal can be accessed at http://transmed.stanford.edu/ssa/. Presented web application supplies large scale MS data online uploading and analysis with a simple user interface. This bioinformatic tool will facilitate the discovery of the potential protein biomarkers using MS.

Statistical Analysis Experiment for Freshman Chemistry Lab.

ERIC Educational Resources Information Center

Salzsieder, John C.

1995-01-01

Describes a laboratory experiment dissolving zinc from galvanized nails in which data can be gathered very quickly for statistical analysis. The data have sufficient significant figures and the experiment yields a nice distribution of random errors. Freshman students can gain an appreciation of the relationships between random error, number of…

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

USGS Publications Warehouse

DeSimone, Leslie A.; Barbaro, Jeffrey R.

2012-01-01

The yield of bedrock wells in the fractured-bedrock aquifers of the Nashoba terrane and surrounding area, central and eastern Massachusetts, was investigated with analyses of existing data. Reported well yield was compiled for 7,287 wells from Massachusetts Department of Environmental Protection and U.S. Geological Survey databases. Yield of these wells ranged from 0.04 to 625 gallons per minute. In a comparison with data from 103 supply wells, yield and specific capacity from aquifer tests were well correlated, indicating that reported well yield was a reasonable measure of aquifer characteristics in the study area. Statistically significant relations were determined between well yield and a number of cultural and hydrogeologic factors. Cultural variables included intended water use, well depth, year of construction, and method of yield measurement. Bedrock geology, topography, surficial geology, and proximity to surface waters were statistically significant hydrogeologic factors. Yield of wells was higher in areas of granites, mafic intrusive rocks, and amphibolites than in areas of schists and gneisses or pelitic rocks; higher in valleys and low-slope areas than on hills, ridges, or high slopes; higher in areas overlain by stratified glacial deposits than in areas overlain by till; and higher in close proximity to streams, ponds, and wetlands than at greater distances from these surface-water features. Proximity to mapped faults and to lineaments from aerial photographs also were related to well yield by some measures in three quadrangles in the study area. Although the statistical significance of these relations was high, their predictive power was low, and these relations explained little of the variability in the well-yield data. Similar results were determined from a multivariate regression analysis. Multivariate regression models for the Nashoba terrane and for a three-quadrangle subarea included, as significant variables, many of the cultural and

Statistical Significance of Optical Map Alignments

PubMed Central

Sarkar, Deepayan; Goldstein, Steve; Schwartz, David C.

2012-01-01

Abstract The Optical Mapping System constructs ordered restriction maps spanning entire genomes through the assembly and analysis of large datasets comprising individually analyzed genomic DNA molecules. Such restriction maps uniquely reveal mammalian genome structure and variation, but also raise computational and statistical questions beyond those that have been solved in the analysis of smaller, microbial genomes. We address the problem of how to filter maps that align poorly to a reference genome. We obtain map-specific thresholds that control errors and improve iterative assembly. We also show how an optimal self-alignment score provides an accurate approximation to the probability of alignment, which is useful in applications seeking to identify structural genomic abnormalities. PMID:22506568

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research.

PubMed

Gaskin, Cadeyrn J; Happell, Brenda

2014-05-01

improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Harvests from bone marrow donors who weigh less than their recipients are associated with a significantly increased probability of a suboptimal harvest yield.

PubMed

Anthias, Chloe; Billen, Annelies; Arkwright, Rebecca; Szydlo, Richard M; Madrigal, J Alejandro; Shaw, Bronwen E

2016-05-01

Previous studies have demonstrated the importance of bone marrow (BM) harvest yield in determining transplant outcomes, but little is known regarding donor and procedure variables associated with achievement of an optimal yield. We hypothesized that donor demographics and variables relating to the procedure were likely to impact the yield (total nucleated cells [TNCs]/kg recipient weight) and quality (TNCs/mL) of the harvest. To test our hypothesis, BM harvests of 110 consecutive unrelated donors were evaluated. The relationship between donor or procedure characteristics and the BM harvest yield was examined. The relationship between donor and recipient weight significantly influenced the harvest yield; only 14% of BM harvests from donors who weighed less than their recipient achieved a TNC count of more than 4 × 10(8) /kg compared to 56% of harvests from donors heavier than their recipient (p = 0.001). Higher-volume harvests were significantly less likely to achieve an optimal yield than lower-volume harvests (32% vs. 78%; p = 0.007), and higher-volume harvests contained significantly fewer TNCs/mL, indicating peripheral blood contamination. BM harvest quality also varied significantly between collection centers adding to recent concerns regarding maintenance of BM harvest expertise within the transplant community. Since the relationship between donor and recipient weight has a critical influence yield, we recommend prioritizing this secondary donor characteristic when selecting from multiple well-matched donors. Given the declining number of requests for BM harvests, it is crucial that systems are developed to train operators and ensure expertise in this procedure is retained. © 2016 AABB.

Similar Estimates of Temperature Impacts on Global Wheat Yield by Three Independent Methods

NASA Technical Reports Server (NTRS)

Liu, Bing; Asseng, Senthold; Muller, Christoph; Ewart, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.;

Similar estimates of temperature impacts on global wheat yield by three independent methods

NASA Astrophysics Data System (ADS)

Liu, Bing; Asseng, Senthold; Müller, Christoph; Ewert, Frank; Elliott, Joshua; Lobell, David B.; Martre, Pierre; Ruane, Alex C.; Wallach, Daniel; Jones, James W.; Rosenzweig, Cynthia; Aggarwal, Pramod K.; Alderman, Phillip D.; Anothai, Jakarat; Basso, Bruno; Biernath, Christian; Cammarano, Davide; Challinor, Andy; Deryng, Delphine; Sanctis, Giacomo De; Doltra, Jordi; Fereres, Elias; Folberth, Christian; Garcia-Vila, Margarita; Gayler, Sebastian; Hoogenboom, Gerrit; Hunt, Leslie A.; Izaurralde, Roberto C.; Jabloun, Mohamed; Jones, Curtis D.; Kersebaum, Kurt C.; Kimball, Bruce A.; Koehler, Ann-Kristin; Kumar, Soora Naresh; Nendel, Claas; O'Leary, Garry J.; Olesen, Jørgen E.; Ottman, Michael J.; Palosuo, Taru; Prasad, P. V. Vara; Priesack, Eckart; Pugh, Thomas A. M.; Reynolds, Matthew; Rezaei, Ehsan E.; Rötter, Reimund P.; Schmid, Erwin; Semenov, Mikhail A.; Shcherbak, Iurii; Stehfest, Elke; Stöckle, Claudio O.; Stratonovitch, Pierre; Streck, Thilo; Supit, Iwan; Tao, Fulu; Thorburn, Peter; Waha, Katharina; Wall, Gerard W.; Wang, Enli; White, Jeffrey W.; Wolf, Joost; Zhao, Zhigan; Zhu, Yan

2016-12-01

The potential impact of global temperature change on global crop yield has recently been assessed with different methods. Here we show that grid-based and point-based simulations and statistical regressions (from historic records), without deliberate adaptation or CO2 fertilization effects, produce similar estimates of temperature impact on wheat yields at global and national scales. With a 1 °C global temperature increase, global wheat yield is projected to decline between 4.1% and 6.4%. Projected relative temperature impacts from different methods were similar for major wheat-producing countries China, India, USA and France, but less so for Russia. Point-based and grid-based simulations, and to some extent the statistical regressions, were consistent in projecting that warmer regions are likely to suffer more yield loss with increasing temperature than cooler regions. By forming a multi-method ensemble, it was possible to quantify `method uncertainty’ in addition to model uncertainty. This significantly improves confidence in estimates of climate impacts on global food security.

Differences, or lack thereof, in wheat and maize yields under three low-warming scenarios

NASA Astrophysics Data System (ADS)

Tebaldi, Claudia; Lobell, David

2018-06-01

The availability of climate model experiments under three alternative scenarios stabilizing at warming targets inspired by the COP21 agreements (a 1.5 °C not exceed, a 1.5 °C with overshoot and a 2.0 °C) makes it possible to assess future expected changes in global yields for two staple crops, wheat and maize. In this study an empirical model of the relation between crop yield anomalies and temperature and precipitation changes, with or without the inclusion of CO2 fertilization effects, is used to produce ensembles of time series of yield outcomes on a yearly basis over the course of the 21st century, for each scenario. The 21st century is divided into 10 year windows starting from 2020, within which the statistical significance and the magnitude of the differences in yield changes between pairs of scenarios are assessed, thus evaluating if and when benefits of mitigations appear, and how substantial they are. Additionally, a metric of extreme heat tailored to the individual crops (number of days during the growing season above a crop-specific threshold) is used to measure exposure to harmful temperatures under the different scenarios. If CO2 effects are not included, statistically significant differences in yields of both crops appear as early as the 2030s but the magnitude of the differences remains below 3% of the historical baseline in all cases until the second part of the century. In the later decades of the 21st century, differences remain small and eventually stop being statistically significant between the two scenarios stabilizing at 1.5 °C, while differences between these two lower scenarios and the 2.0 °C scenario grow to about 4%. The inclusion of CO2 effects erases all significant benefits of mitigation for wheat, while the significance of differences is maintained for maize yields between the higher and the two lower scenarios, albeit with smaller benefits in magnitude. Changes in extremes are significant within each of the scenarios

Climate variation explains a third of global crop yield variability

PubMed Central

Ray, Deepak K.; Gerber, James S.; MacDonald, Graham K.; West, Paul C.

2015-01-01

Many studies have examined the role of mean climate change in agriculture, but an understanding of the influence of inter-annual climate variations on crop yields in different regions remains elusive. We use detailed crop statistics time series for ~13,500 political units to examine how recent climate variability led to variations in maize, rice, wheat and soybean crop yields worldwide. While some areas show no significant influence of climate variability, in substantial areas of the global breadbaskets, >60% of the yield variability can be explained by climate variability. Globally, climate variability accounts for roughly a third (~32–39%) of the observed yield variability. Our study uniquely illustrates spatial patterns in the relationship between climate variability and crop yield variability, highlighting where variations in temperature, precipitation or their interaction explain yield variability. We discuss key drivers for the observed variations to target further research and policy interventions geared towards buffering future crop production from climate variability. PMID:25609225

Statistically significant performance results of a mine detector and fusion algorithm from an x-band high-resolution SAR

NASA Astrophysics Data System (ADS)

Williams, Arnold C.; Pachowicz, Peter W.

2004-09-01

Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

This paper seeks to understand the role that climate variability has on annual yield of sugarcane in Louisiana. Unique features of sugarcane growth in Louisiana and nonclimatic, yield-influencing factors make this goal an interesting and challenging one. Several methods of seeking and establishing the relations between yield and climate variables are employed. First, yield climate relations were investigated at a single research station where crop variety and growing conditions could be held constant and yield relations could be established between a predominant older crop variety and a newer one. Interviews with crop experts and a literature survey were used to identify potential climatic factors that control yield. A statistical analysis was performed using statewide yield data from the American Sugar Cane League from 1963 to 2002 and a climate database. Yield values for later years were adjusted downward to form an adjusted yield dataset. The climate database was principally constructed from daily and monthly values of maximum and minimum temperature and daily and monthly total precipitation for six cooperative weather-reporting stations representative of the area of sugarcane production. The influence of 74 different, though not independent, climate-related variables on sugarcane yield was investigated. The fact that a climate signal exists is demonstrated by comparing mean values of the climate variables corresponding to the upper and lower third of adjusted yield values. Most of these mean-value differences show an intuitively plausible difference between the high- and low-yield years. The difference between means of the climate variables for years corresponding to the upper and lower third of annual yield values for 13 of the variables is statistically significant at or above the 90% level. A correlation matrix was used to identify the variables that had the largest influence on annual yield. Four variables [called here critical climatic variables (CCV

Estimating variability in grain legume yields across Europe and the Americas

NASA Astrophysics Data System (ADS)

Cernay, Charles; Ben-Ari, Tamara; Pelzer, Elise; Meynard, Jean-Marc; Makowski, David

2015-06-01

Grain legume production in Europe has recently come under scrutiny. Although legume crops are often promoted to provide environmental services, European farmers tend to turn to non-legume crops. It is assumed that high variability in legume yields explains this aversion, but so far this hypothesis has not been tested. Here, we estimate the variability of major grain legume and non-legume yields in Europe and the Americas from yield time series over 1961-2013. Results show that grain legume yields are significantly more variable than non-legume yields in Europe. These differences are smaller in the Americas. Our results are robust at the level of the statistical methods. In all regions, crops with high yield variability are allocated to less than 1% of cultivated areas. Although the expansion of grain legumes in Europe may be hindered by high yield variability, some species display risk levels compatible with the development of specialized supply chains.

Fusion yield: Guderley model and Tsallis statistics

NASA Astrophysics Data System (ADS)

Haubold, H. J.; Kumar, D.

2011-02-01

The reaction rate probability integral is extended from Maxwell-Boltzmann approach to a more general approach by using the pathway model introduced by Mathai in 2005 (A pathway to matrix-variate gamma and normal densities. Linear Algebr. Appl. 396, 317-328). The extended thermonuclear reaction rate is obtained in the closed form via a Meijer's G-function and the so-obtained G-function is represented as a solution of a homogeneous linear differential equation. A physical model for the hydrodynamical process in a fusion plasma-compressed and laser-driven spherical shock wave is used for evaluating the fusion energy integral by integrating the extended thermonuclear reaction rate integral over the temperature. The result obtained is compared with the standard fusion yield obtained by Haubold and John in 1981 (Analytical representation of the thermonuclear reaction rate and fusion energy production in a spherical plasma shock wave. Plasma Phys. 23, 399-411). An interpretation for the pathway parameter is also given.

Why publishing everything is more effective than selective publishing of statistically significant results.

PubMed

van Assen, Marcel A L M; van Aert, Robbie C M; Nuijten, Michèle B; Wicherts, Jelte M

2014-01-01

De Winter and Happee examined whether science based on selective publishing of significant results may be effective in accurate estimation of population effects, and whether this is even more effective than a science in which all results are published (i.e., a science without publication bias). Based on their simulation study they concluded that "selective publishing yields a more accurate meta-analytic estimation of the true effect than publishing everything, (and that) publishing nonreplicable results while placing null results in the file drawer can be beneficial for the scientific collective" (p.4). Using their scenario with a small to medium population effect size, we show that publishing everything is more effective for the scientific collective than selective publishing of significant results. Additionally, we examined a scenario with a null effect, which provides a more dramatic illustration of the superiority of publishing everything over selective publishing. Publishing everything is more effective than only reporting significant outcomes.

Why Publishing Everything Is More Effective than Selective Publishing of Statistically Significant Results

PubMed Central

van Assen, Marcel A. L. M.; van Aert, Robbie C. M.; Nuijten, Michèle B.; Wicherts, Jelte M.

2014-01-01

Background De Winter and Happee [1] examined whether science based on selective publishing of significant results may be effective in accurate estimation of population effects, and whether this is even more effective than a science in which all results are published (i.e., a science without publication bias). Based on their simulation study they concluded that “selective publishing yields a more accurate meta-analytic estimation of the true effect than publishing everything, (and that) publishing nonreplicable results while placing null results in the file drawer can be beneficial for the scientific collective” (p.4). Methods and Findings Using their scenario with a small to medium population effect size, we show that publishing everything is more effective for the scientific collective than selective publishing of significant results. Additionally, we examined a scenario with a null effect, which provides a more dramatic illustration of the superiority of publishing everything over selective publishing. Conclusion Publishing everything is more effective than only reporting significant outcomes. PMID:24465448

Colored plastic mulch microclimates affect strawberry fruit yield and quality

NASA Astrophysics Data System (ADS)

Shiukhy, Saeid; Raeini-Sarjaz, Mahmoud; Chalavi, Vida

2015-08-01

Significant reduction of strawberry ( Fragaria × ananassa, Duch.) fruit yield and quality, as a consequence of conventional cultivation method, is common in the Caspian Sea region, Iran. Recently, growers started using plastic mulches to overcome these shortcomings. Plastic mulches have different thermal and radiation properties and could affect strawberry fruit yield and quality. In the present study, the effect of different colored plastic mulches (black, red, and white) along with conventional practice was tested on yield and quality of strawberry Camarosa cultivar, in a completely randomized block design. Colored plastic mulches had highly significant effect on fruit weight, size, and phytochemical contents. In the most harvest times, mean fruit weight was significantly higher in red plastic relative to white and control treatments. Total fruit weight of plastic mulches was not significantly different, while all were statistically higher than that of control. Fruit size significantly increased over red plastic mulch. Total fruit numbers over plastic mulches were significantly higher than that of control treatment. The content of phenolic compounds was similar between treatments, while anthocyanin content, IC50 value, and flavonoid content significantly were affected by colored plastics. In conclusion, colored plastic mulches could affect strawberry fruit weight and quality through altering strawberry thermal and radiation environment.

Colored plastic mulch microclimates affect strawberry fruit yield and quality.

PubMed

Shiukhy, Saeid; Raeini-Sarjaz, Mahmoud; Chalavi, Vida

2015-08-01

Significant reduction of strawberry (Fragaria × ananassa, Duch.) fruit yield and quality, as a consequence of conventional cultivation method, is common in the Caspian Sea region, Iran. Recently, growers started using plastic mulches to overcome these shortcomings. Plastic mulches have different thermal and radiation properties and could affect strawberry fruit yield and quality. In the present study, the effect of different colored plastic mulches (black, red, and white) along with conventional practice was tested on yield and quality of strawberry Camarosa cultivar, in a completely randomized block design. Colored plastic mulches had highly significant effect on fruit weight, size, and phytochemical contents. In the most harvest times, mean fruit weight was significantly higher in red plastic relative to white and control treatments. Total fruit weight of plastic mulches was not significantly different, while all were statistically higher than that of control. Fruit size significantly increased over red plastic mulch. Total fruit numbers over plastic mulches were significantly higher than that of control treatment. The content of phenolic compounds was similar between treatments, while anthocyanin content, IC(50) value, and flavonoid content significantly were affected by colored plastics. In conclusion, colored plastic mulches could affect strawberry fruit weight and quality through altering strawberry thermal and radiation environment.

How to get statistically significant effects in any ERP experiment (and why you shouldn't).

PubMed

Luck, Steven J; Gaspelin, Nicholas

2017-01-01

ERP experiments generate massive datasets, often containing thousands of values for each participant, even after averaging. The richness of these datasets can be very useful in testing sophisticated hypotheses, but this richness also creates many opportunities to obtain effects that are statistically significant but do not reflect true differences among groups or conditions (bogus effects). The purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant but bogus effects, with the likelihood of obtaining at least one such bogus effect exceeding 50% in many experiments. We focus on two specific problems: using the grand-averaged data to select the time windows and electrode sites for quantifying component amplitudes and latencies, and using one or more multifactor statistical analyses. Reanalyses of prior data and simulations of typical experimental designs are used to show how these problems can greatly increase the likelihood of significant but bogus results. Several strategies are described for avoiding these problems and for increasing the likelihood that significant effects actually reflect true differences among groups or conditions. © 2016 Society for Psychophysiological Research.

How to Get Statistically Significant Effects in Any ERP Experiment (and Why You Shouldn’t)

PubMed Central

Luck, Steven J.; Gaspelin, Nicholas

2016-01-01

Event-related potential (ERP) experiments generate massive data sets, often containing thousands of values for each participant, even after averaging. The richness of these data sets can be very useful in testing sophisticated hypotheses, but this richness also creates many opportunities to obtain effects that are statistically significant but do not reflect true differences among groups or conditions (bogus effects). The purpose of this paper is to demonstrate how common and seemingly innocuous methods for quantifying and analyzing ERP effects can lead to very high rates of significant-but-bogus effects, with the likelihood of obtaining at least one such bogus effect exceeding 50% in many experiments. We focus on two specific problems: using the grand average data to select the time windows and electrode sites for quantifying component amplitudes and latencies, and using one or more multi-factor statistical analyses. Re-analyses of prior data and simulations of typical experimental designs are used to show how these problems can greatly increase the likelihood of significant-but-bogus results. Several strategies are described for avoiding these problems and for increasing the likelihood that significant effects actually reflect true differences among groups or conditions. PMID:28000253

Significant Association of Urinary Toxic Metals and Autism-Related Symptoms—A Nonlinear Statistical Analysis with Cross Validation

PubMed Central

Adams, James; Kruger, Uwe; Geis, Elizabeth; Gehn, Eva; Fimbres, Valeria; Pollard, Elena; Mitchell, Jessica; Ingram, Julie; Hellmers, Robert; Quig, David; Hahn, Juergen

2017-01-01

Introduction A number of previous studies examined a possible association of toxic metals and autism, and over half of those studies suggest that toxic metal levels are different in individuals with Autism Spectrum Disorders (ASD). Additionally, several studies found that those levels correlate with the severity of ASD. Methods In order to further investigate these points, this paper performs the most detailed statistical analysis to date of a data set in this field. First morning urine samples were collected from 67 children and adults with ASD and 50 neurotypical controls of similar age and gender. The samples were analyzed to determine the levels of 10 urinary toxic metals (UTM). Autism-related symptoms were assessed with eleven behavioral measures. Statistical analysis was used to distinguish participants on the ASD spectrum and neurotypical participants based upon the UTM data alone. The analysis also included examining the association of autism severity with toxic metal excretion data using linear and nonlinear analysis. “Leave-one-out” cross-validation was used to ensure statistical independence of results. Results and Discussion Average excretion levels of several toxic metals (lead, tin, thallium, antimony) were significantly higher in the ASD group. However, ASD classification using univariate statistics proved difficult due to large variability, but nonlinear multivariate statistical analysis significantly improved ASD classification with Type I/II errors of 15% and 18%, respectively. These results clearly indicate that the urinary toxic metal excretion profiles of participants in the ASD group were significantly different from those of the neurotypical participants. Similarly, nonlinear methods determined a significantly stronger association between the behavioral measures and toxic metal excretion. The association was strongest for the Aberrant Behavior Checklist (including subscales on Irritability, Stereotypy, Hyperactivity, and Inappropriate

Statistics of contractive cracking patterns. [frozen soil-water rheology

NASA Technical Reports Server (NTRS)

Noever, David A.

1991-01-01

The statistics of convective soil patterns are analyzed using statistical crystallography. An underlying hierarchy of order is found to span four orders of magnitude in characteristic pattern length. Strict mathematical requirements determine the two-dimensional (2D) topology, such that random partitioning of space yields a predictable statistical geometry for polygons. For all lengths, Aboav's and Lewis's laws are verified; this result is consistent both with the need to fill 2D space and most significantly with energy carried not by the patterns' interior, but by the boundaries. Together, this suggests a common mechanism of formation for both micro- and macro-freezing patterns.

Statistical significance estimation of a signal within the GooFit framework on GPUs

NASA Astrophysics Data System (ADS)

Cristella, Leonardo; Di Florio, Adriano; Pompili, Alexis

2017-03-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B+ → J/ψϕK+. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

A multivariate model and statistical method for validating tree grade lumber yield equations

Treesearch

Donald W. Seegrist

1975-01-01

Lumber yields within lumber grades can be described by a multivariate linear model. A method for validating lumber yield prediction equations when there are several tree grades is presented. The method is based on multivariate simultaneous test procedures.

Statistical Optimization of 1,3-Propanediol (1,3-PD) Production from Crude Glycerol by Considering Four Objectives: 1,3-PD Concentration, Yield, Selectivity, and Productivity.

PubMed

Supaporn, Pansuwan; Yeom, Sung Ho

2018-04-30

This study investigated the biological conversion of crude glycerol generated from a commercial biodiesel production plant as a by-product to 1,3-propanediol (1,3-PD). Statistical analysis was employed to derive a statistical model for the individual and interactive effects of glycerol, (NH 4 ) 2 SO 4 , trace elements, pH, and cultivation time on the four objectives: 1,3-PD concentration, yield, selectivity, and productivity. Optimum conditions for each objective with its maximum value were predicted by statistical optimization, and experiments under the optimum conditions verified the predictions. In addition, by systematic analysis of the values of four objectives, optimum conditions for 1,3-PD concentration (49.8 g/L initial glycerol, 4.0 g/L of (NH 4 ) 2 SO 4 , 2.0 mL/L of trace element, pH 7.5, and 11.2 h of cultivation time) were determined to be the global optimum culture conditions for 1,3-PD production. Under these conditions, we could achieve high 1,3-PD yield (47.4%), 1,3-PD selectivity (88.8%), and 1,3-PD productivity (2.1/g/L/h) as well as high 1,3-PD concentration (23.6 g/L).

Constitutive overexpression of the TaNF-YB4 gene in transgenic wheat significantly improves grain yield

PubMed Central

Yadav, Dinesh; Shavrukov, Yuri; Bazanova, Natalia; Chirkova, Larissa; Borisjuk, Nikolai; Kovalchuk, Nataliya; Ismagul, Ainur; Parent, Boris; Langridge, Peter; Hrmova, Maria; Lopato, Sergiy

2015-01-01

Heterotrimeric nuclear factors Y (NF-Ys) are involved in regulation of various vital functions in all eukaryotic organisms. Although a number of NF-Y subunits have been characterized in model plants, only a few have been functionally evaluated in crops. In this work, a number of genes encoding NF-YB and NF-YC subunits were isolated from drought-tolerant wheat (Triticum aestivum L. cv. RAC875), and the impact of the overexpression of TaNF-YB4 in the Australian wheat cultivar Gladius was investigated. TaNF-YB4 was isolated as a result of two consecutive yeast two-hybrid (Y2H) screens, where ZmNF-YB2a was used as a starting bait. A new NF-YC subunit, designated TaNF-YC15, was isolated in the first Y2H screen and used as bait in a second screen, which identified two wheat NF-YB subunits, TaNF-YB2 and TaNF-YB4. Three-dimensional modelling of a TaNF-YB2/TaNF-YC15 dimer revealed structural determinants that may underlie interaction selectivity. The TaNF-YB4 gene was placed under the control of the strong constitutive polyubiquitin promoter from maize and introduced into wheat by biolistic bombardment. The growth and yield components of several independent transgenic lines with up-regulated levels of TaNF-YB4 were evaluated under well-watered conditions (T1–T3 generations) and under mild drought (T2 generation). Analysis of T2 plants was performed in large deep containers in conditions close to field trials. Under optimal watering conditions, transgenic wheat plants produced significantly more spikes but other yield components did not change. This resulted in a 20–30% increased grain yield compared with untransformed control plants. Under water-limited conditions transgenic lines maintained parity in yield performance. PMID:26220082

The intriguing evolution of effect sizes in biomedical research over time: smaller but more often statistically significant.

PubMed

Monsarrat, Paul; Vergnes, Jean-Noel

2018-01-01

In medicine, effect sizes (ESs) allow the effects of independent variables (including risk/protective factors or treatment interventions) on dependent variables (e.g., health outcomes) to be quantified. Given that many public health decisions and health care policies are based on ES estimates, it is important to assess how ESs are used in the biomedical literature and to investigate potential trends in their reporting over time. Through a big data approach, the text mining process automatically extracted 814 120 ESs from 13 322 754 PubMed abstracts. Eligible ESs were risk ratio, odds ratio, and hazard ratio, along with their confidence intervals. Here we show a remarkable decrease of ES values in PubMed abstracts between 1990 and 2015 while, concomitantly, results become more often statistically significant. Medians of ES values have decreased over time for both "risk" and "protective" values. This trend was found in nearly all fields of biomedical research, with the most marked downward tendency in genetics. Over the same period, the proportion of statistically significant ESs increased regularly: among the abstracts with at least 1 ES, 74% were statistically significant in 1990-1995, vs 85% in 2010-2015. whereas decreasing ESs could be an intrinsic evolution in biomedical research, the concomitant increase of statistically significant results is more intriguing. Although it is likely that growing sample sizes in biomedical research could explain these results, another explanation may lie in the "publish or perish" context of scientific research, with the probability of a growing orientation toward sensationalism in research reports. Important provisions must be made to improve the credibility of biomedical research and limit waste of resources. © The Authors 2017. Published by Oxford University Press.

Relationships of concentrations of certain blood constituents with milk yield and age of cows in dairy herds.

PubMed

Kitchenham, B A; Rowlands, G J; Shorbagi, H

1975-05-01

Regression analyses were performed on data from 48 Compton metabolic profile tests relating the concentrations of certain constituents in the blood of dairy cows to their milk yield, age and stage of lactation. The common partial regression coefficients for milk yield, age and stage of lactation were estimated for each blood constituent. The relationships of greatest statistical significance were between the concentrations of inorganic phosphate and globulin and age, and the concentration of albumin and milk yield.

Air-insufflated high-definition dacryoendoscopy yields significantly better image quality than conventional dacryoendoscopy.

PubMed

Sasaki, Tsugihisa; Sounou, Tsutomu; Tsuji, Hideki; Sugiyama, Kazuhisa

2017-01-01

To facilitate the analysis of lacrimal conditions, we utilized high-definition dacryoendoscopy (HDD) and undertook observations with a pressure-controlled air-insufflation system. We report the safety and performance of HDD. In this retrospective, non-randomized clinical trial, 46 patients (14 males and 32 females; age range 39-91 years; mean age ± SD 70.3±12.0 years) who had lacrimal disorders were examined with HDD and conventional dacryoendoscopy (CD). The high-definition dacryoendoscope had 15,000 picture element image fibers and an advanced objective lens. Its outer diameter was 0.9-1.2 mm. Air insufflation was controlled at 0-20 kPa with a digital manometer-based pressure-controlled air-insufflation system to evaluate the quality of the image. The HDD had an air/saline irrigation channel between the outer sheath (outer diameter =1.2 mm) and the metal inner sheath of the endoscope. We used it and the CD in air, saline, and diluted milk saline with and without manual irrigation to quantitatively evaluate the effect of air pressure and saline irrigation on image quality. In vivo, the most significant improvement in image quality was demonstrated with air-insufflated (5-15 kPa) HDD, as compared with saline-irrigated HDD and saline-irrigated CD. No emphysema or damage was noted under observation with HDD. In vitro, no significant difference was demonstrated between air-insufflated HDD and saline-irrigated HDD. In vitro, the image quality of air-insufflated HDD was significantly improved as compared with that of saline-irrigated CD. Pressure-controlled (5-15 kPa) air-insufflated HDD is safe, and yields significantly better image quality than CD and saline-irrigated HDD.

Observation of the rare decay B{sup +}{yields}K{sup +}{pi}{sup 0}{pi}{sup 0} and measurement of the quasi-two-body contributions B{sup +}{yields}K*(892){sup +}{pi}{sup 0}, B{sup +}{yields}f{sub 0}(980)K{sup +}, and B{sup +}{yields}{chi}{sub c0}K{sup +}

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

Lees, J. P.; Poireau, V.; Tisserand, V.

We report an analysis of charmless hadronic decays of charged B mesons to the final state K{sup +}{pi}{sup 0}{pi}{sup 0}, using a data sample of (470.9{+-}2.8)x10{sup 6} BB events collected with the BABAR detector at the {Upsilon}(4S) resonance. We observe an excess of signal events, with a significance above 10 standard deviations including systematic uncertainties, and measure the branching fraction and CP asymmetry to be B(B{sup +}{yields}K{sup +}{pi}{sup 0}{pi}{sup 0})=(16.2{+-}1.2{+-}1.5)x10{sup -6} and A{sub CP}(B{sup +}{yields}K{sup +}{pi}{sup 0}{pi}{sup 0})=-0.06{+-}0.06{+-}0.04, where the uncertainties are statistical and systematic, respectively. Additionally, we study the contributions of the B{sup +}{yields}K{sup *}(892){sup +}{pi}{sup 0}, B{sup +}{yields}f{submore » 0}(980)K{sup +}, and B{sup +}{yields}{chi}{sub c0}K{sup +} quasi-two-body decays. We report the world's best measurements of the branching fraction and CP asymmetry of the B{sup +}{yields}K{sup +}{pi}{sup 0}{pi}{sup 0} and B{sup +}{yields}K{sup *}(892){sup +}{pi}{sup 0} channels.« less

Tipping points in the arctic: eyeballing or statistical significance?

PubMed

Carstensen, Jacob; Weydmann, Agata

2012-02-01

Arctic ecosystems have experienced and are projected to experience continued large increases in temperature and declines in sea ice cover. It has been hypothesized that small changes in ecosystem drivers can fundamentally alter ecosystem functioning, and that this might be particularly pronounced for Arctic ecosystems. We present a suite of simple statistical analyses to identify changes in the statistical properties of data, emphasizing that changes in the standard error should be considered in addition to changes in mean properties. The methods are exemplified using sea ice extent, and suggest that the loss rate of sea ice accelerated by factor of ~5 in 1996, as reported in other studies, but increases in random fluctuations, as an early warning signal, were observed already in 1990. We recommend to employ the proposed methods more systematically for analyzing tipping points to document effects of climate change in the Arctic.

Constitutive overexpression of the TaNF-YB4 gene in transgenic wheat significantly improves grain yield.

PubMed

Yadav, Dinesh; Shavrukov, Yuri; Bazanova, Natalia; Chirkova, Larissa; Borisjuk, Nikolai; Kovalchuk, Nataliya; Ismagul, Ainur; Parent, Boris; Langridge, Peter; Hrmova, Maria; Lopato, Sergiy

2015-11-01

Heterotrimeric nuclear factors Y (NF-Ys) are involved in regulation of various vital functions in all eukaryotic organisms. Although a number of NF-Y subunits have been characterized in model plants, only a few have been functionally evaluated in crops. In this work, a number of genes encoding NF-YB and NF-YC subunits were isolated from drought-tolerant wheat (Triticum aestivum L. cv. RAC875), and the impact of the overexpression of TaNF-YB4 in the Australian wheat cultivar Gladius was investigated. TaNF-YB4 was isolated as a result of two consecutive yeast two-hybrid (Y2H) screens, where ZmNF-YB2a was used as a starting bait. A new NF-YC subunit, designated TaNF-YC15, was isolated in the first Y2H screen and used as bait in a second screen, which identified two wheat NF-YB subunits, TaNF-YB2 and TaNF-YB4. Three-dimensional modelling of a TaNF-YB2/TaNF-YC15 dimer revealed structural determinants that may underlie interaction selectivity. The TaNF-YB4 gene was placed under the control of the strong constitutive polyubiquitin promoter from maize and introduced into wheat by biolistic bombardment. The growth and yield components of several independent transgenic lines with up-regulated levels of TaNF-YB4 were evaluated under well-watered conditions (T1-T3 generations) and under mild drought (T2 generation). Analysis of T2 plants was performed in large deep containers in conditions close to field trials. Under optimal watering conditions, transgenic wheat plants produced significantly more spikes but other yield components did not change. This resulted in a 20-30% increased grain yield compared with untransformed control plants. Under water-limited conditions transgenic lines maintained parity in yield performance. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

A Note on Comparing the Power of Test Statistics at Low Significance Levels.

PubMed

Morris, Nathan; Elston, Robert

2011-01-01

It is an obvious fact that the power of a test statistic is dependent upon the significance (alpha) level at which the test is performed. It is perhaps a less obvious fact that the relative performance of two statistics in terms of power is also a function of the alpha level. Through numerous personal discussions, we have noted that even some competent statisticians have the mistaken intuition that relative power comparisons at traditional levels such as α = 0.05 will be roughly similar to relative power comparisons at very low levels, such as the level α = 5 × 10 -8 , which is commonly used in genome-wide association studies. In this brief note, we demonstrate that this notion is in fact quite wrong, especially with respect to comparing tests with differing degrees of freedom. In fact, at very low alpha levels the cost of additional degrees of freedom is often comparatively low. Thus we recommend that statisticians exercise caution when interpreting the results of power comparison studies which use alpha levels that will not be used in practice.

The effect of general anesthesia versus intravenous sedation on diagnostic yield and success in electromagnetic navigation bronchoscopy.

PubMed

Bowling, Mark R; Kohan, Matthew W; Walker, Paul; Efird, Jimmy; Ben Or, Sharon

2015-01-01

Navigational bronchoscopy is utilized to guide biopsies of peripheral lung nodules and place fiducial markers for treatment of limited stage lung cancer with stereotactic body radiotherapy. The type of sedation used for this procedure remains controversial. We performed a retrospective chart review to evaluate the differences of diagnostic yield and overall success of the procedure based on anesthesia type. Electromagnetic navigational bronchoscopy was performed using the superDimension software system. Once the targeted lesion was within reach, multiple tissue samples were obtained. Statistical analysis was used to correlate the yield with the type of sedation among other factors. A successful procedure was defined if a diagnosis was made or a fiducial marker was adequately placed. Navigational bronchoscopy was performed on a total of 120 targeted lesions. The overall complication rate of the procedure was 4.1%. The diagnostic yield and success of the procedure was 74% and 87%, respectively. Duration of the procedure was the only significant difference between the general anesthesia and IV sedation groups (mean, 58 vs. 43 min, P=0.0005). A larger tumor size was associated with a higher diagnostic yield (P=0.032). All other variables in terms of effect on diagnostic yield and an unsuccessful procedure did not meet statistical significance. Navigational bronchoscopy is a safe and effective pulmonary diagnostic tool with relatively low complication rate. The diagnostic yield and overall success of the procedure does not seem to be affected by the type of sedation used.

Acid soil infertility effects on peanut yields and yield components

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

Blamey, F.P.C.

1983-01-01

The interpretation of soil amelioration experiments with peanuts is made difficult by the unpredictibility of the crop and by the many factors altered when ameliorating acid soils. The present study was conducted to investigate the effects of lime and gypsum applications on peanut kernel yield via the three first order yield components, pods per ha, kernels per pod, and kernel mass. On an acid medium sandy loam soil (typic Plinthustult), liming resulted in a highly significant kernel yield increase of 117% whereas gypsum applications were of no significant benefit. As indicated by path coefficient analysis, an increase in the numbermore » of pods per ha was markedly more important in increasing yield than an increase in either the number of kernels per pod or kernel mass. Furthermore, exch. Al was found to be particularly detrimental to pod number. It was postulated that poor peanut yields resulting from acid soil infertility were mainly due to the depressive effect of exch. Al on pod number. Exch. Ca appeared to play a secondary role by ameliorating the adverse effects of exch. Al.« less

Review on the significance of chlorine for crop yield and quality.

PubMed

Geilfus, Christoph-Martin

2018-05-01

The chloride concentration in the plant determines yield and quality formation for two reasons. First, chlorine is a mineral nutrient and deficiencies thereof induce metabolic problems that interfere with growth. However, due to low requirement of most crops, deficiency of chloride hardly appears in the field. Second, excess of chloride, an event that occurs under chloride-salinity, results in severe physiological dysfunctions impairing both quality and yield formation. The chloride ion can effect quality of plant-based products by conferring a salty taste that decreases market appeal of e.g. fruit juices and beverages. However, most of the quality impairments are based on physiological dysfunctions that arise under conditions of chloride-toxicity: Shelf life of persimmon is shortened due to an autocatalytic ethylene production in fruit tissues. High concentrations of chloride in the soil can increase phyto-availability of the heavy metal cadmium, accumulating in wheat grains above dietary intake thresholds. When crops are cultivated on soils that are moderately salinized by chloride, nitrate fertilization might be a strategy to suppress uptake of chloride by means of an antagonistic anion-anion uptake competition. Overall, knowledge about proteins that catalyse chloride-efflux out of the roots or that restrict xylem loading is needed to engineer more resistant crops. Copyright © 2018 Elsevier B.V. All rights reserved.

Global evidence of positive impacts of freshwater biodiversity on fishery yields.

PubMed

Brooks, Emma Grace Elizabeth; Holland, Robert Alan; Darwall, William Robert Thomas; Eigenbrod, Felix; Tittensor, Derek

2016-05-01

An often-invoked benefit of high biodiversity is the provision of ecosystem services. However, evidence for this is largely based on data from small-scale experimental studies of relationships between biodiversity and ecosystem function that may have little relevance to real-world systems. Here, large-scale biodiversity datasets are used to test the relationship between the yield of inland capture fisheries and species richness from 100 countries. Inland waters of Africa, Europe and parts of Asia. A multimodel inference approach was used to assess inland fishery yields at the country level against species richness, waterside human population, area, elevation and various climatic variables, to determine the relative importance of species richness to fisheries yields compared with other major large-scale drivers. Secondly, the mean decadal variation in fishery yields at the country level for 1981-2010 was regressed against species richness to assess if greater diversity reduces the variability in yields over time. Despite a widespread reliance on targeting just a few species of fish, freshwater fish species richness is highly correlated with yield ( R 2  = 0.55) and remains an important and statistically significant predictor of yield once other macroecological drivers are controlled for. Freshwater richness also has a significant negative relationship with variability of yield over time in Africa ( R 2  = 0.16) but no effect in Europe. The management of inland waters should incorporate the protection of freshwater biodiversity, particularly in countries with the highest-yielding inland fisheries as these also tend to have high freshwater biodiversity. As these results suggest a link between biodiversity and stable, high-yielding fisheries, an important win-win outcome may be possible for food security and conservation of freshwater ecosystems. However, findings also highlight the urgent need for more data to fully understand and monitor the contribution of

Use of Tests of Statistical Significance and Other Analytic Choices in a School Psychology Journal: Review of Practices and Suggested Alternatives.

ERIC Educational Resources Information Center

Snyder, Patricia A.; Thompson, Bruce

The use of tests of statistical significance was explored, first by reviewing some criticisms of contemporary practice in the use of statistical tests as reflected in a series of articles in the "American Psychologist" and in the appointment of a "Task Force on Statistical Inference" by the American Psychological Association…

Application of Serratia marcescens RZ-21 significantly enhances peanut yield and remediates continuously cropped peanut soil.

PubMed

Ma, Hai-Yan; Yang, Bo; Wang, Hong-Wei; Yang, Qi-Yin; Dai, Chuan-Chao

2016-01-15

Continuous cropping practices cause a severe decline in peanut yield. The aim of this study was to investigate the remediation effect of Serratia marcescens on continuously cropped peanut soil. A pot experiment was conducted under natural conditions to determine peanut agronomic indices, soil microorganism characteristics, soil enzyme activities and antagonism ability to typical pathogens at different growth stages. Four treatments were applied to red soil as follows: an active fermentation liquor of S. marcescens (RZ-21), an equivalent sterilized fermentation liquor (M), an equivalent fermentation medium (P) and distilled water (CK). S. marcescens significantly inhibited the two typical plant pathogens Fusarium oxysporum A1 and Ralstonia solanacearum B1 and reduced their populations in rhizosphere soil. The RZ-21 treatment significantly increased peanut yield, vine dry weight, root nodules and taproot length by 62.3, 33, 72 and 61.4% respectively, followed by the M treatment. The P treatment also increased root nodules and root length slightly. RZ-21 also enhanced the activities of soil urease, sucrase and hydrogen peroxidase at various stages. In addition, RZ-21 and M treatments increased the average population of soil bacteria and decreased the average population of fungi in the three critical peanut growth stages, except for M in the case of the fungal population at flowering, thus balancing the structure of the soil microorganism community. This is the first report of S. marcescens being applied to continuously cropped peanut soil. The results suggest that S. marcescens RZ-21 has the potential to improve the soil environment and agricultural products and thus allow the development of sustainable management practices. © 2015 Society of Chemical Industry.

On Interestingness Measures for Mining Statistically Significant and Novel Clinical Associations from EMRs

PubMed Central

Abar, Orhan; Charnigo, Richard J.; Rayapati, Abner

2017-01-01

Association rule mining has received significant attention from both the data mining and machine learning communities. While data mining researchers focus more on designing efficient algorithms to mine rules from large datasets, the learning community has explored applications of rule mining to classification. A major problem with rule mining algorithms is the explosion of rules even for moderate sized datasets making it very difficult for end users to identify both statistically significant and potentially novel rules that could lead to interesting new insights and hypotheses. Researchers have proposed many domain independent interestingness measures using which, one can rank the rules and potentially glean useful rules from the top ranked ones. However, these measures have not been fully explored for rule mining in clinical datasets owing to the relatively large sizes of the datasets often encountered in healthcare and also due to limited access to domain experts for review/analysis. In this paper, using an electronic medical record (EMR) dataset of diagnoses and medications from over three million patient visits to the University of Kentucky medical center and affiliated clinics, we conduct a thorough evaluation of dozens of interestingness measures proposed in data mining literature, including some new composite measures. Using cumulative relevance metrics from information retrieval, we compare these interestingness measures against human judgments obtained from a practicing psychiatrist for association rules involving the depressive disorders class as the consequent. Our results not only surface new interesting associations for depressive disorders but also indicate classes of interestingness measures that weight rule novelty and statistical strength in contrasting ways, offering new insights for end users in identifying interesting rules. PMID:28736771

A randomized trial in a massive online open course shows people don't know what a statistically significant relationship looks like, but they can learn.

PubMed

Fisher, Aaron; Anderson, G Brooke; Peng, Roger; Leek, Jeff

2014-01-01

Scatterplots are the most common way for statisticians, scientists, and the public to visually detect relationships between measured variables. At the same time, and despite widely publicized controversy, P-values remain the most commonly used measure to statistically justify relationships identified between variables. Here we measure the ability to detect statistically significant relationships from scatterplots in a randomized trial of 2,039 students in a statistics massive open online course (MOOC). Each subject was shown a random set of scatterplots and asked to visually determine if the underlying relationships were statistically significant at the P < 0.05 level. Subjects correctly classified only 47.4% (95% CI [45.1%-49.7%]) of statistically significant relationships, and 74.6% (95% CI [72.5%-76.6%]) of non-significant relationships. Adding visual aids such as a best fit line or scatterplot smooth increased the probability a relationship was called significant, regardless of whether the relationship was actually significant. Classification of statistically significant relationships improved on repeat attempts of the survey, although classification of non-significant relationships did not. Our results suggest: (1) that evidence-based data analysis can be used to identify weaknesses in theoretical procedures in the hands of average users, (2) data analysts can be trained to improve detection of statistically significant results with practice, but (3) data analysts have incorrect intuition about what statistically significant relationships look like, particularly for small effects. We have built a web tool for people to compare scatterplots with their corresponding p-values which is available here: http://glimmer.rstudio.com/afisher/EDA/.

A randomized trial in a massive online open course shows people don’t know what a statistically significant relationship looks like, but they can learn

PubMed Central

Fisher, Aaron; Anderson, G. Brooke; Peng, Roger

2014-01-01

Scatterplots are the most common way for statisticians, scientists, and the public to visually detect relationships between measured variables. At the same time, and despite widely publicized controversy, P-values remain the most commonly used measure to statistically justify relationships identified between variables. Here we measure the ability to detect statistically significant relationships from scatterplots in a randomized trial of 2,039 students in a statistics massive open online course (MOOC). Each subject was shown a random set of scatterplots and asked to visually determine if the underlying relationships were statistically significant at the P < 0.05 level. Subjects correctly classified only 47.4% (95% CI [45.1%–49.7%]) of statistically significant relationships, and 74.6% (95% CI [72.5%–76.6%]) of non-significant relationships. Adding visual aids such as a best fit line or scatterplot smooth increased the probability a relationship was called significant, regardless of whether the relationship was actually significant. Classification of statistically significant relationships improved on repeat attempts of the survey, although classification of non-significant relationships did not. Our results suggest: (1) that evidence-based data analysis can be used to identify weaknesses in theoretical procedures in the hands of average users, (2) data analysts can be trained to improve detection of statistically significant results with practice, but (3) data analysts have incorrect intuition about what statistically significant relationships look like, particularly for small effects. We have built a web tool for people to compare scatterplots with their corresponding p-values which is available here: http://glimmer.rstudio.com/afisher/EDA/. PMID:25337457

Methods for estimating selected low-flow statistics and development of annual flow-duration statistics for Ohio

USGS Publications Warehouse

Koltun, G.F.; Kula, Stephanie P.

2013-01-01

This report presents the results of a study to develop methods for estimating selected low-flow statistics and for determining annual flow-duration statistics for Ohio streams. Regression techniques were used to develop equations for estimating 10-year recurrence-interval (10-percent annual-nonexceedance probability) low-flow yields, in cubic feet per second per square mile, with averaging periods of 1, 7, 30, and 90-day(s), and for estimating the yield corresponding to the long-term 80-percent duration flow. These equations, which estimate low-flow yields as a function of a streamflow-variability index, are based on previously published low-flow statistics for 79 long-term continuous-record streamgages with at least 10 years of data collected through water year 1997. When applied to the calibration dataset, average absolute percent errors for the regression equations ranged from 15.8 to 42.0 percent. The regression results have been incorporated into the U.S. Geological Survey (USGS) StreamStats application for Ohio (http://water.usgs.gov/osw/streamstats/ohio.html) in the form of a yield grid to facilitate estimation of the corresponding streamflow statistics in cubic feet per second. Logistic-regression equations also were developed and incorporated into the USGS StreamStats application for Ohio for selected low-flow statistics to help identify occurrences of zero-valued statistics. Quantiles of daily and 7-day mean streamflows were determined for annual and annual-seasonal (September–November) periods for each complete climatic year of streamflow-gaging station record for 110 selected streamflow-gaging stations with 20 or more years of record. The quantiles determined for each climatic year were the 99-, 98-, 95-, 90-, 80-, 75-, 70-, 60-, 50-, 40-, 30-, 25-, 20-, 10-, 5-, 2-, and 1-percent exceedance streamflows. Selected exceedance percentiles of the annual-exceedance percentiles were subsequently computed and tabulated to help facilitate consideration of the

An image based method for crop yield prediction using remotely sensed and crop canopy data: the case of Paphos district, western Cyprus

NASA Astrophysics Data System (ADS)

Papadavid, G.; Hadjimitsis, D.

2014-08-01

Remote sensing techniques development have provided the opportunity for optimizing yields in the agricultural procedure and moreover to predict the forthcoming yield. Yield prediction plays a vital role in Agricultural Policy and provides useful data to policy makers. In this context, crop and soil parameters along with NDVI index which are valuable sources of information have been elaborated statistically to test if a) Durum wheat yield can be predicted and b) when is the actual time-window to predict the yield in the district of Paphos, where Durum wheat is the basic cultivation and supports the rural economy of the area. 15 plots cultivated with Durum wheat from the Agricultural Research Institute of Cyprus for research purposes, in the area of interest, have been under observation for three years to derive the necessary data. Statistical and remote sensing techniques were then applied to derive and map a model that can predict yield of Durum wheat in this area. Indeed the semi-empirical model developed for this purpose, with very high correlation coefficient R2=0.886, has shown in practice that can predict yields very good. Students T test has revealed that predicted values and real values of yield have no statistically significant difference. The developed model can and will be further elaborated with more parameters and applied for other crops in the near future.

The Harm Done to Reproducibility by the Culture of Null Hypothesis Significance Testing.

PubMed

Lash, Timothy L

2017-09-15

In the last few years, stakeholders in the scientific community have raised alarms about a perceived lack of reproducibility of scientific results. In reaction, guidelines for journals have been promulgated and grant applicants have been asked to address the rigor and reproducibility of their proposed projects. Neither solution addresses a primary culprit, which is the culture of null hypothesis significance testing that dominates statistical analysis and inference. In an innovative research enterprise, selection of results for further evaluation based on null hypothesis significance testing is doomed to yield a low proportion of reproducible results and a high proportion of effects that are initially overestimated. In addition, the culture of null hypothesis significance testing discourages quantitative adjustments to account for systematic errors and quantitative incorporation of prior information. These strategies would otherwise improve reproducibility and have not been previously proposed in the widely cited literature on this topic. Without discarding the culture of null hypothesis significance testing and implementing these alternative methods for statistical analysis and inference, all other strategies for improving reproducibility will yield marginal gains at best. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Observation of B{sup +}{yields}{xi}{sub c}{sup 0}{lambda}{sub c}{sup +} and evidence for B{sup 0}{yields}{xi}{sub c}{sup -}{lambda}{sub c}{sup +}

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

Chistov, R.; Aushev, T.; Balagura, V.

We report the first observation of the decay B{sup +}{yields}{xi}{sub c}{sup 0}{lambda}{sub c}{sup +} with a significance of 8.7{sigma} and evidence for the decay B{sup 0}{yields}{xi}{sub c}{sup -}{lambda}{sub c}{sup +} with a significance of 3.8{sigma}. The product B(B{sup +}{yields}{xi}{sub c}{sup 0}{lambda}{sub c}{sup +})xB({xi}{sub c}{sup 0}{yields}{xi}{sup +}{pi}{sup -}) is measured to be (4.8{sub -0.9}{sup +1.0}{+-}1.1{+-}1.2)x10{sup -5}, and B(B{sup 0}{yields}{xi}{sub c}{sup -}{lambda}{sub c}{sup +})xB({xi}{sub c}{sup -}{yields}{xi}{sup +}{pi}{sup -}{pi}{sup -}) is measured to be (9.3{sub -2.8}{sup +3.7}{+-}1.9{+-}2.4)x10{sup -5}. The errors are statistical, systematic and the error of the {lambda}{sub c}{sup +}{yields}pK{sup -}{pi}{sup +} branching fraction, respectively. The decay B{sup +}{yields}{xi}{sub c}{sup 0}{lambda}{sub c}{supmore » +} is the first example of a two-body exclusive B{sup +} decay into two charmed baryons. The data used for this analysis was accumulated at the {upsilon}(4S) resonance, using the Belle detector at the e{sup +}e{sup -} asymmetric-energy collider KEKB. The integrated luminosity of the data sample is equal to 357 fb{sup -1}, corresponding to 386x10{sup 6} BB pairs.« less

Spatial variability effects on precision and power of forage yield estimation

USDA-ARS?s Scientific Manuscript database

Spatial analyses of yield trials are important, as they adjust cultivar means for spatial variation and improve the statistical precision of yield estimation. While the relative efficiency of spatial analysis has been frequently reported in several yield trials, its application on long-term forage y...

What's holding us back? Raising the alfalfa yield bar

USDA-ARS?s Scientific Manuscript database

Measuring yield of commodity crops is easy – weight and moisture content are determined on delivery. Consequently, reports of production or yield for grain crops can be made reliably to the agencies that track crop production, such as the USDA-National Agricultural Statistics Service (NASS). The s...

The alfalfa yield gap: A review of the evidence

USDA-ARS?s Scientific Manuscript database

Knowledge of feasibly attainable crop yields is needed for many purposes, from field-scale management to national policy decisions. For alfalfa (Medicago sativa L.), the most widely used estimates of yield in the US are whole-farm reports from the National Agriculture Statistics Service, which are b...

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data

PubMed Central

Kim, Sung-Min; Choi, Yosoon

2017-01-01

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z-score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z-scores: high content with a high z-score (HH), high content with a low z-score (HL), low content with a high z-score (LH), and low content with a low z-score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1–4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required. PMID:28629168

Assessing Statistically Significant Heavy-Metal Concentrations in Abandoned Mine Areas via Hot Spot Analysis of Portable XRF Data.

PubMed

Kim, Sung-Min; Choi, Yosoon

2017-06-18

To develop appropriate measures to prevent soil contamination in abandoned mining areas, an understanding of the spatial variation of the potentially toxic trace elements (PTEs) in the soil is necessary. For the purpose of effective soil sampling, this study uses hot spot analysis, which calculates a z -score based on the Getis-Ord Gi* statistic to identify a statistically significant hot spot sample. To constitute a statistically significant hot spot, a feature with a high value should also be surrounded by other features with high values. Using relatively cost- and time-effective portable X-ray fluorescence (PXRF) analysis, sufficient input data are acquired from the Busan abandoned mine and used for hot spot analysis. To calibrate the PXRF data, which have a relatively low accuracy, the PXRF analysis data are transformed using the inductively coupled plasma atomic emission spectrometry (ICP-AES) data. The transformed PXRF data of the Busan abandoned mine are classified into four groups according to their normalized content and z -scores: high content with a high z -score (HH), high content with a low z -score (HL), low content with a high z -score (LH), and low content with a low z -score (LL). The HL and LH cases may be due to measurement errors. Additional or complementary surveys are required for the areas surrounding these suspect samples or for significant hot spot areas. The soil sampling is conducted according to a four-phase procedure in which the hot spot analysis and proposed group classification method are employed to support the development of a sampling plan for the following phase. Overall, 30, 50, 80, and 100 samples are investigated and analyzed in phases 1-4, respectively. The method implemented in this case study may be utilized in the field for the assessment of statistically significant soil contamination and the identification of areas for which an additional survey is required.

Development of LACIE CCEA-1 weather/wheat yield models. [regression analysis

NASA Technical Reports Server (NTRS)

Strommen, N. D.; Sakamoto, C. M.; Leduc, S. K.; Umberger, D. E. (Principal Investigator)

1979-01-01

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

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

PubMed

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

2018-02-01

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

The role of baryons in creating statistically significant planes of satellites around Milky Way-mass galaxies

NASA Astrophysics Data System (ADS)

Ahmed, Sheehan H.; Brooks, Alyson M.; Christensen, Charlotte R.

2017-04-01

We investigate whether the inclusion of baryonic physics influences the formation of thin, coherently rotating planes of satellites such as those seen around the Milky Way and Andromeda. For four Milky Way-mass simulations, each run both as dark matter-only and with baryons included, we are able to identify a planar configuration that significantly maximizes the number of plane satellite members. The maximum plane member satellites are consistently different between the dark matter-only and baryonic versions of the same run due to the fact that satellites are both more likely to be destroyed and to infall later in the baryonic runs. Hence, studying satellite planes in dark matter-only simulations is misleading, because they will be composed of different satellite members than those that would exist if baryons were included. Additionally, the destruction of satellites in the baryonic runs leads to less radially concentrated satellite distributions, a result that is critical to making planes that are statistically significant compared to a random distribution. Since all planes pass through the centre of the galaxy, it is much harder to create a plane of a given height from a random distribution if the satellites have a low radial concentration. We identify Andromeda's low radial satellite concentration as a key reason why the plane in Andromeda is highly significant. Despite this, when corotation is considered, none of the satellite planes identified for the simulated galaxies are as statistically significant as the observed planes around the Milky Way and Andromeda, even in the baryonic runs.

Amplicon-based metagenomics identified candidate organisms in soils that caused yield decline in strawberry

PubMed Central

Xu, Xiangming; Passey, Thomas; Wei, Feng; Saville, Robert; Harrison, Richard J.

2015-01-01

A phenomenon of yield decline due to weak plant growth in strawberry was recently observed in non-chemo-fumigated soils, which was not associated with the soil fungal pathogen Verticillium dahliae, the main target of fumigation. Amplicon-based metagenomics was used to profile soil microbiota in order to identify microbial organisms that may have caused the yield decline. A total of 36 soil samples were obtained in 2013 and 2014 from four sites for metagenomic studies; two of the four sites had a yield-decline problem, the other two did not. More than 2000 fungal or bacterial operational taxonomy units (OTUs) were found in these samples. Relative abundance of individual OTUs was statistically compared for differences between samples from sites with or without yield decline. A total of 721 individual comparisons were statistically significant – involving 366 unique bacterial and 44 unique fungal OTUs. Based on further selection criteria, we focused on 34 bacterial and 17 fungal OTUs and found that yield decline resulted probably from one or more of the following four factors: (1) low abundance of Bacillus and Pseudomonas populations, which are well known for their ability of supressing pathogen development and/or promoting plant growth; (2) lack of the nematophagous fungus (Paecilomyces species); (3) a high level of two non-specific fungal root rot pathogens; and (4) wet soil conditions. This study demonstrated the usefulness of an amplicon-based metagenomics approach to profile soil microbiota and to detect differential abundance in microbes. PMID:26504572

Heterogeneous variances in multi-environment yield trials for corn hybrids

USDA-ARS?s Scientific Manuscript database

Recent developments in statistics and computing have enabled much greater levels of complexity in statistical models of multi-environment yield trial data. One particular feature of interest to breeders is simultaneously modeling heterogeneity of variances among environments and cultivars. Our obj...

The In Vitro Mass-Produced Model Mycorrhizal Fungus, Rhizophagus irregularis, Significantly Increases Yields of the Globally Important Food Security Crop Cassava

PubMed Central

Ceballos, Isabel; Ruiz, Michael; Fernández, Cristhian; Peña, Ricardo

2013-01-01

The arbuscular mycorrhizal symbiosis is formed between arbuscular mycorrhizal fungi (AMF) and plant roots. The fungi provide the plant with inorganic phosphate (P). The symbiosis can result in increased plant growth. Although most global food crops naturally form this symbiosis, very few studies have shown that their practical application can lead to large-scale increases in food production. Application of AMF to crops in the tropics is potentially effective for improving yields. However, a main problem of using AMF on a large-scale is producing cheap inoculum in a clean sterile carrier and sufficiently concentrated to cheaply transport. Recently, mass-produced in vitro inoculum of the model mycorrhizal fungus Rhizophagus irregularis became available, potentially making its use viable in tropical agriculture. One of the most globally important food plants in the tropics is cassava. We evaluated the effect of in vitro mass-produced R. irregularis inoculum on the yield of cassava crops at two locations in Colombia. A significant effect of R. irregularis inoculation on yield occurred at both sites. At one site, yield increases were observed irrespective of P fertilization. At the other site, inoculation with AMF and 50% of the normally applied P gave the highest yield. Despite that AMF inoculation resulted in greater food production, economic analyses revealed that AMF inoculation did not give greater return on investment than with conventional cultivation. However, the amount of AMF inoculum used was double the recommended dose and was calculated with European, not Colombian, inoculum prices. R. irregularis can also be manipulated genetically in vitro, leading to improved plant growth. We conclude that application of in vitro R. irregularis is currently a way of increasing cassava yields, that there is a strong potential for it to be economically profitable and that there is enormous potential to improve this efficiency further in the future. PMID:23950975

"Clinical" Significance: "Clinical" Significance and "Practical" Significance are NOT the Same Things

ERIC Educational Resources Information Center

Peterson, Lisa S.

2008-01-01

Clinical significance is an important concept in research, particularly in education and the social sciences. The present article first compares clinical significance to other measures of "significance" in statistics. The major methods used to determine clinical significance are explained and the strengths and weaknesses of clinical significance…

The distribution of P-values in medical research articles suggested selective reporting associated with statistical significance.

PubMed

Perneger, Thomas V; Combescure, Christophe

2017-07-01

Published P-values provide a window into the global enterprise of medical research. The aim of this study was to use the distribution of published P-values to estimate the relative frequencies of null and alternative hypotheses and to seek irregularities suggestive of publication bias. This cross-sectional study included P-values published in 120 medical research articles in 2016 (30 each from the BMJ, JAMA, Lancet, and New England Journal of Medicine). The observed distribution of P-values was compared with expected distributions under the null hypothesis (i.e., uniform between 0 and 1) and the alternative hypothesis (strictly decreasing from 0 to 1). P-values were categorized according to conventional levels of statistical significance and in one-percent intervals. Among 4,158 recorded P-values, 26.1% were highly significant (P < 0.001), 9.1% were moderately significant (P ≥ 0.001 to < 0.01), 11.7% were weakly significant (P ≥ 0.01 to < 0.05), and 53.2% were nonsignificant (P ≥ 0.05). We noted three irregularities: (1) high proportion of P-values <0.001, especially in observational studies, (2) excess of P-values equal to 1, and (3) about twice as many P-values less than 0.05 compared with those more than 0.05. The latter finding was seen in both randomized trials and observational studies, and in most types of analyses, excepting heterogeneity tests and interaction tests. Under plausible assumptions, we estimate that about half of the tested hypotheses were null and the other half were alternative. This analysis suggests that statistical tests published in medical journals are not a random sample of null and alternative hypotheses but that selective reporting is prevalent. In particular, significant results are about twice as likely to be reported as nonsignificant results. Copyright © 2017 Elsevier Inc. All rights reserved.

The thresholds for statistical and clinical significance – a five-step procedure for evaluation of intervention effects in randomised clinical trials

PubMed Central

2014-01-01

Background Thresholds for statistical significance are insufficiently demonstrated by 95% confidence intervals or P-values when assessing results from randomised clinical trials. First, a P-value only shows the probability of getting a result assuming that the null hypothesis is true and does not reflect the probability of getting a result assuming an alternative hypothesis to the null hypothesis is true. Second, a confidence interval or a P-value showing significance may be caused by multiplicity. Third, statistical significance does not necessarily result in clinical significance. Therefore, assessment of intervention effects in randomised clinical trials deserves more rigour in order to become more valid. Methods Several methodologies for assessing the statistical and clinical significance of intervention effects in randomised clinical trials were considered. Balancing simplicity and comprehensiveness, a simple five-step procedure was developed. Results For a more valid assessment of results from a randomised clinical trial we propose the following five-steps: (1) report the confidence intervals and the exact P-values; (2) report Bayes factor for the primary outcome, being the ratio of the probability that a given trial result is compatible with a ‘null’ effect (corresponding to the P-value) divided by the probability that the trial result is compatible with the intervention effect hypothesised in the sample size calculation; (3) adjust the confidence intervals and the statistical significance threshold if the trial is stopped early or if interim analyses have been conducted; (4) adjust the confidence intervals and the P-values for multiplicity due to number of outcome comparisons; and (5) assess clinical significance of the trial results. Conclusions If the proposed five-step procedure is followed, this may increase the validity of assessments of intervention effects in randomised clinical trials. PMID:24588900

Characterizing bias correction uncertainty in wheat yield predictions

NASA Astrophysics Data System (ADS)

Ortiz, Andrea Monica; Jones, Julie; Freckleton, Robert; Scaife, Adam

2017-04-01

Farming systems are under increased pressure due to current and future climate change, variability and extremes. Research on the impacts of climate change on crop production typically rely on the output of complex Global and Regional Climate Models, which are used as input to crop impact models. Yield predictions from these top-down approaches can have high uncertainty for several reasons, including diverse model construction and parameterization, future emissions scenarios, and inherent or response uncertainty. These uncertainties propagate down each step of the 'cascade of uncertainty' that flows from climate input to impact predictions, leading to yield predictions that may be too complex for their intended use in practical adaptation options. In addition to uncertainty from impact models, uncertainty can also stem from the intermediate steps that are used in impact studies to adjust climate model simulations to become more realistic when compared to observations, or to correct the spatial or temporal resolution of climate simulations, which are often not directly applicable as input into impact models. These important steps of bias correction or calibration also add uncertainty to final yield predictions, given the various approaches that exist to correct climate model simulations. In order to address how much uncertainty the choice of bias correction method can add to yield predictions, we use several evaluation runs from Regional Climate Models from the Coordinated Regional Downscaling Experiment over Europe (EURO-CORDEX) at different resolutions together with different bias correction methods (linear and variance scaling, power transformation, quantile-quantile mapping) as input to a statistical crop model for wheat, a staple European food crop. The objective of our work is to compare the resulting simulation-driven hindcasted wheat yields to climate observation-driven wheat yield hindcasts from the UK and Germany in order to determine ranges of yield

A Probabilistic Model of Local Sequence Alignment That Simplifies Statistical Significance Estimation

PubMed Central

Eddy, Sean R.

2008-01-01

Sequence database searches require accurate estimation of the statistical significance of scores. Optimal local sequence alignment scores follow Gumbel distributions, but determining an important parameter of the distribution (λ) requires time-consuming computational simulation. Moreover, optimal alignment scores are less powerful than probabilistic scores that integrate over alignment uncertainty (“Forward” scores), but the expected distribution of Forward scores remains unknown. Here, I conjecture that both expected score distributions have simple, predictable forms when full probabilistic modeling methods are used. For a probabilistic model of local sequence alignment, optimal alignment bit scores (“Viterbi” scores) are Gumbel-distributed with constant λ = log 2, and the high scoring tail of Forward scores is exponential with the same constant λ. Simulation studies support these conjectures over a wide range of profile/sequence comparisons, using 9,318 profile-hidden Markov models from the Pfam database. This enables efficient and accurate determination of expectation values (E-values) for both Viterbi and Forward scores for probabilistic local alignments. PMID:18516236

Effects of starter nitrogen fertilizer on soybean root activity, leaf photosynthesis and grain yield

PubMed Central

Gai, Zhijia; Zhang, Jingtao; Li, Caifeng

2017-01-01

The objective of this study was to examine the impact of starter nitrogen fertilizer on soybean root activity, leaf photosynthesis, grain yield and their relationship. To achieve this objective, field experiments were conducted in 2013 and 2014, using a randomized complete block design, with three replications. Nitrogen was applied at planting at rates of 0, 25, 50, and 75 kg N ha-1. In both years, starter nitrogen fertilizer benefited root activity, leaf photosynthesis, and consequently its yield. Statistically significant correlation was found among root activity, leaf photosynthetic rate, and grain yield at the developmental stage. The application of N25, N50, and N75 increased grain yield by 1.28%, 2.47%, and 1.58% in 2013 and by 0.62%, 2.77%, and 2.06% in 2014 compared to the N0 treatment. Maximum grain yield of 3238.91 kg ha-1 in 2013 and 3086.87 kg ha-1 in 2014 were recorded for N50 treatment. Grain yield was greater for 2013 than 2014, possibly due to more favorable environmental conditions. This research indicated that applying nitrogen as starter is necessary to increase soybean yield in Sangjiang River Plain in China. PMID:28388620

Conducting tests for statistically significant differences using forest inventory data

Treesearch

James A. Westfall; Scott A. Pugh; John W. Coulston

2013-01-01

Many forest inventory and monitoring programs are based on a sample of ground plots from which estimates of forest resources are derived. In addition to evaluating metrics such as number of trees or amount of cubic wood volume, it is often desirable to make comparisons between resource attributes. To properly conduct statistical tests for differences, it is imperative...

Plausible rice yield losses under future climate warming.

PubMed

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Huang, Yao; Ciais, Philippe; Elliott, Joshua; Huang, Mengtian; Janssens, Ivan A; Li, Tao; Lian, Xu; Liu, Yongwen; Müller, Christoph; Peng, Shushi; Wang, Tao; Zeng, Zhenzhong; Peñuelas, Josep

2016-12-19

Rice is the staple food for more than 50% of the world's population 1-3 . Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of -5.2 ± 1.4% K -1 . Local crop models give a similar sensitivity (-6.3 ± 0.4% K -1 ), but statistical and global gridded crop models both suggest less negative impacts of warming on yields (-0.8 ± 0.3% and -2.4 ± 3.7% K -1 , respectively). Using data from field warming experiments, we further propose a conditional probability approach to constrain the large range of global gridded crop model results for the future yield changes in response to warming by the end of the century (from -1.3% to -9.3% K -1 ). The constraint implies a more negative response to warming (-8.3 ± 1.4% K -1 ) and reduces the spread of the model ensemble by 33%. This yield reduction exceeds that estimated by the International Food Policy Research Institute assessment (-4.2 to -6.4% K -1 ) (ref. 4). Our study suggests that without CO 2 fertilization, effective adaptation and genetic improvement, severe rice yield losses are plausible under intensive climate warming scenarios.

Evaluation of Solid Rocket Motor Component Data Using a Commercially Available Statistical Software Package

NASA Technical Reports Server (NTRS)

Stefanski, Philip L.

2015-01-01

Commercially available software packages today allow users to quickly perform the routine evaluations of (1) descriptive statistics to numerically and graphically summarize both sample and population data, (2) inferential statistics that draws conclusions about a given population from samples taken of it, (3) probability determinations that can be used to generate estimates of reliability allowables, and finally (4) the setup of designed experiments and analysis of their data to identify significant material and process characteristics for application in both product manufacturing and performance enhancement. This paper presents examples of analysis and experimental design work that has been conducted using Statgraphics®(Registered Trademark) statistical software to obtain useful information with regard to solid rocket motor propellants and internal insulation material. Data were obtained from a number of programs (Shuttle, Constellation, and Space Launch System) and sources that include solid propellant burn rate strands, tensile specimens, sub-scale test motors, full-scale operational motors, rubber insulation specimens, and sub-scale rubber insulation analog samples. Besides facilitating the experimental design process to yield meaningful results, statistical software has demonstrated its ability to quickly perform complex data analyses and yield significant findings that might otherwise have gone unnoticed. One caveat to these successes is that useful results not only derive from the inherent power of the software package, but also from the skill and understanding of the data analyst.

A statistical approach to instrument calibration

Treesearch

Robert R. Ziemer; David Strauss

1978-01-01

Summary - It has been found that two instruments will yield different numerical values when used to measure identical points. A statistical approach is presented that can be used to approximate the error associated with the calibration of instruments. Included are standard statistical tests that can be used to determine if a number of successive calibrations of the...

Statistical significance of seasonal warming/cooling trends

NASA Astrophysics Data System (ADS)

Ludescher, Josef; Bunde, Armin; Schellnhuber, Hans Joachim

2017-04-01

The question whether a seasonal climate trend (e.g., the increase of summer temperatures in Antarctica in the last decades) is of anthropogenic or natural origin is of great importance for mitigation and adaption measures alike. The conventional significance analysis assumes that (i) the seasonal climate trends can be quantified by linear regression, (ii) the different seasonal records can be treated as independent records, and (iii) the persistence in each of these seasonal records can be characterized by short-term memory described by an autoregressive process of first order. Here we show that assumption ii is not valid, due to strong intraannual correlations by which different seasons are correlated. We also show that, even in the absence of correlations, for Gaussian white noise, the conventional analysis leads to a strong overestimation of the significance of the seasonal trends, because multiple testing has not been taken into account. In addition, when the data exhibit long-term memory (which is the case in most climate records), assumption iii leads to a further overestimation of the trend significance. Combining Monte Carlo simulations with the Holm-Bonferroni method, we demonstrate how to obtain reliable estimates of the significance of the seasonal climate trends in long-term correlated records. For an illustration, we apply our method to representative temperature records from West Antarctica, which is one of the fastest-warming places on Earth and belongs to the crucial tipping elements in the Earth system.

What Your Yield Says about You

ERIC Educational Resources Information Center

Hoover, Eric

2009-01-01

The recession has turned Americans into numbers addicts. Seemingly endless supplies of statistics--stock prices, retail sales, and the gross domestic product--offer various views about the health of the nation's economy. Higher education has its own economic indicators. Among the most important is "yield," the percentage of admitted students who…

A Remote Sensing-Derived Corn Yield Assessment Model

NASA Astrophysics Data System (ADS)

Shrestha, Ranjay Man

Agricultural studies and food security have become critical research topics due to continuous growth in human population and simultaneous shrinkage in agricultural land. In spite of modern technological advancements to improve agricultural productivity, more studies on crop yield assessments and food productivities are still necessary to fulfill the constantly increasing food demands. Besides human activities, natural disasters such as flood and drought, along with rapid climate changes, also inflect an adverse effect on food productivities. Understanding the impact of these disasters on crop yield and making early impact estimations could help planning for any national or international food crisis. Similarly, the United States Department of Agriculture (USDA) Risk Management Agency (RMA) insurance management utilizes appropriately estimated crop yield and damage assessment information to sustain farmers' practice through timely and proper compensations. Through County Agricultural Production Survey (CAPS), the USDA National Agricultural Statistical Service (NASS) uses traditional methods of field interviews and farmer-reported survey data to perform annual crop condition monitoring and production estimations at the regional and state levels. As these manual approaches of yield estimations are highly inefficient and produce very limited samples to represent the entire area, NASS requires supplemental spatial data that provides continuous and timely information on crop production and annual yield. Compared to traditional methods, remote sensing data and products offer wider spatial extent, more accurate location information, higher temporal resolution and data distribution, and lower data cost--thus providing a complementary option for estimation of crop yield information. Remote sensing derived vegetation indices such as Normalized Difference Vegetation Index (NDVI) provide measurable statistics of potential crop growth based on the spectral reflectance and could

Performance of cancer cluster Q-statistics for case-control residential histories

PubMed Central

Sloan, Chantel D.; Jacquez, Geoffrey M.; Gallagher, Carolyn M.; Ward, Mary H.; Raaschou-Nielsen, Ole; Nordsborg, Rikke Baastrup; Meliker, Jaymie R.

2012-01-01

Few investigations of health event clustering have evaluated residential mobility, though causative exposures for chronic diseases such as cancer often occur long before diagnosis. Recently developed Q-statistics incorporate human mobility into disease cluster investigations by quantifying space- and time-dependent nearest neighbor relationships. Using residential histories from two cancer case-control studies, we created simulated clusters to examine Q-statistic performance. Results suggest the intersection of cases with significant clustering over their life course, Qi, with cases who are constituents of significant local clusters at given times, Qit, yielded the best performance, which improved with increasing cluster size. Upon comparison, a larger proportion of true positives were detected with Kulldorf’s spatial scan method if the time of clustering was provided. We recommend using Q-statistics to identify when and where clustering may have occurred, followed by the scan method to localize the candidate clusters. Future work should investigate the generalizability of these findings. PMID:23149326

A Network-Based Method to Assess the Statistical Significance of Mild Co-Regulation Effects

PubMed Central

Horvát, Emőke-Ágnes; Zhang, Jitao David; Uhlmann, Stefan; Sahin, Özgür; Zweig, Katharina Anna

2013-01-01

Recent development of high-throughput, multiplexing technology has initiated projects that systematically investigate interactions between two types of components in biological networks, for instance transcription factors and promoter sequences, or microRNAs (miRNAs) and mRNAs. In terms of network biology, such screening approaches primarily attempt to elucidate relations between biological components of two distinct types, which can be represented as edges between nodes in a bipartite graph. However, it is often desirable not only to determine regulatory relationships between nodes of different types, but also to understand the connection patterns of nodes of the same type. Especially interesting is the co-occurrence of two nodes of the same type, i.e., the number of their common neighbours, which current high-throughput screening analysis fails to address. The co-occurrence gives the number of circumstances under which both of the biological components are influenced in the same way. Here we present SICORE, a novel network-based method to detect pairs of nodes with a statistically significant co-occurrence. We first show the stability of the proposed method on artificial data sets: when randomly adding and deleting observations we obtain reliable results even with noise exceeding the expected level in large-scale experiments. Subsequently, we illustrate the viability of the method based on the analysis of a proteomic screening data set to reveal regulatory patterns of human microRNAs targeting proteins in the EGFR-driven cell cycle signalling system. Since statistically significant co-occurrence may indicate functional synergy and the mechanisms underlying canalization, and thus hold promise in drug target identification and therapeutic development, we provide a platform-independent implementation of SICORE with a graphical user interface as a novel tool in the arsenal of high-throughput screening analysis. PMID:24039936

Estimating agricultural yield gap in Africa using MODIS NDVI dataset

NASA Astrophysics Data System (ADS)

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.

Incremental yield of dysplasia detection in Barrett's esophagus using volumetric laser endomicroscopy with and without laser marking compared with a standardized random biopsy protocol.

PubMed

Alshelleh, Mohammad; Inamdar, Sumant; McKinley, Matthew; Stewart, Molly; Novak, Jeffrey S; Greenberg, Ronald E; Sultan, Keith; Devito, Bethany; Cheung, Mary; Cerulli, Maurice A; Miller, Larry S; Sejpal, Divyesh V; Vegesna, Anil K; Trindade, Arvind J

2018-02-02

Volumetric laser endomicroscopy (VLE) is a new wide-field advanced imaging technology for Barrett's esophagus (BE). No data exist on incremental yield of dysplasia detection. Our aim is to report the incremental yield of dysplasia detection in BE using VLE. This is a retrospective study from a prospectively maintained database from 2011 to 2017 comparing the dysplasia yield of 4 different surveillance strategies in an academic BE tertiary care referral center. The groups were (1) random biopsies (RB), (2) Seattle protocol random biopsies (SP), (3) VLE without laser marking (VLE), and (4) VLE with laser marking (VLEL). A total of 448 consecutive patients (79 RB, 95 SP, 168 VLE, and 106 VLEL) met the inclusion criteria. After adjusting for visible lesions, the total dysplasia yield was 5.7%, 19.6%, 24.8%, and 33.7%, respectively. When compared with just the SP group, the VLEL group had statistically higher rates of overall dysplasia yield (19.6% vs 33.7%, P = .03; odds ratio, 2.1, P = .03). Both the VLEL and VLE groups had statistically significant differences in neoplasia (high-grade dysplasia and intramucosal cancer) detection compared with the SP group (14% vs 1%, P = .001 and 11% vs 1%, P = .003). A surveillance strategy involving VLEL led to a statistically significant higher yield of dysplasia and neoplasia detection compared with a standard random biopsy protocol. These results support the use of VLEL for surveillance in BE in academic centers. Copyright © 2018 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

Statistical modeling of yield and variance instability in conventional and organic cropping systems

USDA-ARS?s Scientific Manuscript database

Cropping systems research was undertaken to address declining crop diversity and verify competitiveness of alternatives to the predominant conventional cropping system in the northern Corn Belt. To understand and capitalize on temporal yield variability within corn and soybean fields, we quantified ...

Synthetic velocity gradient tensors and the identification of statistically significant aspects of the structure of turbulence

NASA Astrophysics Data System (ADS)

Keylock, Christopher J.

2017-08-01

A method is presented for deriving random velocity gradient tensors given a source tensor. These synthetic tensors are constrained to lie within mathematical bounds of the non-normality of the source tensor, but we do not impose direct constraints upon scalar quantities typically derived from the velocity gradient tensor and studied in fluid mechanics. Hence, it becomes possible to ask hypotheses of data at a point regarding the statistical significance of these scalar quantities. Having presented our method and the associated mathematical concepts, we apply it to homogeneous, isotropic turbulence to test the utility of the approach for a case where the behavior of the tensor is understood well. We show that, as well as the concentration of data along the Vieillefosse tail, actual turbulence is also preferentially located in the quadrant where there is both excess enstrophy (Q>0 ) and excess enstrophy production (R<0 ). We also examine the topology implied by the strain eigenvalues and find that for the statistically significant results there is a particularly strong relative preference for the formation of disklike structures in the (Q<0 ,R<0 ) quadrant. With the method shown to be useful for a turbulence that is already understood well, it should be of even greater utility for studying complex flows seen in industry and the environment.

Delayed Carcass Deboning Results in Significantly Reduced Cook Yields of Boneless Skinless Chicken Thighs

USDA-ARS?s Scientific Manuscript database

Boneless skinless chicken thighs are a new deboned poultry product in the retail market. Three trials were conducted to investigate the effect of postmortem carcass deboning time on the cook yields of boneless skinless chicken thighs as well as boneless skinless chicken breasts. Broiler carcasses ...

Correlations between the modelled potato crop yield and the general atmospheric circulation

NASA Astrophysics Data System (ADS)

Sepp, Mait; Saue, Triin

2012-07-01

Biology-related indicators do not usually depend on just one meteorological element but on a combination of several weather indicators. One way to establish such integral indicators is to classify the general atmospheric circulation into a small number of circulation types. The aim of present study is to analyse connections between general atmospheric circulation and potato crop yield in Estonia. Meteorologically possible yield (MPY), calculated by the model POMOD, is used to characterise potato crop yield. Data of three meteorological stations and the biological parameters of two potato sorts were applied to the model, and 73 different classifications of atmospheric circulation from catalogue 1.2 of COST 733, domain 05 are used to qualify circulation conditions. Correlation analysis showed that there is at least one circulation type in each of the classifications with at least one statistically significant (99%) correlation with potato crop yield, whether in Kuressaare, Tallinn or Tartu. However, no classifications with circulation types correlating with MPY in all three stations at the same time were revealed. Circulation types inducing a decrease in the potato crop yield are more clearly represented. Clear differences occurred between the observed geographical locations as well as between the seasons: derived from the number of significant circulation types, summer and Kuressaare stand out. Of potato varieties, late 'Anti' is more influenced by circulation. Analysis of MSLP maps of circulation types revealed that the seaside stations (Tallinn, Kuressaare) suffer from negative effects of anti-cyclonic conditions (drought), while Tartu suffers from the cyclonic activity (excessive water).

Statistical optimization for enhanced yields of probiotic Bacillus coagulans and its phage resistant mutants followed by kinetic modelling of the process.

PubMed

Pandey, Kavita R; Joshi, Chetan; Vakil, Babu V

2016-01-01

Probiotics are microorganisms which when administered in adequate amounts confer health benefits to the host. A leading pharmaceutical company producing Bacillus coagulans as a probiotic was facing the problem of recurring phage attacks. Two mutants viz. B. co PIII and B. co MIII that were isolated as phage resistant mutants after UV irradiation and MMS treatment of phage sensitive B. coagulans parental culture were characterized at functional and molecular level and were noted to have undergone interesting genetic changes. The non-specific genetic alterations induced by mutagenesis can also lead to alterations in cell performance. Hence, in the current study the parental strain and the two mutants were selected for shake flask optimization. Plackett-Burman design was used to select the significant culture variables affecting biomass production. Evolutionary operation method was applied for further optimization. The study showed wide variations in the nutritional requirements of phage resistant mutants, post exposure to mutagens. An increment of 150, 134 and 152 % was observed in the biomass productions of B. coagulans (parental type) and mutants B.co PIII and B.co MIII respectively, compared to the yield from one-factor-at-a-time technique. Using Logistic and modified Leudeking-Piret equations, biomass accumulation and substrate utilization efficiency of the bioprocess were determined. The experimental data was in agreement with the results predicted by statistical analysis and modelling. The developed model may be useful for controlling the growth and substrate consumption kinetics in large scale fermentation using B. coagulans .

Significantly improving the yield of recombinant proteins in Bacillus subtilis by a novel powerful mutagenesis tool (ARTP): Alkaline α-amylase as a case study.

PubMed

Ma, Yingfang; Yang, Haiquan; Chen, Xianzhong; Sun, Bo; Du, Guocheng; Zhou, Zhemin; Song, Jiangning; Fan, You; Shen, Wei

2015-10-01

In this study, atmospheric and room temperature plasma (ARTP), a promising mutation breeding technique, was successfully applied to generate Bacillus subtilis mutants that yielded large quantities of recombinant protein. The high throughput screening platform was implemented to select those mutants with the highest yield of recombinant alkaline α-amylase (AMY), including the preferred mutant B. subtilis WB600 mut-12#. The yield and productivity of recombinant AMY in B. subtilis WB600 mut-12# increased 35.0% and 8.8%, respectively, the extracellular protein concentration of which increased 37.9%. B. subtilis WB600 mut-12# exhibited good genetic stability. Cells from B. subtilis WB600 mut-12# became shorter and wider than those from the wild-type. This study is the first to report a novel powerful mutagenesis tool (ARTP) that significantly improves the yield of recombinant proteins in B. subtilis and may therefore play an important role in the high expression level of proteins in recombinant microbial hosts. Copyright © 2015 Elsevier Inc. All rights reserved.

Statistical Significance of Periodicity and Log-Periodicity with Heavy-Tailed Correlated Noise

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Sornette, Didier

We estimate the probability that random noise, of several plausible standard distributions, creates a false alarm that a periodicity (or log-periodicity) is found in a time series. The solution of this problem is already known for independent Gaussian distributed noise. We investigate more general situations with non-Gaussian correlated noises and present synthetic tests on the detectability and statistical significance of periodic components. A periodic component of a time series is usually detected by some sort of Fourier analysis. Here, we use the Lomb periodogram analysis, which is suitable and outperforms Fourier transforms for unevenly sampled time series. We examine the false-alarm probability of the largest spectral peak of the Lomb periodogram in the presence of power-law distributed noises, of short-range and of long-range fractional-Gaussian noises. Increasing heavy-tailness (respectively correlations describing persistence) tends to decrease (respectively increase) the false-alarm probability of finding a large spurious Lomb peak. Increasing anti-persistence tends to decrease the false-alarm probability. We also study the interplay between heavy-tailness and long-range correlations. In order to fully determine if a Lomb peak signals a genuine rather than a spurious periodicity, one should in principle characterize the Lomb peak height, its width and its relations to other peaks in the complete spectrum. As a step towards this full characterization, we construct the joint-distribution of the frequency position (relative to other peaks) and of the height of the highest peak of the power spectrum. We also provide the distributions of the ratio of the highest Lomb peak to the second highest one. Using the insight obtained by the present statistical study, we re-examine previously reported claims of ``log-periodicity'' and find that the credibility for log-periodicity in 2D-freely decaying turbulence is weakened while it is strengthened for fracture, for the

Low Carbon Rice Farming Practices in the Mekong Delta Yield Significantly Higher Profits and Lower Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Rudek, J.; Van Sanh, N.; Tinh, T. K.; Tin, H. Q.; Thu Ha, T.; Pha, D. N.; Cui, T. Q.; Tin, N. H.; Son, N. N.; Thanh, H. H.; Kien, H. T.; Kritee, K.; Ahuja, R.

2014-12-01

The Vietnam Low-Carbon Rice Project (VLCRP) seeks to significantly reduce GHG emissions from rice cultivation, an activity responsible for more than 30% of Vietnam's overall GHG emissions, while improving livelihoods for the rice farmer community by decreasing costs and enhancing yield as well as providing supplemental farmer income through the sale of carbon credits. The Mekong Delta makes up 12% of Vietnam's land area, but produces more than 50% of the country's rice, including more than 90% of the rice for export. Rice cultivation is the main source of income for 80% of farmers in the Mekong Delta. VLCRP was launched in late 2012 in the Mekong Delta in two major rice production provinces, Kien Giang and An Giang. To date, VLCRP has completed 11 crop seasons (in Kien Giang and An Giang combined), training over 400 farmer households in applying VLCRP's package of practices (known as 1 Must - 6 Reductions) and building technical capacity to its key stakeholders and rice farmer community leaders. By adopting the 1 Must- 6 Reductions practices (including reduced seeding density, reduced fertilizer and pesticide application, and alternative wetting and drying water management), rice farmers reduce their input costs while maintaining or improving yields, and decreasing greenhouse gas emissions. The VLCRP package of practices also deliver other environmental and social co-benefits, such as reduced water pollution, improved habitat for fishery resources and reduced health risks for farmers through the reduction of agri-chemicals. VLCRP farmers use significantly less inputs (50% reduction in seed, 30% reduction in fertilizer, 40-50% reduction in water) while improving yields 5-10%, leading to an increase in profit from 10% to as high as 60% per hectare. Preliminary results indicate that the 1 Must- 6 Reductions practices have led to approximately 40-65% reductions in greenhouse gas emissions, equivalent to 4 tons of CO2e/ha/yr in An Giang and 35 tons of CO2e/ha/yr in Kien

Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?

NASA Astrophysics Data System (ADS)

Vu, Minh Tue; Aribarg, Thannob; Supratid, Siriporn; Raghavan, Srivatsan V.; Liong, Shie-Yui

2016-11-01

Artificial neural network (ANN) is an established technique with a flexible mathematical structure that is capable of identifying complex nonlinear relationships between input and output data. The present study utilizes ANN as a method of statistically downscaling global climate models (GCMs) during the rainy season at meteorological site locations in Bangkok, Thailand. The study illustrates the applications of the feed forward back propagation using large-scale predictor variables derived from both the ERA-Interim reanalyses data and present day/future GCM data. The predictors are first selected over different grid boxes surrounding Bangkok region and then screened by using principal component analysis (PCA) to filter the best correlated predictors for ANN training. The reanalyses downscaled results of the present day climate show good agreement against station precipitation with a correlation coefficient of 0.8 and a Nash-Sutcliffe efficiency of 0.65. The final downscaled results for four GCMs show an increasing trend of precipitation for rainy season over Bangkok by the end of the twenty-first century. The extreme values of precipitation determined using statistical indices show strong increases of wetness. These findings will be useful for policy makers in pondering adaptation measures due to flooding such as whether the current drainage network system is sufficient to meet the changing climate and to plan for a range of related adaptation/mitigation measures.

The Z {yields} cc-bar {yields} {gamma}{gamma}*, Z {yields} bb-bar {yields} {gamma}{gamma}* triangle diagrams and the Z {yields} {gamma}{psi}, Z {yields} {gamma}Y decays

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

Achasov, N. N., E-mail: achasov@math.nsc.ru

2011-03-15

The approach to the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decay study is presented in detail, based on the sum rules for the Z {yields} cc-bar {yields} {gamma}{gamma}* and Z {yields} bb-bar {yields} {gamma}{gamma}* amplitudes and their derivatives. The branching ratios of the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decays are calculated for different hypotheses on saturation of the sum rules. The lower bounds of {Sigma}{sub {psi}} BR(Z {yields} {gamma}{psi}) = 1.95 Multiplication-Sign 10{sup -7} and {Sigma}{sub {upsilon}} BR(Z {yields} {gamma}Y) = 7.23 Multiplication-Sign 10{sup -7} are found. Deviations from the lower bounds are discussed, including the possibilitymore » of BR(Z {yields} {gamma}J/{psi}(1S)) {approx} BR(Z {yields} {gamma}Y(1S)) {approx} 10{sup -6}, that could be probably measured in LHC. The angular distributions in the Z {yields} {gamma}{psi} and Z {yields} {gamma}Y decays are also calculated.« less

Application of Bioorganic Fertilizer Significantly Increased Apple Yields and Shaped Bacterial Community Structure in Orchard Soil.

PubMed

Wang, Lei; Li, Jing; Yang, Fang; E, Yaoyao; Raza, Waseem; Huang, Qiwei; Shen, Qirong

2017-02-01

and Rhodospirillaceae, were found to be the significantly increased by the BOF addition and the genus Lysobacter may identify members of this group effective in biological control-based plant disease management and the members of family Rhodospirillaceae had an important role in fixing molecular nitrogen. These results strengthen the understanding of responses to the BOF and possible interactions within bacterial communities in soil that can be associated with disease suppression and the accumulation of carbon and nitrogen. The increase of apple yields after the application of BOF might be attributed to the fact that the application of BOF increased SOM, and soil total nitrogen, and changed the bacterial community by enriching Rhodospirillaceae, Alphaprotreobateria, and Proteobacteria.

Methane yield in source-sorted organic fraction of municipal solid waste.

PubMed

Davidsson, Asa; Gruvberger, Christopher; Christensen, Thomas H; Hansen, Trine Lund; Jansen, Jes la Cour

2007-01-01

Treating the source-separated organic fraction of municipal solid waste (SS-OFMSW) by anaerobic digestion is considered by many municipalities in Europe as an environmentally friendly means of treating organic waste and simultaneously producing methane gas. Methane yield can be used as a parameter for evaluation of the many different systems that exist for sorting and pre-treating waste. Methane yield from the thermophilic pilot scale digestion of 17 types of domestically SS-OFMSW originating from seven full-scale sorting systems was found. The samples were collected during 1 year using worked-out procedures tested statistically to ensure representative samples. Each waste type was identified by its origin and by pre-sorting, collection and pre-treatment methods. In addition to the pilot scale digestion, all samples were examined by chemical analyses and methane potential measurements. A VS-degradation rate of around 80% and a methane yield of 300-400Nm(3) CH(4)/ton VS(in) were achieved with a retention time of 15 days, corresponding to approximately 70% of the methane potential. The different waste samples gave minor variation in chemical composition and thus also in methane yield and methane potential. This indicates that sorting and collection systems in the present study do not significantly affect the amount of methane produced per VS treated.

On the statistical significance of excess events: Remarks of caution and the need for a standard method of calculation

NASA Technical Reports Server (NTRS)

Staubert, R.

1985-01-01

Methods for calculating the statistical significance of excess events and the interpretation of the formally derived values are discussed. It is argued that a simple formula for a conservative estimate should generally be used in order to provide a common understanding of quoted values.

Relationship between mozzarella yield and milk composition, processing factors, and recovery of whey constituents.

PubMed

Sales, D C; Rangel, A H N; Urbano, S A; Freitas, Alfredo R; Tonhati, Humberto; Novaes, L P; Pereira, M I B; Borba, L H F

2017-06-01

Our aim was to identify the relationship between mozzarella cheese yield and buffalo milk composition, processing factors, and recovery of whey constituents. A production of 30 batches of mozzarella cheese at a dairy industry in northeast Brazil (Rio Grande do Norte) was monitored between March and November 2015. Mozzarella yield and 32 other variables were observed for each batch, and divided into 3 groups: milk composition variables (12); variables involved in the cheesemaking process (14); and variables for recovery of whey constituents (6). Data were analyzed using descriptive statistics, Pearson correlation, and principal component analysis. Most of the correlations between milk composition variables and between the variables of the manufacturing processes were not significant. Significant correlations were mostly observed between variables for recovery of whey constituents. Yield only showed significant correlation with time elapsed between curd cuttings and age of the starter culture, and it showed greater association with age of the starter culture, time elapsed between curd cuttings, and during stretching, as well as with milk pH and density. Thus, processing factors and milk characteristics are closely related to dairy efficiency in mozzarella manufacturing. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Improving biogas quality and methane yield via co-digestion of agricultural and urban biomass wastes.

PubMed

Poulsen, Tjalfe G; Adelard, Laetitia

2016-08-01

Impact of co-digestion versus mono-digestion on biogas and CH4 yield for a set of five biomass materials (vegetable food waste, cow dung, pig manure, grass clippings, and chicken manure) was investigated considering 95 different biomass mixes of the five materials under thermophilic conditions in bench-scale batch experiments over a period of 65days. Average biogas and CH4 yields were significantly higher during co-digestion than during mono-digestion of the same materials. This improvement was most significant for co-digestion experiments involving three biomass types, although it was independent of the specific biomasses being co-digested. Improvement in CH4 production was further more prominent early in the digestion process during co-digestion compared to mono-digestion. Co-digestion also appeared to increase the ultimate CH4/CO2 ratio of the gas produced compared to mono-digestion although this tendency was relatively weak and not statistically significant. Copyright © 2016 Elsevier Ltd. All rights reserved.

Statistically Valid Planting Trials

Treesearch

C. B. Briscoe

1961-01-01

More than 100 million tree seedlings are planted each year in Latin America, and at least ten time'that many should be planted Rational control and development of a program of such magnitude require establishing and interpreting carefully planned trial plantings which will yield statistically valid answers to real and important questions. Unfortunately, many...

On the significance of δ13C correlations in ancient sediments

NASA Astrophysics Data System (ADS)

Derry, Louis A.

2010-08-01

A graphical analysis of the correlations between δc and ɛTOC was introduced by Rothman et al. (2003) to obtain estimates of the carbon isotopic composition of inputs to the oceans and the organic carbon burial fraction. Applied to Cenozoic data, the method agrees with independent estimates, but with Neoproterozoic data the method yields results that cannot be accommodated with standard models of sedimentary carbon isotope mass balance. We explore the sensitivity of the graphical correlation method and find that the variance ratio between δc and δo is an important control on the correlation of δc and ɛ. If the variance ratio σc/ σo ≥ 1 highly correlated arrays very similar to those obtained from the data are produced from independent random variables. The Neoproterozoic data shows such variance patterns, and the regression parameters for the Neoproterozoic data are statistically indistinguishable from the randomized model at the 95% confidence interval. The projection of the data into δc- ɛ space cannot distinguish between signal and noise, such as post-depositional alteration, under these circumstances. There appears to be no need to invoke unusual carbon cycle dynamics to explain the Neoproterozoic δc- ɛ array. The Cenozoic data have σc/ σo < 1 and the δc vs. ɛ correlation is probably geologically significant, but the analyzed sample size is too small to yield statistically significant results.

Potential impacts of agricultural drought on crop yield variability under a changing climate in Texas

NASA Astrophysics Data System (ADS)

Lee, K.; Leng, G.; Huang, M.; Sheffield, J.; Zhao, G.; Gao, H.

2017-12-01

Texas has the largest farm area in the U.S, and its revenue from crop production ranks third overall. With the changing climate, hydrological extremes such as droughts are becoming more frequent and intensified, causing significant yield reduction in rainfed agricultural systems. The objective of this study is to investigate the potential impacts of agricultural drought on crop yields (corn, sorghum, and wheat) under a changing climate in Texas. The Variable Infiltration Capacity (VIC) model, which is calibrated and validated over 10 major Texas river basins during the historical period, is employed in this study.The model is forced by a set of statistically downscaled climate projections from Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensembles at a spatial resolution of 1/8°. The CMIP5 projections contain four Representative Concentration Pathways (RCP) that represent different greenhouse gas concentration (4.5 and 8.5 w/m2 are selected in this study). To carry out the analysis, VIC simulations from 1950 to 2099 are first analyzed to investigate how the frequency and severity of agricultural droughts will be altered in Texas (under a changing climate). Second, future crop yields are projected using a statistical crop model. Third, the effects of agricultural drought on crop yields are quantitatively analyzed. The results are expected to contribute to future water resources planning, with a goal of mitigating the negative impacts of future droughts on agricultural production in Texas.

Self-assessed performance improves statistical fusion of image labels

PubMed Central

Bryan, Frederick W.; Xu, Zhoubing; Asman, Andrew J.; Allen, Wade M.; Reich, Daniel S.; Landman, Bennett A.

2014-01-01

. Statistical fusion resulted in statistically indistinguishable performance from self-assessed weighted voting. The authors developed a new theoretical basis for using self-assessed performance in the framework of statistical fusion and demonstrated that the combined sources of information (both statistical assessment and self-assessment) yielded statistically significant improvement over the methods considered separately. Conclusions: The authors present the first systematic characterization of self-assessed performance in manual labeling. The authors demonstrate that self-assessment and statistical fusion yield similar, but complementary, benefits for label fusion. Finally, the authors present a new theoretical basis for combining self-assessments with statistical label fusion. PMID:24593721

Sigsearch: a new term for post hoc unplanned search for statistically significant relationships with the intent to create publishable findings.

PubMed

Hashim, Muhammad Jawad

2010-09-01

Post-hoc secondary data analysis with no prespecified hypotheses has been discouraged by textbook authors and journal editors alike. Unfortunately no single term describes this phenomenon succinctly. I would like to coin the term "sigsearch" to define this practice and bring it within the teaching lexicon of statistics courses. Sigsearch would include any unplanned, post-hoc search for statistical significance using multiple comparisons of subgroups. It would also include data analysis with outcomes other than the prespecified primary outcome measure of a study as well as secondary data analyses of earlier research.

[Effects of climate warming and drying on millet yield in Gansu Province and related countermeasures].

PubMed

Cao, Ling; Wang, Qiang; Deng, Zhen-yong; Guo, Xiao-qin; Ma, Xing-xiang; Ning, Hui-fang

2010-11-01

Based on the data of air temperature, precipitation, and millet yield from Ganzhou, Anding, and Xifeng, the representative stations in Hexi moderate arid oasis irrigation area, moderate sub-arid dry area in middle Gansu, and moderate sub-humid dry area in eastern Gansu, respectively, this paper calculated the regional active accumulated temperature of > or = 0 degrees C, > or =5 degrees C, > or =10 degrees C, > or =15 degrees C, and > or =20 degrees C in millet growth period, and the average temperature and precipitation in millet key growth stages. The millet climatic yield was isolated by orthogonal polynomial, and the change characteristics of climate and millet climatic yield as well as the effects of climate change on millet yield were analyzed by statistical methods of linear tendency, cumulative anomaly, and Mann-Kendall. The results showed that warming and drying were the main regional features in the modern climatic change of Gansu. The regional temperature had a significant upward trend since the early 1990s, while the precipitation was significantly reduced from the late 1980s. There were significant correlations between millet yield and climatic factors. The millet yield in dry areas increased with the increasing temperature and precipitation in millet key growth stages, and that in Hexi Corridor area increased with increasing temperature. Warming and drying affected millet yield prominently. The weather fluctuation index of regional millet yield in Xifeng, Anding, and Ganzhou accounted for 73%, 72%, and 54% of real output coefficient variation, respectively, and the percentages increased significantly after warming. Warming was conducive to the increase of millet production, and the annual increment of millet climatic yield in Xifeng, Anding, and Ganzhou after warming was 30.6, 43.1, and 121.1 kg x hm(-2), respectively. Aiming at the warming and drying trend in Gansu Province in the future, the millet planting area in the Province should be further

Determination of gaseous fission product yields from 14 MeV neutron induced fission of 238U at the National Ignition Facility

DOE PAGES

Cassata, W. S.; Velsko, C. A.; Stoeffl, W.; ...

2016-01-14

We determined fission yields of xenon ( 133mXe, 135Xe, 135mXe, 137Xe, 138Xe, and 139Xe) resulting from 14 MeV neutron induced fission of depleted uranium at the National Ignition Facility. Measurements begin approximately 20 s after shot time, and yields have been determined for nuclides with half-lives as short as tens of seconds. We determined the relative independent yields of 133mXe, 135Xe, and 135mXe to significantly higher precision than previously reported. The relative fission yields of all nuclides are statistically indistinguishable from values reported by England and Rider (ENDF-349. LA-UR-94-3106, 1994), with exception of the cumulative yield of 139Xe. Furthermore, considerablemore » differences exist between our measured yields and the JEFF-3.1 database values.« less

Linking Field and Satellite Observations to Reveal Differences in Single vs. Double-Cropped Soybean Yields in Central Brazil

NASA Astrophysics Data System (ADS)

Jeffries, G. R.; Cohn, A.

2016-12-01

Soy-corn double cropping (DC) has been widely adopted in Central Brazil alongside single cropped (SC) soybean production. DC involves different cropping calendars, soy varieties, and may be associated with different crop yield patterns and volatility than SC. Study of the performance of the region's agriculture in a changing climate depends on tracking differences in the productivity of SC vs. DC, but has been limited by crop yield data that conflate the two systems. We predicted SC and DC yields across Central Brazil, drawing on field observations and remotely sensed data. We first modeled field yield estimates as a function of remotely sensed DC status and vegetation index (VI) metrics, and other management and biophysical factors. We then used the statistical model estimated to predict SC and DC soybean yields at each 500 m2 grid cell of Central Brazil for harvest years 2001 - 2015. The yield estimation model was constructed using 1) a repeated cross-sectional survey of soybean yields and management factors for years 2007-2015, 2) a custom agricultural land cover classification dataset which assimilates earlier datasets for the region, and 3) 500m 8-day MODIS image composites used to calculate the wide dynamic range vegetation index (WDRVI) and derivative metrics such as area under the curve for WDRVI values in critical crop development periods. A statistical yield estimation model which primarily entails WDRVI metrics, DC status, and spatial fixed effects was developed on a subset of the yield dataset. Model validation was conducted by predicting previously withheld yield records, and then assessing error and goodness-of-fit for predicted values with metrics including root mean squared error (RMSE), mean squared error (MSE), and R2. We found a statistical yield estimation model which incorporates WDRVI and DC status to be way to estimate crop yields over the region. Statistical properties of the resulting gridded yield dataset may be valuable for understanding

Scalable detection of statistically significant communities and hierarchies, using message passing for modularity

PubMed Central

Zhang, Pan; Moore, Cristopher

2014-01-01

Modularity is a popular measure of community structure. However, maximizing the modularity can lead to many competing partitions, with almost the same modularity, that are poorly correlated with each other. It can also produce illusory ‘‘communities’’ in random graphs where none exist. We address this problem by using the modularity as a Hamiltonian at finite temperature and using an efficient belief propagation algorithm to obtain the consensus of many partitions with high modularity, rather than looking for a single partition that maximizes it. We show analytically and numerically that the proposed algorithm works all of the way down to the detectability transition in networks generated by the stochastic block model. It also performs well on real-world networks, revealing large communities in some networks where previous work has claimed no communities exist. Finally we show that by applying our algorithm recursively, subdividing communities until no statistically significant subcommunities can be found, we can detect hierarchical structure in real-world networks more efficiently than previous methods. PMID:25489096

Annual Corn Yield Estimation through Multi-temporal MODIS Data

NASA Astrophysics Data System (ADS)

Shao, Y.; Zheng, B.; Campbell, J. B.

2013-12-01

This research employed 13 years of the Moderate Resolution Imaging Spectroradiometer (MODIS) to estimate annual corn yield for the Midwest of the United States. The overall objective of this study was to examine if annual corn yield could be accurately predicted using MODIS time-series NDVI (Normalized Difference Vegetation Index) and ancillary data such monthly precipitation and temperature. MODIS-NDVI 16-Day composite images were acquired from the USGS EROS Data Center for calendar years 2000 to 2012. For the same time-period, county level corn yield statistics were obtained from the National Agricultural Statistics Service (NASS). The monthly precipitation and temperature measures were derived from Precipitation-Elevation Regressions on Independent Slopes Model (PRISM) climate data. A cropland mask was derived using 2006 National Land Cover Database. For each county and within the cropland mask, the MODIS-NDVI time-series data and PRISM climate data were spatially averaged, at their respective time steps. We developed a random forest predictive model with the MODIS-NDVI and climate data as predictors and corn yield as response. To assess the model accuracy, we used twelve years of data as training and the remaining year as hold-out testing set. The training and testing procedures were repeated 13 times. The R2 ranged from 0.72 to 0.83 for testing years. It was also found that the inclusion of climate data did not improve the model predictive performance. MODIS-NDVI time-series data alone might provide sufficient information for county level corn yield prediction.

Effects of different irrigation practices using treated wastewater on tomato yields, quality, water productivity, and soil and fruit mineral contents.

PubMed

Demir, Azize Dogan; Sahin, Ustun

2017-11-01

Wastewater use in agricultural irrigation is becoming a common practice in order to meet the rising water demands in arid and semi-arid regions. The study was conducted to determine the effects of the full (FI), deficit (DI), and partial root-zone drying (PRD) irrigation practices using treated municipal wastewater (TWW) and freshwater (FW) on tomato yield, water use, fruit quality, and soil and fruit heavy metal concentrations. The TWW significantly increased marketable yield compared to the FW, as well as decreased water consumption. Therefore, water use efficiency (WUE) in the TWW was significantly higher than in the FW. Although the DI and the PRD practices caused less yields, these practices significantly increased WUE values due to less irrigation water applied. The water-yield linear relationships were statistically significant. TWW significantly increased titratable acidity and vitamin C contents. Reduced irrigation provided significantly lower titratable acidity, vitamin C, and lycopene contents. TWW increased the surface soil and fruit mineral contents in response to FW. Greater increases were observed under FI, and mineral contents declined with reduction in irrigation water. Heavy metal accumulation in soils was within safe limits. However, Cd and Pb contents in fruits exceeded standard limits given by FAO/WHO. Higher metal pollution index values determined for fruits also indicated that TWW application, especially under FI, might cause health risks in long term.

[Spatial-temporal variations of spring maize potential yields in a changing climate in Northeast China.

PubMed

Liu, Zhi Juan; Yang, Xiao Guang; Lyu, Shuo; Wang, Jing; Lin, Xiao Mao

2018-01-01

Based on meteorological data, agro-meteorological observations, and agricultural statistical data in Northeast China (NEC), by using the validated Agricultural Production System sIMulator (APSIM-maize), the potential, attainable, potential farmers' and actual farmers' yields of spring maize during the period 1961 to 2015 were analyzed, and the effects of climate variation on maize potential yield in NEC were quantified. Results indicated that the potential yield of spring maize was 12.2 t·hm -2 during the period 1961 to 2015, with those in northeast being lower than southwest within the study region. The attainable yield of spring maize was 11.3 t·hm -2 , and showed a similar spatial distribution with potential yield. Under the current farmers' management practices, mean simulated potential and actual farmers' yields were 6.5 and 4.5 t·hm -2 , respectively. Assuming there were no changes in cultivars and management practices in NEC, the mean potential, attainable, and potential farmers' yields of spring maize would decrease by 0.34, 0.25 and 0.10 t·hm -2 per decade in NEC. However, the actual farmers' yields increased with the value of 1.27 t·hm -2 per decade averaged over NEC. Due to climate variation, year-to-year variations of spring maize potential, attainable, and potential farmers' yields were significant, ranging from 10.0 to 14.4, 9.8 to 13.3, 4.4 to 8.5 t·hm -2 , respectively.

Effects of Hydrological Parameters on Palm Oil Fresh Fruit Bunch Yield)

NASA Astrophysics Data System (ADS)

Nda, M.; Adnan, M. S.; Suhadak, M. A.; Zakaria, M. S.; Lopa, R. T.

2018-04-01

Climate change effects and variability have been studied by many researchers in diverse geophysical fields. Malaysia produces large volume of palm oil, the effects of climate change on hydrological parameters (rainfall and precipitation) could have adverse effects on palm oil fresh fruit bunch (FFB) production with implications at both local and international market. It is important to understand the effects of climate change on crop yield to adopt new cultivation techniques and guaranteeing food security globally. Based on this background, the paper’s objective is to investigate the effects of rainfall and temperature pattern on crop yield (FFB) within five years period (2013 - 2017) at Batu Pahat District. The Man - Kendall rank technique (trend test) and statistical analyses (correlation and regression) were applied to the dataset used for the study. The results reveal that there are variabilities in rainfall and temperature from one month to the other and the statistical analysis reveals that the hydrological parameters have an insignificant effect on crop yield.

Agricultural land use doubled sediment yield of western China's rivers

NASA Astrophysics Data System (ADS)

Schmidt, A. H.; Bierman, P. R.; Sosa-Gonzalez, V.; Neilson, T. B.; Rood, D. H.; Martin, J.; Hill, M.

2017-12-01

Land use changes, such as deforestation and agriculture, increase soil erosion rates on the scale of hillslopes and small drainage basins; however, the effects of these changes on the sediment load in larger rivers is poorly quantified, with a few studies scattered globally, and only 10 data points in the world's most populous nation, China. At 20 different sites in western China, we compare contemporary (1945-1987) fluvial sediment yield data collected daily over 4 to 26 years (median = 19 years) to long-term measures of erosion (sediment generation) based on new isotopic measurements of in situ 10Be in river sediments. We find that median sediment transport at these sites exceeds background sediment generation rates by a factor of two (from 0.13 to 5.79 times, median 1.85 times) and that contemporary sediment yield is statistically significantly different from long-term sediment yield (p < 0.05). Agricultural land use is directly and significantly proportional to the ratio of contemporary sediment yield to long term sediment generation rates (Spearman correlation coefficient rho = 0.52, p < 0.05). We support these findings by calculating erosion indices (following Brown et al., 1988), which compare the delivery of meteoric 10Be to each watershed with the export of meteoric 10Be bound to riverine sediment. Erosion indices are also directly and significantly proportional to agricultural land use (rho = 0.58, p < 0.05). We measured unsupported 210Pb and 137Cs in 130 detrital samples from throughout the region. We find that only 4 samples (those from high elevation, low relief watersheds) have detectable 137Cs and 31 samples have detectable unsupported 210Pb. The lack of 137Cs in most samples suggests high rates of erosion in the 1950s-1960s when 137Cs would have been delivered to the landscape. Detectable 210Pb in 25% of the watersheds suggests that in some areas erosion rates have slowed since that time allowing 210Pb to accumulate to measurable levels. Together

GPU-computing in econophysics and statistical physics

NASA Astrophysics Data System (ADS)

Preis, T.

2011-03-01

A recent trend in computer science and related fields is general purpose computing on graphics processing units (GPUs), which can yield impressive performance. With multiple cores connected by high memory bandwidth, today's GPUs offer resources for non-graphics parallel processing. This article provides a brief introduction into the field of GPU computing and includes examples. In particular computationally expensive analyses employed in financial market context are coded on a graphics card architecture which leads to a significant reduction of computing time. In order to demonstrate the wide range of possible applications, a standard model in statistical physics - the Ising model - is ported to a graphics card architecture as well, resulting in large speedup values.

Statistical analysis of CSP plants by simulating extensive meteorological series

NASA Astrophysics Data System (ADS)

Pavón, Manuel; Fernández, Carlos M.; Silva, Manuel; Moreno, Sara; Guisado, María V.; Bernardos, Ana

2017-06-01

The feasibility analysis of any power plant project needs the estimation of the amount of energy it will be able to deliver to the grid during its lifetime. To achieve this, its feasibility study requires a precise knowledge of the solar resource over a long term period. In Concentrating Solar Power projects (CSP), financing institutions typically requires several statistical probability of exceedance scenarios of the expected electric energy output. Currently, the industry assumes a correlation between probabilities of exceedance of annual Direct Normal Irradiance (DNI) and energy yield. In this work, this assumption is tested by the simulation of the energy yield of CSP plants using as input a 34-year series of measured meteorological parameters and solar irradiance. The results of this work show that, even if some correspondence between the probabilities of exceedance of annual DNI values and energy yields is found, the intra-annual distribution of DNI may significantly affect this correlation. This result highlights the need of standardized procedures for the elaboration of representative DNI time series representative of a given probability of exceedance of annual DNI.

Satellite-based assessment of grassland yields

NASA Astrophysics Data System (ADS)

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.

Heat waves imposed during early pod development in soybean (Glycine max) cause significant yield loss despite a rapid recovery from oxidative stress.

PubMed

Siebers, Matthew H; Yendrek, Craig R; Drag, David; Locke, Anna M; Rios Acosta, Lorena; Leakey, Andrew D B; Ainsworth, Elizabeth A; Bernacchi, Carl J; Ort, Donald R

2015-08-01

Heat waves already have a large impact on crops and are predicted to become more intense and more frequent in the future. In this study, heat waves were imposed on soybean using infrared heating technology in a fully open-air field experiment. Five separate heat waves were applied to field-grown soybean (Glycine max) in central Illinois, three in 2010 and two in 2011. Thirty years of historical weather data from Illinois were analyzed to determine the length and intensity of a regionally realistic heat wave resulting in experimental heat wave treatments during which day and night canopy temperatures were elevated 6 °C above ambient for 3 days. Heat waves were applied during early or late reproductive stages to determine whether and when heat waves had an impact on carbon metabolism and seed yield. By the third day of each heat wave, net photosynthesis (A), specific leaf weight (SLW), and leaf total nonstructural carbohydrate concentration (TNC) were decreased, while leaf oxidative stress was increased. However, A, SLW, TNC, and measures of oxidative stress were no different than the control ca. 12 h after the heat waves ended, indicating rapid physiological recovery from the high-temperature stress. That end of season seed yield was reduced (~10%) only when heat waves were applied during early pod developmental stages indicates the yield loss had more to do with direct impacts of the heat waves on reproductive process than on photosynthesis. Soybean was unable to mitigate yield loss after heat waves given during late reproductive stages. This study shows that short high-temperature stress events that reduce photosynthesis and increase oxidative stress resulted in significant losses to soybean production in the Midwest, U.S. The study also suggests that to mitigate heat wave-induced yield loss, soybean needs improved reproductive and photosynthetic tolerance to high but increasingly common temperatures. Published 2015. This article is a U.S. Government work and is

Mapping quantitative trait loci with additive effects and additive x additive epistatic interactions for biomass yield, grain yield, and straw yield using a doubled haploid population of wheat (Triticum aestivum L.).

PubMed

Li, Z K; Jiang, X L; Peng, T; Shi, C L; Han, S X; Tian, B; Zhu, Z L; Tian, J C

2014-02-28

Biomass yield is one of the most important traits for wheat (Triticum aestivum L.)-breeding programs. Increasing the yield of the aerial parts of wheat varieties will be an integral component of future wheat improvement; however, little is known regarding the genetic control of aerial part yield. A doubled haploid population, comprising 168 lines derived from a cross between two winter wheat cultivars, 'Huapei 3' (HP3) and 'Yumai 57' (YM57), was investigated. Quantitative trait loci (QTL) for total biomass yield, grain yield, and straw yield were determined for additive effects and additive x additive epistatic interactions using the QTLNetwork 2.0 software based on the mixed-linear model. Thirteen QTL were determined to have significant additive effects for the three yield traits, of which six also exhibited epistatic effects. Eleven significant additive x additive interactions were detected, of which seven occurred between QTL showing epistatic effects only, two occurred between QTL showing epistatic effects and additive effects, and two occurred between QTL with additive effects. These QTL explained 1.20 to 10.87% of the total phenotypic variation. The QTL with an allele originating from YM57 on chromosome 4B and another QTL contributed by HP3 alleles on chromosome 4D were simultaneously detected on the same or adjacent chromosome intervals for the three traits in two environments. Most of the repeatedly detected QTL across environments were not significant (P > 0.05). These results have implications for selection strategies in wheat biomass yield and for increasing the yield of the aerial part of wheat.

Student and Professor Gender Effects in Introductory Business Statistics

ERIC Educational Resources Information Center

Haley, M. Ryan; Johnson, Marianne F.; Kuennen, Eric W.

2007-01-01

Studies have yielded highly mixed results as to differences in male and female student performance in statistics courses; the role that professors play in these differences is even less clear. In this paper, we consider the impact of professor and student gender on student performance in an introductory business statistics course taught by…

Sunspot activity and influenza pandemics: a statistical assessment of the purported association.

PubMed

Towers, S

2017-10-01

Since 1978, a series of papers in the literature have claimed to find a significant association between sunspot activity and the timing of influenza pandemics. This paper examines these analyses, and attempts to recreate the three most recent statistical analyses by Ertel (1994), Tapping et al. (2001), and Yeung (2006), which all have purported to find a significant relationship between sunspot numbers and pandemic influenza. As will be discussed, each analysis had errors in the data. In addition, in each analysis arbitrary selections or assumptions were also made, and the authors did not assess the robustness of their analyses to changes in those arbitrary assumptions. Varying the arbitrary assumptions to other, equally valid, assumptions negates the claims of significance. Indeed, an arbitrary selection made in one of the analyses appears to have resulted in almost maximal apparent significance; changing it only slightly yields a null result. This analysis applies statistically rigorous methodology to examine the purported sunspot/pandemic link, using more statistically powerful un-binned analysis methods, rather than relying on arbitrarily binned data. The analyses are repeated using both the Wolf and Group sunspot numbers. In all cases, no statistically significant evidence of any association was found. However, while the focus in this particular analysis was on the purported relationship of influenza pandemics to sunspot activity, the faults found in the past analyses are common pitfalls; inattention to analysis reproducibility and robustness assessment are common problems in the sciences, that are unfortunately not noted often enough in review.

Measurements of branching fraction ratios and CP-asymmetries in suppressed B{sup -}{yields}D({yields}K{sup +}{pi}{sup -})K{sup -} and B{sup -}{yields}D({yields}K{sup +}{pi}{sup -}){pi}{sup -} decays

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

Aaltonen, T.; Brucken, E.; Devoto, F.

2011-11-01

We report the first reconstruction in hadron collisions of the suppressed decays B{sup -}{yields}D({yields}K{sup +}{pi}{sup -})K{sup -} and B{sup -}{yields}D({yields}K{sup +}{pi}{sup -}){pi}{sup -}, sensitive to the Cabibbo-Kobayashi-Maskawa phase {gamma}, using data from 7 fb{sup -1} of integrated luminosity collected by the CDF II detector at the Tevatron collider. We reconstruct a signal for the B{sup -}{yields}D({yields}K{sup +}{pi}{sup -})K{sup -} suppressed mode with a significance of 3.2 standard deviations, and measure the ratios of the suppressed to favored branching fractions R(K)=[22.0{+-}8.6(stat){+-}2.6(syst)]x10{sup -3}, R{sup +}(K)=[42.6{+-}13.7(stat){+-}2.8(syst)]x10{sup -3}, R{sup -}(K)=[3.8{+-}10.3(stat){+-}2.7(syst)]x10{sup -3} as well as the direct CP-violating asymmetry A(K)=-0.82{+-}0.44(stat){+-}0.09(syst) of this mode. Corresponding quantitiesmore » for B{sup -}{yields}D({yields}K{sup +}{pi}{sup -}){pi}{sup -} decay are also reported.« less

CorSig: a general framework for estimating statistical significance of correlation and its application to gene co-expression analysis.

PubMed

Wang, Hong-Qiang; Tsai, Chung-Jui

2013-01-01

With the rapid increase of omics data, correlation analysis has become an indispensable tool for inferring meaningful associations from a large number of observations. Pearson correlation coefficient (PCC) and its variants are widely used for such purposes. However, it remains challenging to test whether an observed association is reliable both statistically and biologically. We present here a new method, CorSig, for statistical inference of correlation significance. CorSig is based on a biology-informed null hypothesis, i.e., testing whether the true PCC (ρ) between two variables is statistically larger than a user-specified PCC cutoff (τ), as opposed to the simple null hypothesis of ρ = 0 in existing methods, i.e., testing whether an association can be declared without a threshold. CorSig incorporates Fisher's Z transformation of the observed PCC (r), which facilitates use of standard techniques for p-value computation and multiple testing corrections. We compared CorSig against two methods: one uses a minimum PCC cutoff while the other (Zhu's procedure) controls correlation strength and statistical significance in two discrete steps. CorSig consistently outperformed these methods in various simulation data scenarios by balancing between false positives and false negatives. When tested on real-world Populus microarray data, CorSig effectively identified co-expressed genes in the flavonoid pathway, and discriminated between closely related gene family members for their differential association with flavonoid and lignin pathways. The p-values obtained by CorSig can be used as a stand-alone parameter for stratification of co-expressed genes according to their correlation strength in lieu of an arbitrary cutoff. CorSig requires one single tunable parameter, and can be readily extended to other correlation measures. Thus, CorSig should be useful for a wide range of applications, particularly for network analysis of high-dimensional genomic data. A web server for

Measurements of {Gamma}(Z{sup O} {yields} b{bar b})/{Gamma}(Z{sup O} {yields} hadrons) using the SLD

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

Neal, H.A. Jr. II

1995-07-01

The quantity R{sub b} = {Gamma}(Z{sup o} {yields}b{bar b})/{Gamma}(Z{sup o} {yields} hadrons) is a sensitive measure of corrections to the Zbb vertex. The precision necessary to observe the top quark mass dependent corrections is close to being achieved. LEP is already observing a 1.8{sigma} deviation from the Standard Model prediction. Knowledge of the top quark mass combined with the observation of deviations from the Standard Model prediction would indicate new physics. Models which include charged Higgs or light SUSY particles yield predictions for R{sub b} appreciably different from the Standard Model. In this thesis two independent methods are used tomore » measure R{sub b}. One uses a general event tag which determines R{sub b} from the rate at which events are tagged as Z{sup o} {yields} b{bar b} in data and the estimated rates at which various flavors of events are tagged from the Monte Carlo. The second method reduces the reliance on the Monte Carlo by separately tagging each hemisphere as containing a b-decay. The rates of single hemisphere tagged events and both hemisphere tagged events are used to determine the tagging efficiency for b-quarks directly from the data thus eliminating the main sources of systematic error present in the event tag. Both measurements take advantage of the unique environment provided by the SLAC Linear Collider (SLC) and the SLAC Large Detector (SLD). From the event tag a result of R{sub b} = 0.230{plus_minus}0.004{sub statistical}{plus_minus}0.013{sub systematic} is obtained. The higher precision hemisphere tag result obtained is R{sub b} = 0.218{plus_minus}0.004{sub statistical}{plus_minus}0.004{sub systematic}{plus_minus}0.003{sub Rc}.« less

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

PubMed

Leng, Guoyong

2017-12-15

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

Effect of warming temperatures on US wheat yields.

PubMed

Tack, Jesse; Barkley, Andrew; Nalley, Lawton Lanier

2015-06-02

Climate change is expected to increase future temperatures, potentially resulting in reduced crop production in many key production regions. Research quantifying the complex relationship between weather variables and wheat yields is rapidly growing, and recent advances have used a variety of model specifications that differ in how temperature data are included in the statistical yield equation. A unique data set that combines Kansas wheat variety field trial outcomes for 1985-2013 with location-specific weather data is used to analyze the effect of weather on wheat yield using regression analysis. Our results indicate that the effect of temperature exposure varies across the September-May growing season. The largest drivers of yield loss are freezing temperatures in the Fall and extreme heat events in the Spring. We also find that the overall effect of warming on yields is negative, even after accounting for the benefits of reduced exposure to freezing temperatures. Our analysis indicates that there exists a tradeoff between average (mean) yield and ability to resist extreme heat across varieties. More-recently released varieties are less able to resist heat than older lines. Our results also indicate that warming effects would be partially offset by increased rainfall in the Spring. Finally, we find that the method used to construct measures of temperature exposure matters for both the predictive performance of the regression model and the forecasted warming impacts on yields.

Random Forests for Global and Regional Crop Yield Predictions.

PubMed

Jeong, Jig Han; Resop, Jonathan P; Mueller, Nathaniel D; Fleisher, David H; Yun, Kyungdahm; Butler, Ethan E; Timlin, Dennis J; Shim, Kyo-Moon; Gerber, James S; Reddy, Vangimalla R; Kim, Soo-Hyung

2016-01-01

Accurate predictions of crop yield are critical for developing effective agricultural and food policies at the regional and global scales. We evaluated a machine-learning method, Random Forests (RF), for its ability to predict crop yield responses to climate and biophysical variables at global and regional scales in wheat, maize, and potato in comparison with multiple linear regressions (MLR) serving as a benchmark. We used crop yield data from various sources and regions for model training and testing: 1) gridded global wheat grain yield, 2) maize grain yield from US counties over thirty years, and 3) potato tuber and maize silage yield from the northeastern seaboard region. RF was found highly capable of predicting crop yields and outperformed MLR benchmarks in all performance statistics that were compared. For example, the root mean square errors (RMSE) ranged between 6 and 14% of the average observed yield with RF models in all test cases whereas these values ranged from 14% to 49% for MLR models. Our results show that RF is an effective and versatile machine-learning method for crop yield predictions at regional and global scales for its high accuracy and precision, ease of use, and utility in data analysis. RF may result in a loss of accuracy when predicting the extreme ends or responses beyond the boundaries of the training data.

A dose-response relationship for marketable yield reduction of two lettuce (Lactuca sativa L.) cultivars exposed to tropospheric ozone in Southern Europe.

PubMed

Marzuoli, Riccardo; Finco, Angelo; Chiesa, Maria; Gerosa, Giacomo

2017-12-01

The present study investigated the response to ozone (O 3 ) of two cultivars (cv.'Romana' and cv. 'Canasta') of irrigated lettuce grown in an open-top chamber (OTC) experiment in Mediterranean conditions. Two different levels of O 3 were applied, ambient O 3 in non-filtered OTCs (NF-OTCs) and -40% of ambient O 3 in charcoal-filtered OTCs (CF-OTCs), during four consecutive growing cycles. At the end of each growing cycle, the marketable yield (fresh biomass) was assessed while during the growing periods, measurements of the stomatal conductance at leaf level were performed and used to define a stomatal conductance model for calculation of the phytotoxic ozone dose (POD) absorbed by the plants.Results showed that O 3 caused statistically significant yield reductions in the first and in the last growing cycle. In general, the marketable yield of the NF-OTC plants was always lower than the CF-OTC plants for both cultivars, with mean reductions of -18.5 and -14.5% for 'Romana' and 'Canasta', respectively. On the contrary, there was no statistically significant difference in marketable yield due to the cultivar factor or to the interaction between O 3 and cultivar in any of the growing cycle performed.Dose-response relationships for the marketable relative yield based on the POD values were calculated according to different flux threshold values (Y). The best regression fit was obtained using an instantaneous flux threshold of 6 nmol O 3 m -2  s -1 (POD 6 ); the same value was obtained also for other crops. According to the generic lettuce dose-response relationship, an O 3 critical level of 1 mmol O 3 m -2 of POD 6 for a 15% of marketable yield loss was found.

Searching for statistically significant regulatory modules.

PubMed

Bailey, Timothy L; Noble, William Stafford

2003-10-01

The regulatory machinery controlling gene expression is complex, frequently requiring multiple, simultaneous DNA-protein interactions. The rate at which a gene is transcribed may depend upon the presence or absence of a collection of transcription factors bound to the DNA near the gene. Locating transcription factor binding sites in genomic DNA is difficult because the individual sites are small and tend to occur frequently by chance. True binding sites may be identified by their tendency to occur in clusters, sometimes known as regulatory modules. We describe an algorithm for detecting occurrences of regulatory modules in genomic DNA. The algorithm, called mcast, takes as input a DNA database and a collection of binding site motifs that are known to operate in concert. mcast uses a motif-based hidden Markov model with several novel features. The model incorporates motif-specific p-values, thereby allowing scores from motifs of different widths and specificities to be compared directly. The p-value scoring also allows mcast to only accept motif occurrences with significance below a user-specified threshold, while still assigning better scores to motif occurrences with lower p-values. mcast can search long DNA sequences, modeling length distributions between motifs within a regulatory module, but ignoring length distributions between modules. The algorithm produces a list of predicted regulatory modules, ranked by E-value. We validate the algorithm using simulated data as well as real data sets from fruitfly and human. http://meme.sdsc.edu/MCAST/paper

Societal Statistics by virtue of the Statistical Drake Equation

NASA Astrophysics Data System (ADS)

Maccone, Claudio

2012-09-01

The Drake equation, first proposed by Frank D. Drake in 1961, is the foundational equation of SETI. It yields an estimate of the number N of extraterrestrial communicating civilizations in the Galaxy given by the product N=Ns×fp×ne×fl×fi×fc×fL, where: Ns is the number of stars in the Milky Way Galaxy; fp is the fraction of stars that have planetary systems; ne is the number of planets in a given system that are ecologically suitable for life; fl is the fraction of otherwise suitable planets on which life actually arises; fi is the fraction of inhabited planets on which an intelligent form of life evolves; fc is the fraction of planets inhabited by intelligent beings on which a communicative technical civilization develops; and fL is the fraction of planetary lifetime graced by a technical civilization. The first three terms may be called "the astrophysical terms" in the Drake equation since their numerical value is provided by astrophysical considerations. The fourth term, fl, may be called "the origin-of-life term" and entails biology. The last three terms may be called "the societal terms" inasmuch as their respective numerical values are provided by anthropology, telecommunication science and "futuristic science", respectively. In this paper, we seek to provide a statistical estimate of the three societal terms in the Drake equation basing our calculations on the Statistical Drake Equation first proposed by this author at the 2008 IAC. In that paper the author extended the simple 7-factor product so as to embody Statistics. He proved that, no matter which probability distribution may be assigned to each factor, if the number of factors tends to infinity, then the random variable N follows the lognormal distribution (central limit theorem of Statistics). This author also proved at the 2009 IAC that the Dole (1964) [7] equation, yielding the number of Habitable Planets for Man in the Galaxy, has the same mathematical structure as the Drake equation. So the

Assessing the significance of pedobarographic signals using random field theory.

PubMed

Pataky, Todd C

2008-08-07

Traditional pedobarographic statistical analyses are conducted over discrete regions. Recent studies have demonstrated that regionalization can corrupt pedobarographic field data through conflation when arbitrary dividing lines inappropriately delineate smooth field processes. An alternative is to register images such that homologous structures optimally overlap and then conduct statistical tests at each pixel to generate statistical parametric maps (SPMs). The significance of SPM processes may be assessed within the framework of random field theory (RFT). RFT is ideally suited to pedobarographic image analysis because its fundamental data unit is a lattice sampling of a smooth and continuous spatial field. To correct for the vast number of multiple comparisons inherent in such data, recent pedobarographic studies have employed a Bonferroni correction to retain a constant family-wise error rate. This approach unfortunately neglects the spatial correlation of neighbouring pixels, so provides an overly conservative (albeit valid) statistical threshold. RFT generally relaxes the threshold depending on field smoothness and on the geometry of the search area, but it also provides a framework for assigning p values to suprathreshold clusters based on their spatial extent. The current paper provides an overview of basic RFT concepts and uses simulated and experimental data to validate both RFT-relevant field smoothness estimations and RFT predictions regarding the topological characteristics of random pedobarographic fields. Finally, previously published experimental data are re-analysed using RFT inference procedures to demonstrate how RFT yields easily understandable statistical results that may be incorporated into routine clinical and laboratory analyses.

Post-heading heat stress and yield impact in winter wheat of China.

PubMed

Liu, Bing; Liu, Leilei; Tian, Liying; Cao, Weixing; Zhu, Yan; Asseng, Senthold

2014-02-01

Wheat is sensitive to high temperatures, but the spatial and temporal variability of high temperature and its impact on yield are often not known. An analysis of historical climate and yield data was undertaken to characterize the spatial and temporal variability of heat stress between heading and maturity and its impact on wheat grain yield in China. Several heat stress indices were developed to quantify heat intensity, frequency, and duration between heading and maturity based on measured maximum temperature records of the last 50 years from 166 stations in the main wheat-growing region of China. Surprisingly, heat stress between heading and maturity was more severe in the generally cooler northern wheat-growing regions than the generally warmer southern regions of China, because of the delayed time of heading with low temperatures during the earlier growing season and the exposure of the post-heading phase into the warmer part of the year. Heat stress between heading and maturity has increased in the last decades in most of the main winter wheat production areas of China, but the rate was higher in the south than in the north. The correlation between measured grain yields and post-heading heat stress and average temperature were statistically significant in the entire wheat-producing region, and explained about 29% of the observed spatial and temporal yield variability. A heat stress index considering the duration and intensity of heat between heading and maturity was required to describe the correlation of heat stress and yield variability. Because heat stress is a major cause of yield loss and the number of heat events is projected to increase in the future, quantifying the future impact of heat stress on wheat production and developing appropriate adaptation and mitigation strategies are critical for developing food security policies in China and elsewhere. © 2013 John Wiley & Sons Ltd.

Influence of oxidative stress and grains on sclerotial biomass and carotenoid yield of Penicillium sp. PT95.

PubMed

Chen, Shu-Jun; Wang, Qi; Han, Jian-Rong

2010-08-01

Oxidative stress and grains were evaluated for carotenoid production by solid-state fermentation using Penicillium sp. PT95. When the fungus was grown at high oxidative stress, its sclerotial biomass and carotenoid content in sclerotia increased significantly with respect to low oxidative stress (P < 0.01). High oxidative stress also caused a statistically significant increase in carotenoid yield as compared with low oxidative stress (P < 0.01). Both the sclerotial biomass and the amount of carotenoid accumulated in sclerotia of strain PT95 were strongly dependent on the grain medium used. Among the grain media tested under high oxidative stress, buckwheat medium gave the highest content of carotenoid in sclerotia (828 microg/g dry sclerotia), millet medium gave respectively the highest sclerotial biomass (12.69 g/100 g grain) and carotenoid yield (10.152 mg/100 g grain). Copyright 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Interaction Between Phosphorus and Zinc on the Biomass Yield and Yield Attributes of the Medicinal Plant Stevia (Stevia rebaudiana)

PubMed Central

Das, Kuntal; Dang, Raman; Shivananda, T. N.; Sur, Pintu

2005-01-01

A greenhouse experiment was conducted at the Indian Institute of Horticultural Research (IIHR), Bangalore to study the interaction effect between phosphorus (P) and zinc (Zn) on the yield and yield attributes of the medicinal plant stevia. The results show that the yield and yield attributes have been found to be significantly affected by different treatments. The total yield in terms of biomass production has been increased significantly with the application of Zn and P in different combinations and methods, being highest (23.34 g fresh biomass) in the treatment where Zn was applied as both soil (10 kg ZnSO4/ha) and foliar spray (0.2% ZnSO4). The results also envisaged that the different yield attributes viz. height, total number of branches, and number of leaves per plant have been found to be varied with treatments, being highest in the treatment where Zn was applied as both soil and foliar spray without the application of P. The results further indicated that the yield and yield attributes of stevia have been found to be decreased in the treatment where Zn was applied as both soil and foliar spray along with P suggesting an antagonistic effect between Zn and P. PMID:15915292

SU-F-BRD-05: Dosimetric Comparison of Protocol-Based SBRT Lung Treatment Modalities: Statistically Significant VMAT Advantages Over Fixed- Beam IMRT

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

Best, R; Harrell, A; Geesey, C

2014-06-15

Purpose: The purpose of this study is to inter-compare and find statistically significant differences between flattened field fixed-beam (FB) IMRT with flattening-filter free (FFF) volumetric modulated arc therapy (VMAT) for stereotactic body radiation therapy SBRT. Methods: SBRT plans using FB IMRT and FFF VMAT were generated for fifteen SBRT lung patients using 6 MV beams. For each patient, both IMRT and VMAT plans were created for comparison. Plans were generated utilizing RTOG 0915 (peripheral, 10 patients) and RTOG 0813 (medial, 5 patients) lung protocols. Target dose, critical structure dose, and treatment time were compared and tested for statistical significance. Parametersmore » of interest included prescription isodose surface coverage, target dose heterogeneity, high dose spillage (location and volume), low dose spillage (location and volume), lung dose spillage, and critical structure maximum- and volumetric-dose limits. Results: For all criteria, we found equivalent or higher conformality with VMAT plans as well as reduced critical structure doses. Several differences passed a Student's t-test of significance: VMAT reduced the high dose spillage, evaluated with conformality index (CI), by an average of 9.4%±15.1% (p=0.030) compared to IMRT. VMAT plans reduced the lung volume receiving 20 Gy by 16.2%±15.0% (p=0.016) compared with IMRT. For the RTOG 0915 peripheral lesions, the volumes of lung receiving 12.4 Gy and 11.6 Gy were reduced by 27.0%±13.8% and 27.5%±12.6% (for both, p<0.001) in VMAT plans. Of the 26 protocol pass/fail criteria, VMAT plans were able to achieve an average of 0.2±0.7 (p=0.026) more constraints than the IMRT plans. Conclusions: FFF VMAT has dosimetric advantages over fixed beam IMRT for lung SBRT. Significant advantages included increased dose conformity, and reduced organs-at-risk doses. The overall improvements in terms of protocol pass/fail criteria were more modest and will require more patient data to establish

Funding source and primary outcome changes in clinical trials registered on ClinicalTrials.gov are associated with the reporting of a statistically significant primary outcome: a cross-sectional study.

PubMed

Ramagopalan, Sreeram V; Skingsley, Andrew P; Handunnetthi, Lahiru; Magnus, Daniel; Klingel, Michelle; Pakpoor, Julia; Goldacre, Ben

2015-01-01

We and others have shown a significant proportion of interventional trials registered on ClinicalTrials.gov have their primary outcomes altered after the listed study start and completion dates. The objectives of this study were to investigate whether changes made to primary outcomes are associated with the likelihood of reporting a statistically significant primary outcome on ClinicalTrials.gov. A cross-sectional analysis of all interventional clinical trials registered on ClinicalTrials.gov as of 20 November 2014 was performed. The main outcome was any change made to the initially listed primary outcome and the time of the change in relation to the trial start and end date. 13,238 completed interventional trials were registered with ClinicalTrials.gov that also had study results posted on the website. 2555 (19.3%) had one or more statistically significant primary outcomes. Statistical analysis showed that registration year, funding source and primary outcome change after trial completion were associated with reporting a statistically significant primary outcome .  Funding source and primary outcome change after trial completion are associated with a statistically significant primary outcome report on clinicaltrials.gov.

Comparing and combining process-based crop models and statistical models with some implications for climate change

NASA Astrophysics Data System (ADS)

Roberts, Michael J.; Braun, Noah O.; Sinclair, Thomas R.; Lobell, David B.; Schlenker, Wolfram

2017-09-01

We compare predictions of a simple process-based crop model (Soltani and Sinclair 2012), a simple statistical model (Schlenker and Roberts 2009), and a combination of both models to actual maize yields on a large, representative sample of farmer-managed fields in the Corn Belt region of the United States. After statistical post-model calibration, the process model (Simple Simulation Model, or SSM) predicts actual outcomes slightly better than the statistical model, but the combined model performs significantly better than either model. The SSM, statistical model and combined model all show similar relationships with precipitation, while the SSM better accounts for temporal patterns of precipitation, vapor pressure deficit and solar radiation. The statistical and combined models show a more negative impact associated with extreme heat for which the process model does not account. Due to the extreme heat effect, predicted impacts under uniform climate change scenarios are considerably more severe for the statistical and combined models than for the process-based model.

Evaluating the capabilities of watershed-scale models in estimating sediment yield at field-scale.

PubMed

Sommerlot, Andrew R; Nejadhashemi, A Pouyan; Woznicki, Sean A; Giri, Subhasis; Prohaska, Michael D

2013-09-30

Many watershed model interfaces have been developed in recent years for predicting field-scale sediment loads. They share the goal of providing data for decisions aimed at improving watershed health and the effectiveness of water quality conservation efforts. The objectives of this study were to: 1) compare three watershed-scale models (Soil and Water Assessment Tool (SWAT), Field_SWAT, and the High Impact Targeting (HIT) model) against calibrated field-scale model (RUSLE2) in estimating sediment yield from 41 randomly selected agricultural fields within the River Raisin watershed; 2) evaluate the statistical significance among models; 3) assess the watershed models' capabilities in identifying areas of concern at the field level; 4) evaluate the reliability of the watershed-scale models for field-scale analysis. The SWAT model produced the most similar estimates to RUSLE2 by providing the closest median and the lowest absolute error in sediment yield predictions, while the HIT model estimates were the worst. Concerning statistically significant differences between models, SWAT was the only model found to be not significantly different from the calibrated RUSLE2 at α = 0.05. Meanwhile, all models were incapable of identifying priorities areas similar to the RUSLE2 model. Overall, SWAT provided the most correct estimates (51%) within the uncertainty bounds of RUSLE2 and is the most reliable among the studied models, while HIT is the least reliable. The results of this study suggest caution should be exercised when using watershed-scale models for field level decision-making, while field specific data is of paramount importance. Copyright © 2013 Elsevier Ltd. All rights reserved.

``Models'' CAVEAT EMPTOR!!!: ``Toy Models Too-Often Yield Toy-Results''!!!: Statistics, Polls, Politics, Economics, Elections!!!: GRAPH/Network-Physics: ``Equal-Distribution for All'' TRUMP-ED BEC ``Winner-Take-All'' ``Doctor Livingston I Presume?''

NASA Astrophysics Data System (ADS)

Preibus-Norquist, R. N. C.-Grover; Bush-Romney, G. W.-Willard-Mitt; Dimon, J. P.; Adelson-Koch, Sheldon-Charles-David-Sheldon; Krugman-Axelrod, Paul-David; Siegel, Edward Carl-Ludwig; D. N. C./O. F. P./''47''%/50% Collaboration; R. N. C./G. O. P./''53''%/49% Collaboration; Nyt/Wp/Cnn/Msnbc/Pbs/Npr/Ft Collaboration; Ftn/Fnc/Fox/Wsj/Fbn Collaboration; Lb/Jpmc/Bs/Boa/Ml/Wamu/S&P/Fitch/Moodys/Nmis Collaboration

2013-03-01

``Models''? CAVEAT EMPTOR!!!: ``Toy Models Too-Often Yield Toy-Results''!!!: Goldenfeld[``The Role of Models in Physics'', in Lects.on Phase-Transitions & R.-G.(92)-p.32-33!!!]: statistics(Silver{[NYTimes; Bensinger, ``Math-Geerks Clearly-Defeated Pundits'', LATimes, (11/9/12)])}, polls, politics, economics, elections!!!: GRAPH/network/net/...-PHYSICS Barabasi-Albert[RMP (02)] (r,t)-space VERSUS(???) [Where's the Inverse/ Dual/Integral-Transform???] (Benjamin)Franklin(1795)-Fourier(1795; 1897;1822)-Laplace(1850)-Mellin (1902) Brillouin(1922)-...(k,)-space, {Hubbard [The World According to Wavelets,Peters (96)-p.14!!!/p.246: refs.-F2!!!]},and then (2) Albert-Barabasi[]Bose-Einstein quantum-statistics(BEQS) Bose-Einstein CONDENSATION (BEC) versus Bianconi[pvt.-comm.; arXiv:cond-mat/0204506; ...] -Barabasi [???] Fermi-Dirac

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

Yield modeling of acoustic charge transport transversal filters

NASA Technical Reports Server (NTRS)

Kenney, J. S.; May, G. S.; Hunt, W. D.

1995-01-01

This paper presents a yield model for acoustic charge transport transversal filters. This model differs from previous IC yield models in that it does not assume that individual failures of the nondestructive sensing taps necessarily cause a device failure. A redundancy in the number of taps included in the design is explained. Poisson statistics are used to describe the tap failures, weighted over a uniform defect density distribution. A representative design example is presented. The minimum number of taps needed to realize the filter is calculated, and tap weights for various numbers of redundant taps are calculated. The critical area for device failure is calculated for each level of redundancy. Yield is predicted for a range of defect densities and redundancies. To verify the model, a Monte Carlo simulation is performed on an equivalent circuit model of the device. The results of the yield model are then compared to the Monte Carlo simulation. Better than 95% agreement was obtained for the Poisson model with redundant taps ranging from 30% to 150% over the minimum.

Chemometric investigation of light-shade effects on essential oil yield and morphology of Moroccan Myrtus communis L.

PubMed

Fadil, Mouhcine; Farah, Abdellah; Ihssane, Bouchaib; Haloui, Taoufik; Lebrazi, Sara; Zghari, Badreddine; Rachiq, Saâd

2016-01-01

To investigate the effect of environmental factors such as light and shade on essential oil yield and morphological traits of Moroccan Myrtus communis, a chemometric study was conducted on 20 individuals growing under two contrasting light environments. The study of individual's parameters by principal component analysis has shown that essential oil yield, altitude, and leaves thickness were positively correlated between them and negatively correlated with plants height, leaves length and leaves width. Principal component analysis and hierarchical cluster analysis have also shown that the individuals of each sampling site were grouped separately. The one-way ANOVA test has confirmed the effect of light and shade on essential oil yield and morphological parameters by showing a statistically significant difference between them from the shaded side to the sunny one. Finally, the multiple linear model containing main, interaction and quadratic terms was chosen for the modeling of essential oil yield in terms of morphological parameters. Sun plants have a small height, small leaves length and width, but they are thicker and richer in essential oil than shade plants which have shown almost the opposite. The highlighted multiple linear model can be used to predict essential oil yield in the studied area.

Significant lexical relationships

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

Pedersen, T.; Kayaalp, M.; Bruce, R.

Statistical NLP inevitably deals with a large number of rare events. As a consequence, NLP data often violates the assumptions implicit in traditional statistical procedures such as significance testing. We describe a significance test, an exact conditional test, that is appropriate for NLP data and can be performed using freely available software. We apply this test to the study of lexical relationships and demonstrate that the results obtained using this test are both theoretically more reliable and different from the results obtained using previously applied tests.

Grapevine canopy reflectance and yield

NASA Technical Reports Server (NTRS)

Minden, K. A.; Philipson, W. R.

1982-01-01

Field spectroradiometric and airborne multispectral scanner data were applied in a study of Concord grapevines. Spectroradiometric measurements of 18 experimental vines were collected on three dates during one growing season. Spectral reflectance, determined at 30 intervals from 0.4 to 1.1 microns, was correlated with vine yield, pruning weight, clusters/vine, and nitrogen input. One date of airborne multispectral scanner data (11 channels) was collected over commercial vineyards, and the average radiance values for eight vineyard sections were correlated with the corresponding average yields. Although some correlations were significant, they were inadequate for developing a reliable yield prediction model.

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

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

Leng, Guoyong

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

Stationary statistical theory of two-surface multipactor regarding all impacts for efficient threshold analysis

NASA Astrophysics Data System (ADS)

Lin, Shu; Wang, Rui; Xia, Ning; Li, Yongdong; Liu, Chunliang

2018-01-01

Statistical multipactor theories are critical prediction approaches for multipactor breakdown determination. However, these approaches still require a negotiation between the calculation efficiency and accuracy. This paper presents an improved stationary statistical theory for efficient threshold analysis of two-surface multipactor. A general integral equation over the distribution function of the electron emission phase with both the single-sided and double-sided impacts considered is formulated. The modeling results indicate that the improved stationary statistical theory can not only obtain equally good accuracy of multipactor threshold calculation as the nonstationary statistical theory, but also achieve high calculation efficiency concurrently. By using this improved stationary statistical theory, the total time consumption in calculating full multipactor susceptibility zones of parallel plates can be decreased by as much as a factor of four relative to the nonstationary statistical theory. It also shows that the effect of single-sided impacts is indispensable for accurate multipactor prediction of coaxial lines and also more significant for the high order multipactor. Finally, the influence of secondary emission yield (SEY) properties on the multipactor threshold is further investigated. It is observed that the first cross energy and the energy range between the first cross and the SEY maximum both play a significant role in determining the multipactor threshold, which agrees with the numerical simulation results in the literature.

Quantifying potential yield and water-limited yield of summer maize in the North China Plain

NASA Astrophysics Data System (ADS)

Jiang, Mingnuo; Liu, Chaoshun; Chen, Maosi

2017-09-01

The North China Plain is a major food producing region in China, and climate change could pose a threat to food production in the region. Based on China Meteorological Forcing Dataset, simulating the growth of summer maize in North China Plain from 1979 to 2015 with the regional implementation of crop growth model WOFOST. The results showed that the model can reflect the potential yield and water-limited yield of Summer Maize in North China Plain through the calibration and validation of WOFOST model. After the regional implementation of model, combined with the reanalysis data, the model can better reproduce the regional history of summer maize yield in the North China Plain. The yield gap in Southeastern Beijing, southern Tianjin, southern Hebei province, Northwestern Shandong province is significant, these means the water condition is the main factor to summer maize yield in these regions.

Pinning time statistics for vortex lines in disordered environments.

PubMed

Dobramysl, Ulrich; Pleimling, Michel; Täuber, Uwe C

2014-12-01

We study the pinning dynamics of magnetic flux (vortex) lines in a disordered type-II superconductor. Using numerical simulations of a directed elastic line model, we extract the pinning time distributions of vortex line segments. We compare different model implementations for the disorder in the surrounding medium: discrete, localized pinning potential wells that are either attractive and repulsive or purely attractive, and whose strengths are drawn from a Gaussian distribution; as well as continuous Gaussian random potential landscapes. We find that both schemes yield power-law distributions in the pinned phase as predicted by extreme-event statistics, yet they differ significantly in their effective scaling exponents and their short-time behavior.

Coppice Sycamore Yields Through 9 Years

Treesearch

Harvey E. Kennedy

1980-01-01

Cutting cycle and spacing did not significantly affect sycamore dry-weight yields from ages 5-9 years (1974-l 978). Longer cutting cycles usually did give higher yields. Dry-weight yields ranged from 2886 lb per acre (3233 kg/ha) per year in the 1 year, 4x5 ft (1.2 x 1.5 m) spacing to 4541 lb (5088 kg/ha) in the 4-year, 4x5 ft s,pacing. Survival averaged 67 percent...

The Heuristic Value of p in Inductive Statistical Inference

PubMed Central

Krueger, Joachim I.; Heck, Patrick R.

2017-01-01

Many statistical methods yield the probability of the observed data – or data more extreme – under the assumption that a particular hypothesis is true. This probability is commonly known as ‘the’ p-value. (Null Hypothesis) Significance Testing ([NH]ST) is the most prominent of these methods. The p-value has been subjected to much speculation, analysis, and criticism. We explore how well the p-value predicts what researchers presumably seek: the probability of the hypothesis being true given the evidence, and the probability of reproducing significant results. We also explore the effect of sample size on inferential accuracy, bias, and error. In a series of simulation experiments, we find that the p-value performs quite well as a heuristic cue in inductive inference, although there are identifiable limits to its usefulness. We conclude that despite its general usefulness, the p-value cannot bear the full burden of inductive inference; it is but one of several heuristic cues available to the data analyst. Depending on the inferential challenge at hand, investigators may supplement their reports with effect size estimates, Bayes factors, or other suitable statistics, to communicate what they think the data say. PMID:28649206

The Heuristic Value of p in Inductive Statistical Inference.

PubMed

Krueger, Joachim I; Heck, Patrick R

2017-01-01

Many statistical methods yield the probability of the observed data - or data more extreme - under the assumption that a particular hypothesis is true. This probability is commonly known as 'the' p -value. (Null Hypothesis) Significance Testing ([NH]ST) is the most prominent of these methods. The p -value has been subjected to much speculation, analysis, and criticism. We explore how well the p -value predicts what researchers presumably seek: the probability of the hypothesis being true given the evidence, and the probability of reproducing significant results. We also explore the effect of sample size on inferential accuracy, bias, and error. In a series of simulation experiments, we find that the p -value performs quite well as a heuristic cue in inductive inference, although there are identifiable limits to its usefulness. We conclude that despite its general usefulness, the p -value cannot bear the full burden of inductive inference; it is but one of several heuristic cues available to the data analyst. Depending on the inferential challenge at hand, investigators may supplement their reports with effect size estimates, Bayes factors, or other suitable statistics, to communicate what they think the data say.

A Comparison of Machine Learning Approaches for Corn Yield Estimation

NASA Astrophysics Data System (ADS)

Kim, N.; Lee, Y. W.

2017-12-01

Machine learning is an efficient empirical method for classification and prediction, and it is another approach to crop yield estimation. The objective of this study is to estimate corn yield in the Midwestern United States by employing the machine learning approaches such as the support vector machine (SVM), random forest (RF), and deep neural networks (DNN), and to perform the comprehensive comparison for their results. We constructed the database using satellite images from MODIS, the climate data of PRISM climate group, and GLDAS soil moisture data. In addition, to examine the seasonal sensitivities of corn yields, two period groups were set up: May to September (MJJAS) and July and August (JA). In overall, the DNN showed the highest accuracies in term of the correlation coefficient for the two period groups. The differences between our predictions and USDA yield statistics were about 10-11 %.

Yield surface evolution for columnar ice

NASA Astrophysics Data System (ADS)

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.

Bio hydrogen production from cassava starch by anaerobic mixed cultures: Multivariate statistical modeling

NASA Astrophysics Data System (ADS)

Tien, Hai Minh; Le, Kien Anh; Le, Phung Thi Kim

2017-09-01

Bio hydrogen is a sustainable energy resource due to its potentially higher efficiency of conversion to usable power, high energy efficiency and non-polluting nature resource. In this work, the experiments have been carried out to indicate the possibility of generating bio hydrogen as well as identifying effective factors and the optimum conditions from cassava starch. Experimental design was used to investigate the effect of operating temperature (37-43 °C), pH (6-7), and inoculums ratio (6-10 %) to the yield hydrogen production, the COD reduction and the ratio of volume of hydrogen production to COD reduction. The statistical analysis of the experiment indicated that the significant effects for the fermentation yield were the main effect of temperature, pH and inoculums ratio. The interaction effects between them seem not significant. The central composite design showed that the polynomial regression models were in good agreement with the experimental results. This result will be applied to enhance the process of cassava starch processing wastewater treatment.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

Flexible statistical modelling detects clinical functional magnetic resonance imaging activation in partially compliant subjects.

PubMed

Waites, Anthony B; Mannfolk, Peter; Shaw, Marnie E; Olsrud, Johan; Jackson, Graeme D

2007-02-01

Clinical functional magnetic resonance imaging (fMRI) occasionally fails to detect significant activation, often due to variability in task performance. The present study seeks to test whether a more flexible statistical analysis can better detect activation, by accounting for variance associated with variable compliance to the task over time. Experimental results and simulated data both confirm that even at 80% compliance to the task, such a flexible model outperforms standard statistical analysis when assessed using the extent of activation (experimental data), goodness of fit (experimental data), and area under the operator characteristic curve (simulated data). Furthermore, retrospective examination of 14 clinical fMRI examinations reveals that in patients where the standard statistical approach yields activation, there is a measurable gain in model performance in adopting the flexible statistical model, with little or no penalty in lost sensitivity. This indicates that a flexible model should be considered, particularly for clinical patients who may have difficulty complying fully with the study task.

Universal Recurrence Time Statistics of Characteristic Earthquakes

NASA Astrophysics Data System (ADS)

Goltz, C.; Turcotte, D. L.; Abaimov, S.; Nadeau, R. M.

2006-12-01

Characteristic earthquakes are defined to occur quasi-periodically on major faults. Do recurrence time statistics of such earthquakes follow a particular statistical distribution? If so, which one? The answer is fundamental and has important implications for hazard assessment. The problem cannot be solved by comparing the goodness of statistical fits as the available sequences are too short. The Parkfield sequence of M ≍ 6 earthquakes, one of the most extensive reliable data sets available, has grown to merely seven events with the last earthquake in 2004, for example. Recently, however, advances in seismological monitoring and improved processing methods have unveiled so-called micro-repeaters, micro-earthquakes which recur exactly in the same location on a fault. It seems plausible to regard these earthquakes as a miniature version of the classic characteristic earthquakes. Micro-repeaters are much more frequent than major earthquakes, leading to longer sequences for analysis. Due to their recent discovery, however, available sequences contain less than 20 events at present. In this paper we present results for the analysis of recurrence times for several micro-repeater sequences from Parkfield and adjacent regions. To improve the statistical significance of our findings, we combine several sequences into one by rescaling the individual sets by their respective mean recurrence intervals and Weibull exponents. This novel approach of rescaled combination yields the most extensive data set possible. We find that the resulting statistics can be fitted well by an exponential distribution, confirming the universal applicability of the Weibull distribution to characteristic earthquakes. A similar result is obtained from rescaled combination, however, with regard to the lognormal distribution.

Flood-tolerant rice reduces yield variability and raises expected yield, differentially benefitting socially disadvantaged groups

PubMed Central

Dar, Manzoor H.; de Janvry, Alain; Emerick, Kyle; Raitzer, David; Sadoulet, Elisabeth

2013-01-01

Approximately 30% of the cultivated rice area in India is prone to crop damage from prolonged flooding. We use a randomized field experiment in 128 villages of Orissa India to show that Swarna-Sub1, a recently released submergence-tolerant rice variety, has significant positive impacts on rice yield when fields are submerged for 7 to 14 days with no yield penalty without flooding. We estimate that Swarna-Sub1 offers an approximate 45% increase in yields over the current popular variety when fields are submerged for 10 days. We show additionally that low-lying areas prone to flooding tend to be more heavily occupied by people belonging to lower caste social groups. Thus, a policy relevant implication of our findings is that flood-tolerant rice can deliver both efficiency gains, through reduced yield variability and higher expected yield, and equity gains in disproportionately benefiting the most marginal group of farmers. PMID:24263095

Crop weather models of barley and spring wheat yield for agrophysical units in North Dakota

NASA Technical Reports Server (NTRS)

Leduc, S. (Principal Investigator)

1982-01-01

Models based on multiple regression were developed to estimate barley yield and spring wheat yield from weather data for Agrophysical units(APU) in North Dakota. The predictor variables are derived from monthly average temperature and monthly total precipitation data at meteorological stations in the cooperative network. The models are similar in form to the previous models developed for Crop Reporting Districts (CRD). The trends and derived variables were the same and the approach to select the significant predictors was similar to that used in developing the CRD models. The APU models show sight improvements in some of the statistics of the models, e.g., explained variation. These models are to be independently evaluated and compared to the previously evaluated CRD models. The comparison will indicate the preferred model area for this application, i.e., APU or CRD.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

[Influence of feeding rumen-protected choline to transition dairy cows. Part 1: metabolism and milk yield].

PubMed

Furken, C; Hoedemaker, M

2014-01-01

The effects of rumen-protected choline (RPC) on energy metabolism and milk production in dairy cows were analyzed. Two hundred and ninety-eight primiparous and multiparous cows of a high producing dairy herd (mean daily milk yield: 32 l) were randomly assigned to control or treatment groups and were fed with 0 or 15 g RPC, respectively, (corresponding to 0 and 60 g/d ReaShure®, respectively) from 21 days before expected calving to 21 days postpartum (p. p.). Blood metabolites were determined for either all cows (glucose, β-hydroxybutyrate [BHB]) or randomly (insulin, insulin-like growth factor-1 [IGF-1], non-esterified fatty acids [NEFA]) during the periparturient period. An index for insulin sensitivity (RQUICKI) was calculated and milk production data (dairy herd improvement tests, 100-days-, 305-days-, milk peak yield, colostrum quality) was analyzed. In the statistical analysis, a distinction was made between the feeding groups and between the parity, and their interactions were analyzed. With the exception of a lower 305-day-milk yield in the treatment group (p < 0.05), the evaluated variables did not show statistically significant differences between the feeding groups and no interactions could be found. In comparison to heifers, multiparous cows had less cases of subclinical ketosis a. p. and p. p. (OR a. p.: 0.178; OR p. p.: 0.310), more of them were above the threshold for somatic cell counts (OR 2.584-3.298), and their milk yields were higher (p < 0.05). Supplementing RPC did not affect the energy metabolism or the milk production in this herd. Further research in other dairy herds should focus on this topic.

Benefits of seasonal forecasts of crop yields

NASA Astrophysics Data System (ADS)

Sakurai, G.; Okada, M.; Nishimori, M.; Yokozawa, M.

2017-12-01

Major factors behind recent fluctuations in food prices include increased biofuel production and oil price fluctuations. In addition, several extreme climate events that reduced worldwide food production coincided with upward spikes in food prices. The stabilization of crop yields is one of the most important tasks to stabilize food prices and thereby enhance food security. Recent development of technologies related to crop modeling and seasonal weather forecasting has made it possible to forecast future crop yields for maize and soybean. However, the effective use of these technologies remains limited. Here we present the potential benefits of seasonal crop-yield forecasts on a global scale for choice of planting day. For this purpose, we used a model (PRYSBI-2) that can well replicate past crop yields both for maize and soybean. This model system uses a Bayesian statistical approach to estimate the parameters of a basic process-based model of crop growth. The spatial variability of model parameters was considered by estimating the posterior distribution of the parameters from historical yield data by using the Markov-chain Monte Carlo (MCMC) method with a resolution of 1.125° × 1.125°. The posterior distributions of model parameters were estimated for each spatial grid with 30 000 MCMC steps of 10 chains each. By using this model and the estimated parameter distributions, we were able to estimate not only crop yield but also levels of associated uncertainty. We found that the global average crop yield increased about 30% as the result of the optimal selection of planting day and that the seasonal forecast of crop yield had a large benefit in and near the eastern part of Brazil and India for maize and the northern area of China for soybean. In these countries, the effects of El Niño and Indian Ocean dipole are large. The results highlight the importance of developing a system to forecast global crop yields.

Do increases in cigarette prices lead to increases in sales of cigarettes with high tar and nicotine yields?

PubMed

Farrelly, Matthew C; Loomis, Brett R; Mann, Nathan H

2007-10-01

We used scanner data on cigarette prices and sales collected from supermarkets across the United States from 1994 to 2004 to test the hypothesis that cigarette prices are positively correlated with sales of cigarettes with higher tar and nicotine content. During this period the average inflation-adjusted price for menthol cigarettes increased 55.8%. Price elasticities from multivariate regression models suggest that this price increase led to an increase of 1.73% in sales-weighted average tar yields and a 1.28% increase in sales-weighted average nicotine yields for menthol cigarettes. The 50.5% price increase of nonmenthol varieties over the same period yielded an estimated increase of 1% in tar per cigarette but no statistically significant increase in nicotine yields. An ordered probit model of the impact of cigarette prices on cigarette strength (ultra-light, light, full flavor, unfiltered) offers an explanation: As cigarette prices increase, the probability that stronger cigarette types will be sold increases. This effect is larger for menthol than for nonmenthol cigarettes. Our results are consistent with earlier population-based cross-sectional and longitudinal studies showing that higher cigarette prices and taxes are associated with increasing consumption of higher-yield cigarettes by smokers.

The yield of colorectal cancer among fast track patients with normocytic and microcytic anaemia.

PubMed

Panagiotopoulou, I G; Fitzrol, D; Parker, R A; Kuzhively, J; Luscombe, N; Wells, A D; Menon, M; Bajwa, F M; Watson, M A

2014-05-01

We receive fast track referrals on the basis of iron deficiency anaemia (IDA) for patients with normocytic anaemia or for patients with no iron studies. This study examined the yield of colorectal cancer (CRC) among fast track patients to ascertain whether awaiting confirmation of IDA is necessary prior to performing bowel investigations. A review was undertaken of 321 and 930 consecutive fast track referrals from Centre A and Centre B respectively. Contingency tables were analysed using Fisher's exact test. Logistic regression analyses were performed to investigate significant predictors of CRC. Overall, 229 patients were included from Centre A and 689 from Centre B. The odds ratio for microcytic anaemia versus normocytic anaemia in the outcome of CRC was 1.3 (95% confidence interval [CI]: 0.5-3.9) for Centre A and 1.6 (95% CI: 0.8-3.3) for Centre B. In a logistic regression analysis (Centre B only), no significant difference in CRC rates was seen between microcytic and normocytic anaemia (adjusted odds ratio: 1.9, 95% CI: 0.9-3.9). There was no statistically significant difference in the yield of CRC between microcytic and normocytic anaemia (p=0.515, Fisher's exact test) in patients with anaemia only and no colorectal symptoms. Finally, CRC cases were seen in both microcytic and normocytic groups with or without low ferritin. There is no significant difference in the yield of CRC between fast track patients with microcytic and normocytic anaemia. This study provides insufficient evidence to support awaiting confirmation of IDA in fast track patients with normocytic anaemia prior to requesting bowel investigations.

Effect of enzyme concentration, addition of water and incubation time on increase in yield of starch from potato.

PubMed

Sit, Nandan; Agrawal, U S; Deka, Sankar C

2014-05-01

Enzymatic treatment process for starch extraction from potato was investigated using cellulase enzyme and compared with conventional process. The effects of three parameters, cellulase enzyme concentration, incubation time and addition of water were evaluated for increase in starch yield as compared to the conventional process i.e., without using enzyme. A two-level full factorial design was used to study the process. The results indicated that all the main parameters and their interactions are statistically significant. Enzyme concentration and incubation time had a positive effect on the increase in starch yield while addition of water had a negative effect. The increase in starch yield ranged from 1.9% at low enzyme concentration and incubation time and high addition of water to a maximum of 70% increase from conventional process in starch yield was achieved when enzyme concentration and incubation time were high and addition of water was low suggesting water present in the ground potato meal is sufficient for access to the enzyme with in the slurry ensuring adequate contact with the substrate.

A systematic review and meta-analysis of acute stroke unit care: What’s beyond the statistical significance?

PubMed Central

2013-01-01

Background The benefits of stroke unit care in terms of reducing death, dependency and institutional care were demonstrated in a 2009 Cochrane review carried out by the Stroke Unit Trialists’ Collaboration. Methods As requested by the Belgian health authorities, a systematic review and meta-analysis of the effect of acute stroke units was performed. Clinical trials mentioned in the original Cochrane review were included. In addition, an electronic database search on Medline, Embase, the Cochrane Central Register of Controlled Trials, and Physiotherapy Evidence Database (PEDro) was conducted to identify trials published since 2006. Trials investigating acute stroke units compared to alternative care were eligible for inclusion. Study quality was appraised according to the criteria recommended by Scottish Intercollegiate Guidelines Network (SIGN) and the GRADE system. In the meta-analysis, dichotomous outcomes were estimated by calculating odds ratios (OR) and continuous outcomes were estimated by calculating standardized mean differences. The weight of a study was calculated based on inverse variance. Results Evidence from eight trials comparing acute stroke unit and conventional care (general medical ward) were retained for the main synthesis and analysis. The findings from this study were broadly in line with the original Cochrane review: acute stroke units can improve survival and independency, as well as reduce the chance of hospitalization and the length of inpatient stay. The improvement with stroke unit care on mortality was less conclusive and only reached borderline level of significance (OR 0.84, 95% CI 0.70 to 1.00, P = 0.05). This improvement became statistically non-significant (OR 0.87, 95% CI 0.74 to 1.03, P = 0.12) when data from two unpublished trials (Goteborg-Ostra and Svendborg) were added to the analysis. After further also adding two additional trials (Beijing, Stockholm) with very short observation periods (until discharge), the

Statistical analysis and yield management in LED design through TCAD device simulation

NASA Astrophysics Data System (ADS)

Létay, Gergö; Ng, Wei-Choon; Schneider, Lutz; Bregy, Adrian; Pfeiffer, Michael

2007-02-01

This paper illustrates how technology computer-aided design (TCAD), which nowadays is an essential part of CMOS technology, can be applied to LED development and manufacturing. In the first part, the essential electrical and optical models inherent to LED modeling are reviewed. The second part of the work describes a methodology to improve the efficiency of the simulation procedure by using the concept of process compact models (PCMs). The last part demonstrates the capabilities of PCMs using an example of a blue InGaN LED. In particular, a parameter screening is performed to find the most important parameters, an optimization task incorporating the robustness of the design is carried out, and finally the impact of manufacturing tolerances on yield is investigated. It is indicated how the concept of PCMs can contribute to an efficient design for manufacturing DFM-aware development.

Characteristics of water-well yields in part of the blue ridge geologic Province in Loudoun County, Virginia

USGS Publications Warehouse

Sutphin, D.M.; Drew, L.J.; Schuenemeyer, J.H.; Burton, W.C.

2001-01-01

Loudoun County, Virginia, which is located about 50 km to the west of Washington, DC, was the site of intensive suburban development during the 1980s and 1990s. In the western half of the county, the source of water for domestic use has been from wells drilled into the fractured crystalline bedrock of the Blue Ridge Geologic Province. A comprehensive digital database that contains information on initial yield, location, depth, elevation, and other data for 3651 wells drilled in this 825.5-km2 area was combined with a digital geologic map to form the basis for a study of geologic and temporal controls on water-well yields. Statistical modeling procedures were used to determine that mean yields for the wells were significantly different as a function of structural setting, genetic rock type, and geologic map unit. The Bonferroni procedure then was used to determine which paired comparisons contributed to these significant differences. The data were divided into 15 temporal drilling increments to determine if the time-dependent trends that exist for the Loudoun County data are similar to those discovered in a previous study of water-well yields in the Pinardville 7.5-min quadrangle, New Hampshire. In both regions, trends, which include increasing proportions of very low yield wells and increasing well depths through time, and the counterintuitive result of increasing mean well yields through time, were similar. In addition, a yield-to-depth curve similar to that discovered in the Pinardville quadrangle was recognized in this study. Thus, the temporal model with a feed-forward-loop mechanism to explain the temporal trends in well characteristics proposed for the New Hampshire study appears to apply to western Loudoun County. ?? 2001 International Association for Mathematical Geology.

Calculating stage duration statistics in multistage diseases.

PubMed

Komarova, Natalia L; Thalhauser, Craig J

2011-01-01

Many human diseases are characterized by multiple stages of progression. While the typical sequence of disease progression can be identified, there may be large individual variations among patients. Identifying mean stage durations and their variations is critical for statistical hypothesis testing needed to determine if treatment is having a significant effect on the progression, or if a new therapy is showing a delay of progression through a multistage disease. In this paper we focus on two methods for extracting stage duration statistics from longitudinal datasets: an extension of the linear regression technique, and a counting algorithm. Both are non-iterative, non-parametric and computationally cheap methods, which makes them invaluable tools for studying the epidemiology of diseases, with a goal of identifying different patterns of progression by using bioinformatics methodologies. Here we show that the regression method performs well for calculating the mean stage durations under a wide variety of assumptions, however, its generalization to variance calculations fails under realistic assumptions about the data collection procedure. On the other hand, the counting method yields reliable estimations for both means and variances of stage durations. Applications to Alzheimer disease progression are discussed.

Determining coding CpG islands by identifying regions significant for pattern statistics on Markov chains.

PubMed

Singer, Meromit; Engström, Alexander; Schönhuth, Alexander; Pachter, Lior

2011-09-23

Recent experimental and computational work confirms that CpGs can be unmethylated inside coding exons, thereby showing that codons may be subjected to both genomic and epigenomic constraint. It is therefore of interest to identify coding CpG islands (CCGIs) that are regions inside exons enriched for CpGs. The difficulty in identifying such islands is that coding exons exhibit sequence biases determined by codon usage and constraints that must be taken into account. We present a method for finding CCGIs that showcases a novel approach we have developed for identifying regions of interest that are significant (with respect to a Markov chain) for the counts of any pattern. Our method begins with the exact computation of tail probabilities for the number of CpGs in all regions contained in coding exons, and then applies a greedy algorithm for selecting islands from among the regions. We show that the greedy algorithm provably optimizes a biologically motivated criterion for selecting islands while controlling the false discovery rate. We applied this approach to the human genome (hg18) and annotated CpG islands in coding exons. The statistical criterion we apply to evaluating islands reduces the number of false positives in existing annotations, while our approach to defining islands reveals significant numbers of undiscovered CCGIs in coding exons. Many of these appear to be examples of functional epigenetic specialization in coding exons.

How Big Was It? Getting at Yield

NASA Astrophysics Data System (ADS)

Pasyanos, M.; Walter, W. R.; Ford, S. R.

2013-12-01

One of the most coveted pieces of information in the wake of a nuclear test is the explosive yield. Determining the yield from remote observations, however, is not necessarily a trivial thing. For instance, recorded observations of seismic amplitudes, used to estimate the yield, are significantly modified by the intervening media, which varies widely, and needs to be properly accounted for. Even after correcting for propagation effects such as geometrical spreading, attenuation, and station site terms, getting from the resulting source term to a yield depends on the specifics of the explosion source model, including material properties, and depth. Some formulas are based on assumptions of the explosion having a standard depth-of-burial and observed amplitudes can vary if the actual test is either significantly overburied or underburied. We will consider the complications and challenges of making these determinations using a number of standard, more traditional methods and a more recent method that we have developed using regional waveform envelopes. We will do this comparison for recent declared nuclear tests from the DPRK. We will also compare the methods using older explosions at the Nevada Test Site with announced yields, material and depths, so that actual performance can be measured. In all cases, we also strive to quantify realistic uncertainties on the yield estimation.

Time series, periodograms, and significance

NASA Astrophysics Data System (ADS)

Hernandez, G.

1999-05-01

The geophysical literature shows a wide and conflicting usage of methods employed to extract meaningful information on coherent oscillations from measurements. This makes it difficult, if not impossible, to relate the findings reported by different authors. Therefore, we have undertaken a critical investigation of the tests and methodology used for determining the presence of statistically significant coherent oscillations in periodograms derived from time series. Statistical significance tests are only valid when performed on the independent frequencies present in a measurement. Both the number of possible independent frequencies in a periodogram and the significance tests are determined by the number of degrees of freedom, which is the number of true independent measurements, present in the time series, rather than the number of sample points in the measurement. The number of degrees of freedom is an intrinsic property of the data, and it must be determined from the serial coherence of the time series. As part of this investigation, a detailed study has been performed which clearly illustrates the deleterious effects that the apparently innocent and commonly used processes of filtering, de-trending, and tapering of data have on periodogram analysis and the consequent difficulties in the interpretation of the statistical significance thus derived. For the sake of clarity, a specific example of actual field measurements containing unevenly-spaced measurements, gaps, etc., as well as synthetic examples, have been used to illustrate the periodogram approach, and pitfalls, leading to the (statistical) significance tests for the presence of coherent oscillations. Among the insights of this investigation are: (1) the concept of a time series being (statistically) band limited by its own serial coherence and thus having a critical sampling rate which defines one of the necessary requirements for the proper statistical design of an experiment; (2) the design of a critical

Applied Behavior Analysis and Statistical Process Control?

ERIC Educational Resources Information Center

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

Statistics Education Research in Malaysia and the Philippines: A Comparative Analysis

ERIC Educational Resources Information Center

Reston, Enriqueta; Krishnan, Saras; Idris, Noraini

2014-01-01

This paper presents a comparative analysis of statistics education research in Malaysia and the Philippines by modes of dissemination, research areas, and trends. An electronic search for published research papers in the area of statistics education from 2000-2012 yielded 20 for Malaysia and 19 for the Philippines. Analysis of these papers showed…

Observation of the baryonic B decay B{sup 0}{yields}{Lambda}{sub c}{sup +}{Lambda}K{sup -}

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

Lees, J. P.; Poireau, V.; Tisserand, V.

2011-10-01

We report the observation of the baryonic B decay B{sup 0}{yields}{Lambda}{sub c}{sup +}{Lambda}K{sup -} with a significance larger than 7 standard deviations based on 471x10{sup 6} BB pairs collected with the BABAR detector at the PEP-II storage ring at SLAC. We measure the branching fraction for the decay B{sup 0}{yields}{Lambda}{sub c}{sup +}{Lambda}K{sup -} to be (3.8{+-}0.8{sub stat}{+-}0.2{sub sys}{+-}1.0{sub {Lambda}}{sub c}{sup +})x10{sup -5}. The uncertainties are statistical, systematic, and due to the uncertainty in the {Lambda}{sub c}{sup +} branching fraction. We find that the {Lambda}{sub c}{sup +}K{sup -} invariant-mass distribution shows an enhancement above 3.5 GeV/c{sup 2}.

A Flexible Approach for the Statistical Visualization of Ensemble Data

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

Potter, K.; Wilson, A.; Bremer, P.

2009-09-29

Scientists are increasingly moving towards ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using multiple numerical models, sampled input conditions and perturbed parameters. While ensemble data sets are a powerful tool for mitigating uncertainty, they pose significant visualization and analysis challenges due to their complexity. We present a collection of overview and statistical displays linked through a high level of interactivity to provide a framework for gaining key scientific insight into the distribution of the simulation results as well as the uncertainty associated with the data. In contrast to methodsmore » that present large amounts of diverse information in a single display, we argue that combining multiple linked statistical displays yields a clearer presentation of the data and facilitates a greater level of visual data analysis. We demonstrate this approach using driving problems from climate modeling and meteorology and discuss generalizations to other fields.« less

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

USGS Publications Warehouse

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

2002-01-01

The New Hampshire Bedrock Aquifer Assessment was designed to provide information that can be used by communities, industry, professional consultants, and other interests to evaluate the ground-water development potential of the fractured-bedrock aquifer in the State. The assessment was done at statewide, regional, and well field scales to identify relations that potentially could increase the success in locating high-yield water supplies in the fractured-bedrock aquifer. statewide, data were collected for well construction and yield information, bedrock lithology, surficial geology, lineaments, topography, and various derivatives of these basic data sets. Regionally, geologic, fracture, and lineament data were collected for the Pinardville and Windham quadrangles in New Hampshire. The regional scale of the study examined the degree to which predictive well-yield relations, developed as part of the statewide reconnaissance investigation, could be improved by use of quadrangle-scale geologic mapping. Beginning in 1984, water-well contractors in the State were required to report detailed information on newly constructed wells to the New Hampshire Department of Environmental Services (NHDES). The reports contain basic data on well construction, including six characteristics used in this study?well yield, well depth, well use, method of construction, date drilled, and depth to bedrock (or length of casing). The NHDES has determined accurate georeferenced locations for more than 20,000 wells reported since 1984. The availability of this large data set provided an opportunity for a statistical analysis of bedrock-well yields. Well yields in the database ranged from zero to greater than 500 gallons per minute (gal/min). Multivariate regression was used as the primary statistical method of analysis because it is the most efficient tool for predicting a single variable with many potentially independent variables. The dependent variable that was explored in this study was the

Statistical crystallography of surface micelle spacing

NASA Technical Reports Server (NTRS)

Noever, David A.

1992-01-01

The aggregation of the recently reported surface micelles of block polyelectrolytes is analyzed using techniques of statistical crystallography. A polygonal lattice (Voronoi mosaic) connects center-to-center points, yielding statistical agreement with crystallographic predictions; Aboav-Weaire's law and Lewis's law are verified. This protocol supplements the standard analysis of surface micelles leading to aggregation number determination and, when compared to numerical simulations, allows further insight into the random partitioning of surface films. In particular, agreement with Lewis's law has been linked to the geometric packing requirements of filling two-dimensional space which compete with (or balance) physical forces such as interfacial tension, electrostatic repulsion, and van der Waals attraction.

Mathematical and statistical models for determining the crop load in grapevine

NASA Astrophysics Data System (ADS)

Alina, Dobrei; Alin, Dobrei; Eleonora, Nistor; Teodor, Cristea; Marius, Boldea; Florin, Sala

2016-06-01

Ensuring a balance between vine crop load and vine vegetative growth is a dynamic process, so it is necessary to develop models for describing this relationship. This study analyzed the interrelationship between the crop load and growing specific parameters (viable buds - VB, dead (frost-injured) buds - DB, total shoots growth-TSG, one-year-old wood - MSG), in two vine grapes varieties: Muscat Ottonel cultivar for wine and Victoria cultivar for fresh grapes. In both varieties interrelationship between the buds number and vegetative growth parameters were described by polynomial functions statistically assured. Using regression analysis it was possible to develop predictive models for one-year-old wood (MSG), an important parameter for the yield and quality of wine grape production, with statistical significance results (R2 = 0.884, p <0.001, F = 45.957 in Muscat Ottonel cultivar and R2 = 0.893, p = 0.001, F = 49.886 in Victoria cultivar).

The impact exploration of agricultural drought on winter wheat yield in the North China Plain

NASA Astrophysics Data System (ADS)

Yang, Jianhua; Wu, Jianjun; Han, Xinyi; Zhou, Hongkui

2017-04-01

Drought is one of the most serious agro-climatic disasters in the North China Plain, which has a great influence on winter wheat yield. Global warming exacerbates the drought trend of this region, so it is important to study the effect of drought on winter wheat yield. In order to assess the drought-induced winter wheat yield losses, SPEI (standardized precipitation evapotranspiration index), the widely used drought index, was selected to quantify the drought from 1981 to 2013. Additionally, the EPIC (Environmental Policy Integrated Climate) crop model was used to simulate winter wheat yield at 47 stations in this region from 1981 to 2013. We analyzed the relationship between winter wheat yield and the SPEI at different time scales in each month during the growing season. The trends of the SPEI and the trends of winter wheat yield at 47 stations over the past 32 years were compared with each other. To further quantify the effect of drought on winter wheat yield, we defined the year that SPEI varied from -0.5 to 0.5 as the normal year, and calculated the average winter wheat yield of the normal years as a reference yield, then calculated the reduction ratios of winter wheat based on the yields mentioned above in severe drought years. As a reference, we compared the results with the reduction ratios calculated from the statistical yield data. The results showed that the 9 to 12-month scales' SPEI in April, May and June had a high correlation with winter wheat yield. The trends of the SPEI and the trends of winter wheat yield over the past 32 years showed a positive correlation (p<0.01) and have similar spatial distributions. The proportion of the stations with the same change trend between the SPEI and winter wheat yield was 70%, indicating that drought was the main factor leading to a decline in winter wheat yield in this region. The reduction ratios based on the simulated yield and the reduction ratios calculated from the statistical yield data have a high positive

Soil Texture and Cultivar Effects on Rice (Oryza sativa, L.) Grain Yield, Yield Components and Water Productivity in Three Water Regimes.

PubMed

Dou, Fugen; Soriano, Junel; Tabien, Rodante E; Chen, Kun

2016-01-01

The objective of this study was to determine the effects of water regime/soil condition (continuous flooding, saturated, and aerobic), cultivar ('Cocodrie' and 'Rondo'), and soil texture (clay and sandy loam) on rice grain yield, yield components and water productivity using a greenhouse trial. Rice grain yield was significantly affected by soil texture and the interaction between water regime and cultivar. Significantly higher yield was obtained in continuous flooding than in aerobic and saturated soil conditions but the latter treatments were comparable to each other. For Rondo, its grain yield has decreased with soil water regimes in the order of continuous flooding, saturated and aerobic treatments. The rice grain yield in clay soil was 46% higher than in sandy loam soil averaged across cultivar and water regime. Compared to aerobic condition, saturated and continuous flooding treatments had greater panicle numbers. In addition, panicle number in clay soil was 25% higher than in sandy loam soil. The spikelet number of Cocodrie was 29% greater than that of Rondo, indicating that rice cultivar had greater effect on spikelet number than soil type and water management. Water productivity was significantly affected by the interaction of water regime and cultivar. Compared to sandy loam soil, clay soil was 25% higher in water productivity. Our results indicated that cultivar selection and soil texture are important factors in deciding what water management option to practice.

Use of remote sensing, geographic information systems, and spatial statistics to assess spatio-temporal population dynamics of Heterodera glycines and soybean yield quantity and quality

NASA Astrophysics Data System (ADS)

Moreira, Antonio Jose De Araujo

Soybean, Glycine max (L.) Merr., is an important source of oil and protein worldwide, and soybean cyst nematode (SCN), Heterodera glycines, is among the most important yield-limiting factors in soybean production worldwide. Early detection of SCN is difficult because soybean plants infected by SCN often do not exhibit visible symptoms. It was hypothesized, however, that reflectance data obtained by remote sensing from soybean canopies may be used to detect plant stress caused by SCN infection. Moreover, reflectance measurements may be related to soybean growth and yield. Two field experiments were conducted from 2000 to 2002 to study the relationships among reflectance data, quantity and quality of soybean yield, and SCN population densities. The best relationships between reflectance and the quantity of soybean grain yield occurred when reflectance data were obtained late August to early September. Similarly, reflectance was best related to seed oil and seed protein content and seed size when measured during late August/early September. Grain quality-reflectance relationships varied spatially and temporally. Reflectance measured early or late in the season had the best relationships with SCN population densities measured at planting. Soil properties likely affected reflectance measurements obtained at the beginning of the season and somehow may have been related to SCN population densities at planting. Reflectance data obtained at the end of the growing season likely was affected by early senescence of SCN-infected soybeans. Spatio-temporal aspects of SCN population densities in both experiments were assessed using spatial statistics and regression analyses. In the 2000 and 2001 growing seasons, spring-to-fall changes in SCN population densities were best related to SCN population densities at planting for both experiments. However, within-season changes in SCN population densities were best related to SCN population densities at harvest for both experiments in

Satellite-based assessment of yield variation and its determinants in smallholder African systems

PubMed Central

Lobell, David B.

2017-01-01

The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest (R2 up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods. PMID:28202728

Satellite-based assessment of yield variation and its determinants in smallholder African systems.

PubMed

Burke, Marshall; Lobell, David B

2017-02-28

The emergence of satellite sensors that can routinely observe millions of individual smallholder farms raises possibilities for monitoring and understanding agricultural productivity in many regions of the world. Here we demonstrate the potential to track smallholder maize yield variation in western Kenya, using a combination of 1-m Terra Bella imagery and intensive field sampling on thousands of fields over 2 y. We find that agreement between satellite-based and traditional field survey-based yield estimates depends significantly on the quality of the field-based measures, with agreement highest ([Formula: see text] up to 0.4) when using precise field measures of plot area and when using larger fields for which rounding errors are smaller. We further show that satellite-based measures are able to detect positive yield responses to fertilizer and hybrid seed inputs and that the inferred responses are statistically indistinguishable from estimates based on survey-based yields. These results suggest that high-resolution satellite imagery can be used to make predictions of smallholder agricultural productivity that are roughly as accurate as the survey-based measures traditionally used in research and policy applications, and they indicate a substantial near-term potential to quickly generate useful datasets on productivity in smallholder systems, even with minimal or no field training data. Such datasets could rapidly accelerate learning about which interventions in smallholder systems have the most positive impact, thus enabling more rapid transformation of rural livelihoods.

An assessment of climate change impacts on maize yields in Hebei Province of China.

PubMed

Chen, Yongfu; Han, Xinru; Si, Wei; Wu, Zhigang; Chien, Hsiaoping; Okamoto, Katsuo

2017-03-01

The climate change impacts on maize yields are quantified in this paper using statistical models with panel data from 3731 farmers' observations across nine sample villages in Hebei Province of China. The marginal impacts of climate change and the simulated impacts on maize yields based on scenarios of Representative Concentration Pathways 2.6, 4.5, 6.0, and 8.5 from the global climate models of Model for Interdisciplinary Research on Climate version 5 (MIROC5) and Meteorological Research Institute Coupled General Circulation Model version 3 (MRI-CGCM3) were then calculated, analyzed, and explained. The results indicate that, first, the most important finding was that climate change impacts on maize yields were significant and a 1°C warming or a 1mm decrease in precipitation resulted in a 150.255kg or a 1.941kg loss in maize yields per hectare, respectively. Second, villages with latitudes of less than 39.832 and longitudes of more than 114.839 in Hebei province suffered losses due to warm weather. Third, the simulated impacts for the full sample are all negative based on scenarios from MIROC5, and their magnitudes are more than those of MRI-CGCM3 are. Based on scenarios in the 2050s, the biggest loss for maize yields per hectare for the full sample accounts for about one-tenth of the mean maize yield from 2004 to 2010, and all of the villages are impacted. Hence, it is important to help farms adopt an adaptation strategy to tackle the risk of loss for maize yields from climate change, and it is necessary to develop agricultural synthesis services as a public adaptation policy at the village level to interact with the adaptation strategy at the farm level. Copyright © 2016 Elsevier B.V. All rights reserved.

Genotypic Variation in Yield, Yield Components, Root Morphology and Architecture, in Soybean in Relation to Water and Phosphorus Supply

PubMed Central

He, Jin; Jin, Yi; Du, Yan-Lei; Wang, Tao; Turner, Neil C.; Yang, Ru-Ping; Siddique, Kadambot H. M.; Li, Feng-Min

2017-01-01

Water shortage and low phosphorus (P) availability limit yields in soybean. Roots play important roles in water-limited and P-deficient environment, but the underlying mechanisms are largely unknown. In this study we determined the responses of four soybean [Glycine max (L.) Merr.] genotypes [Huandsedadou (HD), Bailudou (BLD), Jindou 21 (J21), and Zhonghuang 30 (ZH)] to three P levels [applied 0 (P0), 60 (P60), and 120 (P120) mg P kg-1 dry soil to the upper 0.4 m of the soil profile] and two water treatment [well-watered (WW) and water-stressed (WS)] with special reference to root morphology and architecture, we compared yield and its components, root morphology and root architecture to find out which variety and/or what kind of root architecture had high grain yield under P and drought stress. The results showed that water stress and low P, respectively, significantly reduced grain yield by 60 and 40%, daily water use by 66 and 31%, P accumulation by 40 and 80%, and N accumulation by 39 and 65%. The cultivar ZH with the lowest daily water use had the highest grain yield at P60 and P120 under drought. Increased root length was positively associated with N and P accumulation in both the WW and WS treatments, but not with grain yield under water and P deficits. However, in the WS treatment, high adventitious and lateral root densities were associated with high N and P uptake per unit root length which in turn was significantly and positively associated with grain yield. Our results suggest that (1) genetic variation of grain yield, daily water use, P and N accumulation, and root morphology and architecture were observed among the soybean cultivars and ZH had the best yield performance under P and water limited conditions; (2) water has a major influence on nutrient uptake and grain yield, while additional P supply can modestly increase yields under drought in some soybean genotypes; (3) while conserved water use plays an important role in grain yield under drought

Genotypic Variation in Yield, Yield Components, Root Morphology and Architecture, in Soybean in Relation to Water and Phosphorus Supply.

PubMed

He, Jin; Jin, Yi; Du, Yan-Lei; Wang, Tao; Turner, Neil C; Yang, Ru-Ping; Siddique, Kadambot H M; Li, Feng-Min

2017-01-01

Water shortage and low phosphorus (P) availability limit yields in soybean. Roots play important roles in water-limited and P-deficient environment, but the underlying mechanisms are largely unknown. In this study we determined the responses of four soybean [ Glycine max (L.) Merr.] genotypes [Huandsedadou (HD), Bailudou (BLD), Jindou 21 (J21), and Zhonghuang 30 (ZH)] to three P levels [applied 0 (P0), 60 (P60), and 120 (P120) mg P kg -1 dry soil to the upper 0.4 m of the soil profile] and two water treatment [well-watered (WW) and water-stressed (WS)] with special reference to root morphology and architecture, we compared yield and its components, root morphology and root architecture to find out which variety and/or what kind of root architecture had high grain yield under P and drought stress. The results showed that water stress and low P, respectively, significantly reduced grain yield by 60 and 40%, daily water use by 66 and 31%, P accumulation by 40 and 80%, and N accumulation by 39 and 65%. The cultivar ZH with the lowest daily water use had the highest grain yield at P60 and P120 under drought. Increased root length was positively associated with N and P accumulation in both the WW and WS treatments, but not with grain yield under water and P deficits. However, in the WS treatment, high adventitious and lateral root densities were associated with high N and P uptake per unit root length which in turn was significantly and positively associated with grain yield. Our results suggest that (1) genetic variation of grain yield, daily water use, P and N accumulation, and root morphology and architecture were observed among the soybean cultivars and ZH had the best yield performance under P and water limited conditions; (2) water has a major influence on nutrient uptake and grain yield, while additional P supply can modestly increase yields under drought in some soybean genotypes; (3) while conserved water use plays an important role in grain yield under drought

Integrated model for predicting rice yield with climate change

NASA Astrophysics Data System (ADS)

Park, Jin-Ki; Das, Amrita; Park, Jong-Hwa

2018-04-01

Rice is the chief agricultural product and one of the primary food source. For this reason, it is of pivotal importance for worldwide economy and development. Therefore, in a decision-support-system both for the farmers and in the planning and management of the country's economy, forecasting yield is vital. However, crop yield, which is a dependent of the soil-bio-atmospheric system, is difficult to represent in statistical language. This paper describes a novel approach for predicting rice yield using artificial neural network, spatial interpolation, remote sensing and GIS methods. Herein, the variation in the yield is attributed to climatic parameters and crop health, and the normalized difference vegetation index from MODIS is used as an indicator of plant health and growth. Due importance was given to scaling up the input parameters using spatial interpolation and GIS and minimising the sources of error in every step of the modelling. The low percentage error (2.91) and high correlation (0.76) signifies the robust performance of the proposed model. This simple but effective approach is then used to estimate the influence of climate change on South Korean rice production. As proposed in the RCP8.5 scenario, an upswing in temperature may increase the rice yield throughout South Korea.

Statistical significance approximation in local trend analysis of high-throughput time-series data using the theory of Markov chains.

PubMed

Xia, Li C; Ai, Dongmei; Cram, Jacob A; Liang, Xiaoyi; Fuhrman, Jed A; Sun, Fengzhu

2015-09-21

Local trend (i.e. shape) analysis of time series data reveals co-changing patterns in dynamics of biological systems. However, slow permutation procedures to evaluate the statistical significance of local trend scores have limited its applications to high-throughput time series data analysis, e.g., data from the next generation sequencing technology based studies. By extending the theories for the tail probability of the range of sum of Markovian random variables, we propose formulae for approximating the statistical significance of local trend scores. Using simulations and real data, we show that the approximate p-value is close to that obtained using a large number of permutations (starting at time points >20 with no delay and >30 with delay of at most three time steps) in that the non-zero decimals of the p-values obtained by the approximation and the permutations are mostly the same when the approximate p-value is less than 0.05. In addition, the approximate p-value is slightly larger than that based on permutations making hypothesis testing based on the approximate p-value conservative. The approximation enables efficient calculation of p-values for pairwise local trend analysis, making large scale all-versus-all comparisons possible. We also propose a hybrid approach by integrating the approximation and permutations to obtain accurate p-values for significantly associated pairs. We further demonstrate its use with the analysis of the Polymouth Marine Laboratory (PML) microbial community time series from high-throughput sequencing data and found interesting organism co-occurrence dynamic patterns. The software tool is integrated into the eLSA software package that now provides accelerated local trend and similarity analysis pipelines for time series data. The package is freely available from the eLSA website: http://bitbucket.org/charade/elsa.

Climate Change Impact Uncertainties for Maize in Panama: Farm Information, Climate Projections, and Yield Sensitivities

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; Cecil, L. Dewayne; Horton, Radley M.; Gordon, Roman; McCollum, Raymond (Brown, Douglas); Brown, Douglas; Killough, Brian; Goldberg, Richard; Greeley, Adam P.; Rosenzweig, Cynthia

2011-01-01

We present results from a pilot project to characterize and bound multi-disciplinary uncertainties around the assessment of maize (Zea mays) production impacts using the CERES-Maize crop model in a climate-sensitive region with a variety of farming systems (Panama). Segunda coa (autumn) maize yield in Panama currently suffers occasionally from high water stress at the end of the growing season, however under future climate conditions warmer temperatures accelerate crop maturation and elevated CO (sub 2) concentrations improve water retention. This combination reduces end-of-season water stresses and eventually leads to small mean yield gains according to median projections, although accelerated maturation reduces yields in seasons with low water stresses. Calibrations of cultivar traits, soil profile, and fertilizer amounts are most important for representing baseline yields, however sensitivity to all management factors is reduced in an assessment of future yield changes (most dramatically for fertilizers), suggesting that yield changes may be more generalizable than absolute yields. Uncertainty around General Circulation Model (GCM)s' projected changes in rainfall gain in importance throughout the century, with yield changes strongly correlated with growing season rainfall totals. Climate changes are expected to be obscured by the large inter-annual variations in Panamanian climate that will continue to be the dominant influence on seasonal maize yield into the coming decades. The relatively high (A2) and low (B1) emissions scenarios show little difference in their impact on future maize yields until the end of the century. Uncertainties related to the sensitivity of CERES-Maize to carbon dioxide concentrations have a substantial influence on projected changes, and remain a significant obstacle to climate change impacts assessment. Finally, an investigation into the potential of simple statistical yield emulators based upon key climate variables characterizes the

Variable sensitivity of US maize yield to high temperatures across developmental stages

NASA Astrophysics Data System (ADS)

Butler, E. E.; Huybers, P. J.

2013-12-01

The sensitivity of maize to high temperatures has been widely demonstrated. Furthermore, field work has indicated that reproductive development stages are particularly sensitive to stress, but this relationship has not been quantified across a wide geographic region. Here, the relationship between maize yield and temperature variations is examined as a function of developmental stage. US state-level data from the National Agriculture Statistics Service provide dates for six growing stages: planting, silking, doughing, dented, mature, and harvested. Temperatures that correspond to each developmental stage are then inferred from a network of weather station observations interpolated to the county level, and a multiple linear regression technique is employed to estimate the sensitivity of county yield outcomes to variations in growing-degree days and an analogous measure of high temperatures referred to as killing-degree days. Uncertainties in the transition times between county-level growth stages are accounted for. Results indicate that the silking and dented stages are generally the most sensitive to killing degree days, with silking the most sensitive stage in the US South and dented the most sensitive in the US North. These variable patterns of sensitivity aid in interpreting which weather events are of greatest significance to maize yields and provide some insight into how shifts in planting time or changes in developmental timing would influence the risks associated with exposure to high temperatures.

Consomic mouse strain selection based on effect size measurement, statistical significance testing and integrated behavioral z-scoring: focus on anxiety-related behavior and locomotion.

PubMed

Labots, M; Laarakker, M C; Ohl, F; van Lith, H A

2016-06-29

Selecting chromosome substitution strains (CSSs, also called consomic strains/lines) used in the search for quantitative trait loci (QTLs) consistently requires the identification of the respective phenotypic trait of interest and is simply based on a significant difference between a consomic and host strain. However, statistical significance as represented by P values does not necessarily predicate practical importance. We therefore propose a method that pays attention to both the statistical significance and the actual size of the observed effect. The present paper extends on this approach and describes in more detail the use of effect size measures (Cohen's d, partial eta squared - η p (2) ) together with the P value as statistical selection parameters for the chromosomal assignment of QTLs influencing anxiety-related behavior and locomotion in laboratory mice. The effect size measures were based on integrated behavioral z-scoring and were calculated in three experiments: (A) a complete consomic male mouse panel with A/J as the donor strain and C57BL/6J as the host strain. This panel, including host and donor strains, was analyzed in the modified Hole Board (mHB). The consomic line with chromosome 19 from A/J (CSS-19A) was selected since it showed increased anxiety-related behavior, but similar locomotion compared to its host. (B) Following experiment A, female CSS-19A mice were compared with their C57BL/6J counterparts; however no significant differences and effect sizes close to zero were found. (C) A different consomic mouse strain (CSS-19PWD), with chromosome 19 from PWD/PhJ transferred on the genetic background of C57BL/6J, was compared with its host strain. Here, in contrast with CSS-19A, there was a decreased overall anxiety in CSS-19PWD compared to C57BL/6J males, but not locomotion. This new method shows an improved way to identify CSSs for QTL analysis for anxiety-related behavior using a combination of statistical significance testing and effect

Ion induced electron emission statistics under Agm- cluster bombardment of Ag

NASA Astrophysics Data System (ADS)

Breuers, A.; Penning, R.; Wucher, A.

2018-05-01

The electron emission from a polycrystalline silver surface under bombardment with Agm- cluster ions (m = 1, 2, 3) is investigated in terms of ion induced kinetic excitation. The electron yield γ is determined directly by a current measurement method on the one hand and implicitly by the analysis of the electron emission statistics on the other hand. Successful measurements of the electron emission spectra ensure a deeper understanding of the ion induced kinetic electron emission process, with particular emphasis on the effect of the projectile cluster size to the yield as well as to emission statistics. The results allow a quantitative comparison to computer simulations performed for silver atoms and clusters impinging onto a silver surface.

Improving the yield from fermentative hydrogen production.

PubMed

Kraemer, Jeremy T; Bagley, David M

2007-05-01

Efforts to increase H(2) yields from fermentative H(2) production include heat treatment of the inoculum, dissolved gas removal, and varying the organic loading rate. Although heat treatment kills methanogens and selects for spore-forming bacteria, the available evidence indicates H(2) yields are not maximized compared to bromoethanesulfonate, iodopropane, or perchloric acid pre-treatments and spore-forming acetogens are not killed. Operational controls (low pH, short solids retention time) can replace heat treatment. Gas sparging increases H(2) yields compared to un-sparged reactors, but no relationship exists between the sparging rate and H(2) yield. Lower sparging rates may improve the H(2) yield with less energy input and product dilution. The reasons why sparging improves H(2) yields are unknown, but recent measurements of dissolved H(2) concentrations during sparging suggest the assumption of decreased inhibition of the H(2)-producing enzymes is unlikely. Significant disagreement exists over the effect of organic loading rate (OLR); some studies show relatively higher OLRs improve H(2) yield while others show the opposite. Discovering the reasons for higher H(2) yields during dissolved gas removal and changes in OLR will help improve H(2) yields.

Huffman and linear scanning methods with statistical language models.

PubMed

Roark, Brian; Fried-Oken, Melanie; Gibbons, Chris

2015-03-01

Current scanning access methods for text generation in AAC devices are limited to relatively few options, most notably row/column variations within a matrix. We present Huffman scanning, a new method for applying statistical language models to binary-switch, static-grid typing AAC interfaces, and compare it to other scanning options under a variety of conditions. We present results for 16 adults without disabilities and one 36-year-old man with locked-in syndrome who presents with complex communication needs and uses AAC scanning devices for writing. Huffman scanning with a statistical language model yielded significant typing speedups for the 16 participants without disabilities versus any of the other methods tested, including two row/column scanning methods. A similar pattern of results was found with the individual with locked-in syndrome. Interestingly, faster typing speeds were obtained with Huffman scanning using a more leisurely scan rate than relatively fast individually calibrated scan rates. Overall, the results reported here demonstrate great promise for the usability of Huffman scanning as a faster alternative to row/column scanning.

Simulating and Predicting Cereal Crop Yields in Ethiopia: Model Calibration and Verification

NASA Astrophysics Data System (ADS)

Yang, M.; Wang, G.; Ahmed, K. F.; Eggen, M.; Adugna, B.; Anagnostou, E. N.

2017-12-01

Agriculture in developing countries are extremely vulnerable to climate variability and changes. In East Africa, most people live in the rural areas with outdated agriculture techniques and infrastructure. Smallholder agriculture continues to play a key role in this area, and the rate of irrigation is among the lowest of the world. As a result, seasonal and inter-annual weather patterns play an important role in the spatiotemporal variability of crop yields. This study investigates how various climate variables (e.g., temperature, precipitation, sunshine) and agricultural practice (e.g., fertilization, irrigation, planting date) influence cereal crop yields using a process-based model (DSSAT) and statistical analysis, and focuses on the Blue Nile Basin of Ethiopia. The DSSAT model is driven with meteorological forcing from the ECMWF's latest reanalysis product that cover the past 35 years; the statistical model will be developed by linking the same meteorological reanalysis data with harvest data at the woreda level from the Ethiopian national dataset. Results from this study will set the stage for the development of a seasonal prediction system for weather and crop yields in Ethiopia, which will serve multiple sectors in coping with the agricultural impact of climate variability.

Influence of Cutting Cycle and Spacing on Coppice Sycamore Yield

Treesearch

H. E. Kennedy

1975-01-01

Cutting cycle significantly affected total aboveground dry-weight yields, which were greater with the 2-, 3-, and 4-year cycles than with the I-year. For all cutting cycles, significantly higher yields were obtained with 2- by 5-foot spacings than with 4 by 5. Dry-weight yields ranged from 3,229 pounds per acre per year for the I-year cutting cycle spaced at 4 by 5...

Initial yield to depth relation for water wells drilled into crystalline bedrock - Pinardville quadrangle, New Hampshire

USGS Publications Warehouse

Drew, L.J.; Schuenemeyer, J.H.; Amstrong, T.R.; Sutphin, D.M.

2001-01-01

A model is proposed to explain the statistical relations between the mean initial water well yields from eight time increments from 1984 to 1998 for wells drilled into the crystalline bedrock aquifer system in the Pinardville area of southern New Hampshire and the type of bedrock, mean well depth, and mean well elevation. Statistical analyses show that the mean total yield of drilling increments is positively correlated with mean total well depth and mean well elevation. In addition, the mean total well yield varies with rock type from a minimum of 46.9 L/min (12.4 gpm) in the Damon Pond granite to a maximum of 74.5 L/min (19.7 gpm) in the Permian pegmatite and granite unit. Across the eight drilling increments that comprise 211 wells each, the percentages of very low-yield wells (1.9 L/min [0.5 gpm] or less) and high-yield wells (151.4 L/min [40 gpm] or more) increased, and those of intermediate-yield wells decreased. As housing development progressed during the 1984 to 1998 interval, the mean depth of the wells and their elevations increased, and the mix of percentages of the bedrock types drilled changed markedly. The proposed model uses a feed-forward mechanism to explain the interaction between the increasing mean elevation, mean well depth, and percentages of very low-yielding wells and the mean well yield. The increasing percentages of very low-yielding wells through time and the economics of the housing market may control the system that forces the mean well depths, percentages of high-yield wells, and mean well yields to increase. The reason for the increasing percentages of very low-yield wells is uncertain, but the explanation is believed to involve the complex structural geology and tectonic history of the Pinardville quadrangle.

Effects of Presowing Pulsed Electromagnetic Treatment of Tomato Seed on Growth, Yield, and Lycopene Content

PubMed Central

Efthimiadou, Aspasia; Katsenios, Nikolaos; Papastylianou, Panayiota; Triantafyllidis, Vassilios; Travlos, Ilias; Bilalis, Dimitrios J.

2014-01-01

The use of magnetic field as a presowing treatment has been adopted by researchers as a new environmental friendly technique. The aim of this study was to determine the effect of magnetic field exposure on tomato seeds covering a range of parameters such as transplanting percentage, plant height, shoot diameter, number of leaves per plant, fresh weight, dry weight, number of flowers, yield, and lycopene content. Pulsed electromagnetic field was used for 0, 5, 10, and 15 minutes as a presowing treatment of tomato seeds in a field experiment for two years. Papimi device (amplitude on the order of 12.5 mT) has been used. The use of pulsed electromagnetic field as a presowing treatment was found to enhance plant growth in tomato plants at certain duration of exposure. Magnetic field treatments and especially the exposure of 10 and 15 minutes gave the best results in all measurements, except plant height and lycopene content. Yield per plant was higher in magnetic field treatments, compared to control. MF-15 treatment yield was 80.93% higher than control treatment. Lycopene content was higher in magnetic field treatments, although values showed no statistically significant differences. PMID:25097875

Evidence for B{sup 0}{yields}{rho}{sup 0}{rho}{sup 0} Decays and Implications for the Cabibbo-Kobayashi-Maskawa Angle {alpha}

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

Aubert, B.; Bona, M.; Boutigny, D.

2007-03-16

We search for the decays B{sup 0}{yields}{rho}{sup 0}{rho}{sup 0}, B{sup 0}{yields}{rho}{sup 0}f{sub 0}(980), and B{sup 0}{yields}f{sub 0}(980)f{sub 0}(980) in a sample of about 384x10{sup 6} {upsilon}(4S){yields}BB decays collected with the BABAR detector at the PEP-II asymmetric-energy e{sup +}e{sup -} collider at Stanford Linear Accelerator Center. We find evidence for B{sup 0}{yields}{rho}{sup 0}{rho}{sup 0} with 3.5{sigma} significance and measure the branching fraction B=(1.07{+-}0.33{+-}0.19)x10{sup -6} and longitudinal polarization fraction f{sub L}=0.87{+-}0.13{+-}0.04, where the first uncertainty is statistical, and the second is systematic. The uncertainty on the Cabibbo-Kobayashi-Maskawa quark-mixing matrix unitarity angle {alpha} due to penguin contributions in B{yields}{rho}{rho} decays is 18 deg.more » at the 1{sigma} level. We also set upper limits on the B{sup 0}{yields}{rho}{sup 0}f{sub 0}(980) and B{sup 0}{yields}f{sub 0}(980)f{sub 0}(980) decay rates.« less

Role of the N*(1535) in pp{yields}pp{phi} and {pi}{sup -}p{yields}n{phi} reactions

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

Xie Jujun; Graduate University of Chinese Academy of Sciences, Beijing 100049; Zou Bingsong

2008-01-15

The near-threshold {phi}-meson production in proton-proton and {pi}{sup -}p collisions is studied with the assumption that the production mechanism is due to the sub-N{phi}-threshold N*(1535) resonance. The {pi}{sup 0}-,{eta}-, and {rho}{sup 0}-meson exchanges for proton-proton collisions are considered. It is shown that the contribution to the pp{yields}pp{phi} reaction from the t-channel {pi}{sup 0}-meson exchange is dominant. With a significant N*(1535)N{phi} coupling [g{sub N*(1535)N{phi}}{sup 2}/4{pi}=0.13], both pp{yields}pp{phi} and {pi}{sup -}p{yields}n{phi} data are very well reproduced. The significant coupling of the N*(1535) resonance to N{phi} is compatible with previous indications of a large ss component in the quark wave function of themore » N*(1535) resonance and may be the real origin of the significant enhancement of the {phi} production over the naive OZI-rule predictions.« less

Standardized seawater rearing of chinook salmon smolts to evaluate hatchery practices showed low statistical power

USGS Publications Warehouse

Palmisano, Aldo N.; Elder, N.E.

2001-01-01

We examined, under standardized conditions, seawater survival of chinook salmon Oncorhynchus tshawytscha at the smolt stage to evaluate the experimental hatchery practices applied to their rearing. The experimental rearing practices included rearing fish at different densities; attempting to control bacterial kidney disease with broodstock segregation, erythromycin injection, and an experimental diet; rearing fish on different water sources; and freeze branding the fish. After application of experimental rearing practices in hatcheries, smolts were transported to a rearing facility for about 2-3 months of seawater rearing. Of 16 experiments, 4 yielded statistically significant differences in seawater survival. In general we found that high variability among replicates, plus the low numbers of replicates available, resulted in low statistical power. We recommend including four or five replicates and using ?? = 0.10 in 1-tailed tests of hatchery experiments to try to increase the statistical power to 0.80.

Yield gaps and yield relationships in US soybean production systems

USDA-ARS?s Scientific Manuscript database

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

Statistical Mining of Predictability of Seasonal Precipitation over the United States

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kim, Kyu-Myong; Shen, S. P.

2001-01-01

Results from a new ensemble canonical correlation (ECC) prediction model yield a remarkable (10-20%) increases in baseline prediction skills for seasonal precipitation over the US for all seasons, compared to traditional statistical predictions. While the tropical Pacific, i.e., El Nino, contributes to the largest share of potential predictability in the southern tier States during boreal winter, the North Pacific and the North Atlantic are responsible for enhanced predictability in the northern Great Plains, Midwest and the southwest US during boreal summer. Most importantly, ECC significantly reduces the spring predictability barrier over the conterminous US, thereby raising the skill bar for dynamical predictions.

Antecedents of students' achievement in statistics

NASA Astrophysics Data System (ADS)

Awaludin, Izyan Syazana; Razak, Ruzanna Ab; Harris, Hezlin; Selamat, Zarehan

2015-02-01

The applications of statistics in most fields have been vast. Many degree programmes at local universities require students to enroll in at least one statistics course. The standard of these courses varies across different degree programmes. This is because of students' diverse academic backgrounds in which some comes far from the field of statistics. The high failure rate in statistics courses for non-science stream students had been concerning every year. The purpose of this research is to investigate the antecedents of students' achievement in statistics. A total of 272 students participated in the survey. Multiple linear regression was applied to examine the relationship between the factors and achievement. We found that statistics anxiety was a significant predictor of students' achievement. We also found that students' age has significant effect to achievement. Older students are more likely to achieve lowers scores in statistics. Student's level of study also has a significant impact on their achievement in statistics.

Equilibrium statistical-thermal models in high-energy physics

NASA Astrophysics Data System (ADS)

Tawfik, Abdel Nasser

2014-05-01

We review some recent highlights from the applications of statistical-thermal models to different experimental measurements and lattice QCD thermodynamics that have been made during the last decade. We start with a short review of the historical milestones on the path of constructing statistical-thermal models for heavy-ion physics. We discovered that Heinz Koppe formulated in 1948, an almost complete recipe for the statistical-thermal models. In 1950, Enrico Fermi generalized this statistical approach, in which he started with a general cross-section formula and inserted into it, the simplifying assumptions about the matrix element of the interaction process that likely reflects many features of the high-energy reactions dominated by density in the phase space of final states. In 1964, Hagedorn systematically analyzed the high-energy phenomena using all tools of statistical physics and introduced the concept of limiting temperature based on the statistical bootstrap model. It turns to be quite often that many-particle systems can be studied with the help of statistical-thermal methods. The analysis of yield multiplicities in high-energy collisions gives an overwhelming evidence for the chemical equilibrium in the final state. The strange particles might be an exception, as they are suppressed at lower beam energies. However, their relative yields fulfill statistical equilibrium, as well. We review the equilibrium statistical-thermal models for particle production, fluctuations and collective flow in heavy-ion experiments. We also review their reproduction of the lattice QCD thermodynamics at vanishing and finite chemical potential. During the last decade, five conditions have been suggested to describe the universal behavior of the chemical freeze-out parameters. The higher order moments of multiplicity have been discussed. They offer deep insights about particle production and to critical fluctuations. Therefore, we use them to describe the freeze-out parameters

Use of vegetation health data for estimation of aus rice yield in bangladesh.

PubMed

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991-2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March-April (weeks 8-13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost.

Use of Vegetation Health Data for Estimation of Aus Rice Yield in Bangladesh

PubMed Central

Rahman, Atiqur; Roytman, Leonid; Krakauer, Nir Y.; Nizamuddin, Mohammad; Goldberg, Mitch

2009-01-01

Rice is a vital staple crop for Bangladesh and surrounding countries, with interannual variation in yields depending on climatic conditions. We compared Bangladesh yield of aus rice, one of the main varieties grown, from official agricultural statistics with Vegetation Health (VH) Indices [Vegetation Condition Index (VCI), Temperature Condition Index (TCI) and Vegetation Health Index (VHI)] computed from Advanced Very High Resolution Radiometer (AVHRR) data covering a period of 15 years (1991–2005). A strong correlation was found between aus rice yield and VCI and VHI during the critical period of aus rice development that occurs during March–April (weeks 8–13 of the year), several months in advance of the rice harvest. Stepwise principal component regression (PCR) was used to construct a model to predict yield as a function of critical-period VHI. The model reduced the yield prediction error variance by 62% compared with a prediction of average yield for each year. Remote sensing is a valuable tool for estimating rice yields well in advance of harvest and at a low cost. PMID:22574057

Relations between Brain Structure and Attentional Function in Spina Bifida: Utilization of Robust Statistical Approaches

PubMed Central

Kulesz, Paulina A.; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M.; Francis, David J.

2015-01-01

Objective Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Method Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product moment correlation was compared with four robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator Results All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Conclusions Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PMID:25495830

A heuristic statistical stopping rule for iterative reconstruction in emission tomography.

PubMed

Ben Bouallègue, F; Crouzet, J F; Mariano-Goulart, D

2013-01-01

We propose a statistical stopping criterion for iterative reconstruction in emission tomography based on a heuristic statistical description of the reconstruction process. The method was assessed for MLEM reconstruction. Based on Monte-Carlo numerical simulations and using a perfectly modeled system matrix, our method was compared with classical iterative reconstruction followed by low-pass filtering in terms of Euclidian distance to the exact object, noise, and resolution. The stopping criterion was then evaluated with realistic PET data of a Hoffman brain phantom produced using the GATE platform for different count levels. The numerical experiments showed that compared with the classical method, our technique yielded significant improvement of the noise-resolution tradeoff for a wide range of counting statistics compatible with routine clinical settings. When working with realistic data, the stopping rule allowed a qualitatively and quantitatively efficient determination of the optimal image. Our method appears to give a reliable estimation of the optimal stopping point for iterative reconstruction. It should thus be of practical interest as it produces images with similar or better quality than classical post-filtered iterative reconstruction with a mastered computation time.

Study on paddy rice yield estimation based on multisource data and the Grey system theory

NASA Astrophysics Data System (ADS)

Deng, Wensheng; Wang, Wei; Liu, Hai; Li, Chen; Ge, Yimin; Zheng, Xianghua

2009-10-01

The paddy rice is our important crops. In study of the paddy rice yield estimation, compared with the scholars who usually only take the remote sensing data or meteorology as the influence factors, we combine the remote sensing and the meteorological data to make the monitoring result closer reality. Although the gray system theory has used in many aspects, it is applied very little in paddy rice yield estimation. This study introduces it to the paddy rice yield estimation, and makes the yield estimation model. This can resolve small data sets problem that can not be solved by deterministic model. It selects some regions in Jianghan plain for the study area. The data includes multi-temporal remote sensing image, meteorological and statistic data. The remote sensing data is the 16-day composite images (250-m spatial resolution) of MODIS. The meteorological data includes monthly average temperature, sunshine duration and rain fall amount. The statistical data is the long-term paddy rice yield of the study area. Firstly, it extracts the paddy rice planting area from the multi-temporal MODIS images with the help of GIS and RS. Then taking the paddy rice yield as the reference sequence, MODIS data and meteorological data as the comparative sequence, computing the gray correlative coefficient, it selects the yield estimation factor based on the grey system theory. Finally, using the factors, it establishes the yield estimation model and does the result test. The result indicated that the method is feasible and the conclusion is credible. It can provide the scientific method and reference value to carry on the region paddy rice remote sensing estimation.

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

PubMed

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.

Ethiopian Wheat Yield and Yield Gap Estimation: A Spatial Small Area Integrated Data Approach

NASA Astrophysics Data System (ADS)

Mann, M.; Warner, J.

2015-12-01

Despite the collection of routine annual agricultural surveys and significant advances in GIS and remote sensing products, little econometric research has been undertaken in predicting developing nation's agricultural yields. In this paper, we explore the determinants of wheat output per hectare in Ethiopia during the 2011-2013 Meher crop seasons aggregated to the woreda administrative area. Using a panel data approach, combining national agricultural field surveys with relevant GIS and remote sensing products, the model explains nearly 40% of the total variation in wheat output per hectare across the country. The model also identifies specific contributors to wheat yields that include farm management techniques (eg. area planted, improved seed, fertilizer, irrigation), weather (eg. rainfall), water availability (vegetation and moisture deficit indexes) and policy intervention. Our findings suggest that woredas produce between 9.8 and 86.5% of their potential wheat output per hectare given their altitude, weather conditions, terrain, and plant health. At the median, Amhara, Oromiya, SNNP, and Tigray produce 48.6, 51.5, 49.7, and 61.3% of their local attainable yields, respectively. This research has a broad range of applications, especially from a public policy perspective: identifying causes of yield fluctuations, remotely evaluating larger agricultural intervention packages, and analyzing relative yield potential. Overall, the combination of field surveys with spatial data can be used to identify management priorities for improving production at a variety of administrative levels.

An Extension of the Chi-Square Procedure for Non-NORMAL Statistics, with Application to Solar Neutrino Data

NASA Astrophysics Data System (ADS)

Sturrock, P. A.

2008-01-01

Using the chi-square statistic, one may conveniently test whether a series of measurements of a variable are consistent with a constant value. However, that test is predicated on the assumption that the appropriate probability distribution function (pdf) is normal in form. This requirement is usually not satisfied by experimental measurements of the solar neutrino flux. This article presents an extension of the chi-square procedure that is valid for any form of the pdf. This procedure is applied to the GALLEX-GNO dataset, and it is shown that the results are in good agreement with the results of Monte Carlo simulations. Whereas application of the standard chi-square test to symmetrized data yields evidence significant at the 1% level for variability of the solar neutrino flux, application of the extended chi-square test to the unsymmetrized data yields only weak evidence (significant at the 4% level) of variability.

Rice yields in tropical/subtropical Asia exhibit large but opposing sensitivities to minimum and maximum temperatures

PubMed Central

Welch, Jarrod R.; Vincent, Jeffrey R.; Auffhammer, Maximilian; Moya, Piedad F.; Dobermann, Achim; Dawe, David

2010-01-01

Data from farmer-managed fields have not been used previously to disentangle the impacts of daily minimum and maximum temperatures and solar radiation on rice yields in tropical/subtropical Asia. We used a multiple regression model to analyze data from 227 intensively managed irrigated rice farms in six important rice-producing countries. The farm-level detail, observed over multiple growing seasons, enabled us to construct farm-specific weather variables, control for unobserved factors that either were unique to each farm but did not vary over time or were common to all farms at a given site but varied by season and year, and obtain more precise estimates by including farm- and site-specific economic variables. Temperature and radiation had statistically significant impacts during both the vegetative and ripening phases of the rice plant. Higher minimum temperature reduced yield, whereas higher maximum temperature raised it; radiation impact varied by growth phase. Combined, these effects imply that yield at most sites would have grown more rapidly during the high-yielding season but less rapidly during the low-yielding season if observed temperature and radiation trends at the end of the 20th century had not occurred, with temperature trends being more influential. Looking ahead, they imply a net negative impact on yield from moderate warming in coming decades. Beyond that, the impact would likely become more negative, because prior research indicates that the impact of maximum temperature becomes negative at higher levels. Diurnal temperature variation must be considered when investigating the impacts of climate change on irrigated rice in Asia. PMID:20696908

Stability of agronomic and yield related traits of Jatropha curcas accessions raised from cuttings

NASA Astrophysics Data System (ADS)

Mat, Nurul Hidayah Che; Yaakob, Zahira; Ratnam, Wickneswari

2016-11-01

Monitoring stability of agronomic and yield related traits is important for prediction of crop yields. This study was a latter study for the evaluation of 295 J. curcas individuals representing 21 accessions from eight countries at Biodiesel Research Station of Universiti Kebangsaan Malaysia, Kuala Pilah planted in December 2012. In this study, 183 J. curcas individuals were selected randomly from the population and their growth performance evaluated from December 2013 to December 2014. All the individual plants were raised from cuttings. The yield related data were recorded periodically and performance of each accession was analyzed using Statistical Analysis System (SAS) 9.4. Five traits which were number of fruits per plant (NFPP), number of fruits per inflorescence (NFPI), hundred seed weight (g) (HSW), number of seeds per plant (NSPP) and yield per plant (g) (YPP) showed significant differences among the accessions after two years of planting. Maximum values for each trait were 208 cm for plant height (PH), 31 for number of branches per plant (BPP), 115 for number of inflorescence per plant (NIPP), 582 for NFPP, 7 for NFPI, 307 for number of flowers per inflorescence (NFI), 17 for number of female flowers per inflorescence (NFFPI), 91.6 g for HSW, 1647.1 for NSPP and 927.6 g for YPP. Most of the plants which had performed well in the first year were among the best performers in the second year.

Embryo yield after in vitro fertilization in women undergoing embryo banking for fertility preservation before chemotherapy.

PubMed

Robertson, Audra D; Missmer, Stacey A; Ginsburg, Elizabeth S

2011-02-01

To evaluate embryo yield after IVF in patients undergoing embryo banking before chemotherapy. A retrospective cohort study. Hospital-based academic medical center. Thirty-eight women diagnosed with cancer or autoimmune disease presenting for IVF cycles, with or without intracytoplasmic sperm injection (ICSI), for embryo cryopreservation before any therapy were compared with 921 presumably fertile women undergoing IVF for male factor infertility from January 2001 through October 2007. Standard IVF or ICSI protocol, embryo freezing, and ET. The number of 2 pronuclear (2PN) embryos created and suitable for cryopreservation or transfer. No statistically significant differences were observed between preservation and male factor groups for number of embryos, number of oocytes, or amount of gonadotropin needed to stimulate follicular development. Peak serum E(2) levels were significantly lower for women with disease-seeking fertility preservation. Women facing chemotherapy as treatment for cancer or systemic autoimmune disease infrequently undergo fertility preservation. If offered this potentially fertility-preserving option, these data suggest equivalent embryo yield compared with women with infertile male partners. Our data report no significant complications in subsequent births in those who sought fertility preservation, which is informative and encouraging for these women and their providers. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

Recent changes in county-level corn yield variability in the United States from observations and crop models

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

Leng, Guoyong

The United States is responsible for 35% and 60% of global corn supply and exports. Enhanced supply stability through a reduction in the year-to-year variability of US corn yield would greatly benefit global food security. Important in this regard is to understand how corn yield variability has evolved geographically in the history and how it relates to climatic and non-climatic factors. Results showed that year-to-year variation of US corn yield has decreased significantly during 1980-2010, mainly in Midwest Corn Belt, Nebraska and western arid regions. Despite the country-scale decreasing variability, corn yield variability exhibited an increasing trend in South Dakota,more » Texas and Southeast growing regions, indicating the importance of considering spatial scales in estimating yield variability. The observed pattern is partly reproduced by process-based crop models, simulating larger areas experiencing increasing variability and underestimating the magnitude of decreasing variability. And 3 out of 11 models even produced a differing sign of change from observations. Hence, statistical model which produces closer agreement with observations is used to explore the contribution of climatic and non-climatic factors to the changes in yield variability. It is found that climate variability dominate the change trends of corn yield variability in the Midwest Corn Belt, while the ability of climate variability in controlling yield variability is low in southeastern and western arid regions. Irrigation has largely reduced the corn yield variability in regions (e.g. Nebraska) where separate estimates of irrigated and rain-fed corn yield exist, demonstrating the importance of non-climatic factors in governing the changes in corn yield variability. The results highlight the distinct spatial patterns of corn yield variability change as well as its influencing factors at the county scale. I also caution the use of process-based crop models, which have substantially

Evidence for Direct CP Violation in the Measurement of the Cabbibo-Kobayashi-Maskawa Angle {gamma} with B{sup {+-}}{yields}D(*)K{sup (*){+-}} Decays

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

Amo Sanchez, P. del; Lees, J. P.; Poireau, V.

2010-09-17

We report the measurement of the Cabibbo-Kobayashi-Maskawa CP-violating angle {gamma} through a Dalitz plot analysis of neutral D-meson decays to K{sub S}{sup 0}{pi}{sup +}{pi}{sup -} and K{sub S}{sup 0}K{sup +}K{sup -} produced in the processes B{sup {+-}}{yields}DK{sup {+-}}, B{sup {+-}}{yields}D*K{sup {+-}} with D*{yields}D{pi}{sup 0}, D{gamma}, and B{sup {+-}}{yields}DK*{sup {+-}} with K*{sup {+-}}{yields}K{sub S}{sup 0}{pi}{+-}, using 468 million BB pairs collected by the BABAR detector at the PEP-II asymmetric-energy e{sup +}e{sup -} collider at SLAC. We measure {gamma}=(68{+-}14{+-}4{+-}3) deg. (modulo 180 deg.), where the first error is statistical, the second is the experimental systematic uncertainty, and the third reflects the uncertaintymore » in the description of the neutral D decay amplitudes. This result is inconsistent with {gamma}=0 (no direct CP violation) with a significance of 3.5 standard deviations.« less

Worry, Intolerance of Uncertainty, and Statistics Anxiety

ERIC Educational Resources Information Center

Williams, Amanda S.

2013-01-01

Statistics anxiety is a problem for most graduate students. This study investigates the relationship between intolerance of uncertainty, worry, and statistics anxiety. Intolerance of uncertainty was significantly related to worry, and worry was significantly related to three types of statistics anxiety. Six types of statistics anxiety were…

Reducing statistics anxiety and enhancing statistics learning achievement: effectiveness of a one-minute strategy.

PubMed

Chiou, Chei-Chang; Wang, Yu-Min; Lee, Li-Tze

2014-08-01

Statistical knowledge is widely used in academia; however, statistics teachers struggle with the issue of how to reduce students' statistics anxiety and enhance students' statistics learning. This study assesses the effectiveness of a "one-minute paper strategy" in reducing students' statistics-related anxiety and in improving students' statistics-related achievement. Participants were 77 undergraduates from two classes enrolled in applied statistics courses. An experiment was implemented according to a pretest/posttest comparison group design. The quasi-experimental design showed that the one-minute paper strategy significantly reduced students' statistics anxiety and improved students' statistics learning achievement. The strategy was a better instructional tool than the textbook exercise for reducing students' statistics anxiety and improving students' statistics achievement.

Relation of watershed setting and stream nutrient yields at selected sites in central and eastern North Carolina, 1997-2008

USGS Publications Warehouse

Harden, Stephen L.; Cuffney, Thomas F.; Terziotti, Silvia; Kolb, Katharine R.

2013-01-01

Data collected between 1997 and 2008 at 48 stream sites were used to characterize relations between watershed settings and stream nutrient yields throughout central and eastern North Carolina. The focus of the investigation was to identify environmental variables in watersheds that influence nutrient export for supporting the development and prioritization of management strategies for restoring nutrient-impaired streams. Nutrient concentration data and streamflow data compiled for the 1997 to 2008 study period were used to compute stream yields of nitrate, total nitrogen (N), and total phosphorus (P) for each study site. Compiled environmental data (including variables for land cover, hydrologic soil groups, base-flow index, streams, wastewater treatment facilities, and concentrated animal feeding operations) were used to characterize the watershed settings for the study sites. Data for the environmental variables were analyzed in combination with the stream nutrient yields to explore relations based on watershed characteristics and to evaluate whether particular variables were useful indicators of watersheds having relatively higher or lower potential for exporting nutrients. Data evaluations included an examination of median annual nutrient yields based on a watershed land-use classification scheme developed as part of the study. An initial examination of the data indicated that the highest median annual nutrient yields occurred at both agricultural and urban sites, especially for urban sites having large percentages of point-source flow contributions to the streams. The results of statistical testing identified significant differences in annual nutrient yields when sites were analyzed on the basis of watershed land-use category. When statistical differences in median annual yields were noted, the results for nitrate, total N, and total P were similar in that highly urbanized watersheds (greater than 30 percent developed land use) and (or) watersheds with greater

Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

USGS Publications Warehouse

Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

1999-01-01

Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

Hot-boning enhances cook yield of boneless skinless chicken thighs.

PubMed

Zhuang, H; Bowker, B C; Buhr, R J; Brambila, G Sanchez

2014-06-01

Three experiments were conducted to evaluate the effects of postmortem deboning time on cook yield of boneless skinless chicken thighs. In experiment 1, chicken thigh meat was deboned at 0.75 (hot-bone), 2, and 24 h postmortem (PM) and trimmed to obtain mainly iliotibialis muscle. Samples were cooked directly from a frozen state. Cook yield of the muscle was significantly influenced by PM deboning time. Hot-boned thighs exhibited a 7% greater cook yield than the samples deboned at 24 h. In experiment 2, boneless skinless chicken thighs were deboned at 0.3, 2, and 24 h PM and cooked directly from a fresh, never-frozen state at 24 h PM. Cook yield of the hot-boned thighs was significantly higher than those of the 2 and 24 h deboned samples, which did not differ from each other. In experiment 3, whole legs (thigh + drumstick) were cut from the carcass backbone at 0.3 (hot-cut), 2, and 24 h PM. Thighs were separated from the legs (drumsticks) at either the same time the whole legs were removed from the carcasses or at 24 h PM. Intact thighs (bone in) were cooked fresh at 24 h PM. Color of fresh thigh muscles, cook yield, and Warner-Bratzler shear force of cooked samples were measured. Cook yield of the thighs cut from the backbone before chilling was significantly higher than those cut from the carcasses at 2 and 24 h PM, which did not differ from each other. The PM time at which intact thighs were separated from the leg (drumstick) did not influence cook yield. These results demonstrate that postmortem deboning time can significantly affect cook yield of boneless skinless chicken thigh products. Deboning chicken thighs after chilling reduces the cook yield. Differences in the cook yield of thighs may also result from the removal of whole chicken legs from the carcass backbone. Poultry Science Association Inc.

Significant Linkage for Tourette Syndrome in a Large French Canadian Family

PubMed Central

Mérette, Chantal; Brassard, Andrée; Potvin, Anne; Bouvier, Hélène; Rousseau, François; Émond, Claudia; Bissonnette, Luc; Roy, Marc-André; Maziade, Michel; Ott, Jurg; Caron, Chantal

2000-01-01

Family and twin studies provide strong evidence that genetic factors are involved in the transmission of Gilles de la Tourette syndrome (TS) and related psychiatric disorders. To detect the underlying susceptibility gene(s) for TS, we performed linkage analysis in one large French Canadian family (127 members) from the Charlevoix region, in which 20 family members were definitely affected by TS and 20 others showed related tic disorders. Using model-based linkage analysis, we observed a LOD score of 3.24 on chromosome 11 (11q23). This result was obtained in a multipoint approach involving marker D11S1377, the marker for which significant linkage disequilibrium with TS recently has been detected in an Afrikaner population. Altogether, 25 markers were studied, and, for level of significance, we derived a criterion that took into account the multiple testing arising from the use of three phenotype definitions and three modes of inheritance, a procedure that yielded a LOD score of 3.18. Hence, even after adjustment for multiple testing, the present study shows statistically significant evidence for genetic linkage with TS. PMID:10986045

A comparative statistical study of long-term agroclimatic conditions affecting the growth of US winter wheat: Distributions of regional monthly average precipitation on the Great Plains and the state of Maryland and the effect of agroclimatic conditions on yield in the state of Kansas

NASA Technical Reports Server (NTRS)

Welker, J.

1981-01-01

A histogram analysis of average monthly precipitation over 30 and 84 year periods for both Maryland and Kansas was made and the results compared. A second analysis, a statistical assessment of the effect of average monthly precipitation on Kansas winter wheat yield was made. The data sets covered the three periods of 1941-1970, 1887-1970, and 1887-1921. Analyses of the limited data sets used (only the average monthly precipitation and temperature were correlated against yield) indicated that fall precipitation values, especially those of September and October, were more important to winter wheat yield than were spring values, particularly for the period 1941-1970.

Field warming experiments shed light on the wheat yield response to temperature in China

PubMed Central

Zhao, Chuang; Piao, Shilong; Huang, Yao; Wang, Xuhui; Ciais, Philippe; Huang, Mengtian; Zeng, Zhenzhong; Peng, Shushi

2016-01-01

Wheat growth is sensitive to temperature, but the effect of future warming on yield is uncertain. Here, focusing on China, we compiled 46 observations of the sensitivity of wheat yield to temperature change (SY,T, yield change per °C) from field warming experiments and 102 SY,T estimates from local process-based and statistical models. The average SY,T from field warming experiments, local process-based models and statistical models is −0.7±7.8(±s.d.)% per °C, −5.7±6.5% per °C and 0.4±4.4% per °C, respectively. Moreover, SY,T is different across regions and warming experiments indicate positive SY,T values in regions where growing-season mean temperature is low, and water supply is not limiting, and negative values elsewhere. Gridded crop model simulations from the Inter-Sectoral Impact Model Intercomparison Project appear to capture the spatial pattern of SY,T deduced from warming observations. These results from local manipulative experiments could be used to improve crop models in the future. PMID:27853151

The choice of statistical methods for comparisons of dosimetric data in radiotherapy.

PubMed

Chaikh, Abdulhamid; Giraud, Jean-Yves; Perrin, Emmanuel; Bresciani, Jean-Pierre; Balosso, Jacques

2014-09-18

Novel irradiation techniques are continuously introduced in radiotherapy to optimize the accuracy, the security and the clinical outcome of treatments. These changes could raise the question of discontinuity in dosimetric presentation and the subsequent need for practice adjustments in case of significant modifications. This study proposes a comprehensive approach to compare different techniques and tests whether their respective dose calculation algorithms give rise to statistically significant differences in the treatment doses for the patient. Statistical investigation principles are presented in the framework of a clinical example based on 62 fields of radiotherapy for lung cancer. The delivered doses in monitor units were calculated using three different dose calculation methods: the reference method accounts the dose without tissues density corrections using Pencil Beam Convolution (PBC) algorithm, whereas new methods calculate the dose with tissues density correction for 1D and 3D using Modified Batho (MB) method and Equivalent Tissue air ratio (ETAR) method, respectively. The normality of the data and the homogeneity of variance between groups were tested using Shapiro-Wilks and Levene test, respectively, then non-parametric statistical tests were performed. Specifically, the dose means estimated by the different calculation methods were compared using Friedman's test and Wilcoxon signed-rank test. In addition, the correlation between the doses calculated by the three methods was assessed using Spearman's rank and Kendall's rank tests. The Friedman's test showed a significant effect on the calculation method for the delivered dose of lung cancer patients (p <0.001). The density correction methods yielded to lower doses as compared to PBC by on average (-5 ± 4.4 SD) for MB and (-4.7 ± 5 SD) for ETAR. Post-hoc Wilcoxon signed-rank test of paired comparisons indicated that the delivered dose was significantly reduced using density-corrected methods

Hydrogenated pyrene: Statistical single-carbon loss below the knockout threshold

NASA Astrophysics Data System (ADS)

Wolf, Michael; Giacomozzi, Linda; Gatchell, Michael; de Ruette, Nathalie; Stockett, Mark H.; Schmidt, Henning T.; Cederquist, Henrik; Zettergren, Henning

2016-04-01

An ongoing discussion revolves around the question of what effect hydrogenation has on carbon backbone fragmentation in polycyclic aromatic hydrocarbons (PAHs). In order to shed more light on this issue, we have measured absolute single carbon loss cross sections in collisions between native or hydrogenated pyrene cations (C16H+10+m, m = 0, 6, 16) and He as functions of center-of-mass energies down to 20 eV. Classical molecular dynamics (MD) simulations give further insight into energy transfer processes and also yield m-dependent threshold energies for prompt (femtoseconds) carbon knockout. Such fast, non-statistical fragmentation processes dominate CHx-loss for native pyrene (m = 0), while much slower statistical fragmentation processes contribute significantly to single-carbon loss for the hydrogenated molecules (m = 6 and m = 16). The latter is shown by measurements of large CHx-loss cross sections far below the MD knockout thresholds for C16H+16 and C16H+26. Contribution to the "Atomic Cluster Collisions (7th International Symposium)", edited by Gerardo Delgado Barrio, Andrey Solov'Yov, Pablo Villarreal, Rita Prosmiti.

A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

PubMed

Liu, Wei; Ding, Jinhui

2018-04-01

The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

7 CFR 760.811 - Rates and yields; calculating payments.

Code of Federal Regulations, 2010 CFR

2010-01-01

... from NASS or other sources approved by FSA that show there is a significant difference in yield or value based on a distinct and separate end use of the crop. Despite potential differences in yield or...

7 CFR 760.811 - Rates and yields; calculating payments.

Code of Federal Regulations, 2012 CFR

2012-01-01

... from NASS or other sources approved by FSA that show there is a significant difference in yield or value based on a distinct and separate end use of the crop. Despite potential differences in yield or...

7 CFR 760.811 - Rates and yields; calculating payments.

Code of Federal Regulations, 2011 CFR

2011-01-01

... from NASS or other sources approved by FSA that show there is a significant difference in yield or value based on a distinct and separate end use of the crop. Despite potential differences in yield or...

7 CFR 760.811 - Rates and yields; calculating payments.

Code of Federal Regulations, 2013 CFR

2013-01-01

... from NASS or other sources approved by FSA that show there is a significant difference in yield or value based on a distinct and separate end use of the crop. Despite potential differences in yield or...

7 CFR 760.811 - Rates and yields; calculating payments.

Code of Federal Regulations, 2014 CFR

2014-01-01

... from NASS or other sources approved by FSA that show there is a significant difference in yield or value based on a distinct and separate end use of the crop. Despite potential differences in yield or...

Incorporating uncertainty into the ranking of SPARROW model nutrient yields from Mississippi/Atchafalaya River basin watersheds

USGS Publications Warehouse

Robertson, Dale M.; Schwarz, Gregory E.; Saad, David A.; Alexander, Richard B.

2009-01-01

Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient-reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight-digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from

Null-space and statistical significance of first-arrival traveltime inversion

NASA Astrophysics Data System (ADS)

Morozov, Igor B.

2004-03-01

The strong uncertainty inherent in the traveltime inversion of first arrivals from surface sources is usually removed by using a priori constraints or regularization. This leads to the null-space (data-independent model variability) being inadequately sampled, and consequently, model uncertainties may be underestimated in traditional (such as checkerboard) resolution tests. To measure the full null-space model uncertainties, we use unconstrained Monte Carlo inversion and examine the statistics of the resulting model ensembles. In an application to 1-D first-arrival traveltime inversion, the τ-p method is used to build a set of models that are equivalent to the IASP91 model within small, ~0.02 per cent, time deviations. The resulting velocity variances are much larger, ~2-3 per cent within the regions above the mantle discontinuities, and are interpreted as being due to the null-space. Depth-variant depth averaging is required for constraining the velocities within meaningful bounds, and the averaging scalelength could also be used as a measure of depth resolution. Velocity variances show structure-dependent, negative correlation with the depth-averaging scalelength. Neither the smoothest (Herglotz-Wiechert) nor the mean velocity-depth functions reproduce the discontinuities in the IASP91 model; however, the discontinuities can be identified by the increased null-space velocity (co-)variances. Although derived for a 1-D case, the above conclusions also relate to higher dimensions.

The origin and evolution of safe-yield policies in the Kansas groundwater management districts

USGS Publications Warehouse

Sophocleous, M.

2000-01-01

The management of groundwater resources in Kansas continues to evolve. Declines in the High Plains aquifer led to the establishment of groundwater management districts in the mid-1970s and reduced streamflows prompted the enactment of minimum desirable streamflow standards in the mid-1980s. Nonetheless, groundwater levels and streamflows continued to decline, although at reduced rates compared to premid-1980s rates. As a result, "safe-yield" policies were revised to take into account natural groundwater discharge in the form of stream baseflow. These policies, although a step in the right direction, are deficient in several ways. In addition to the need for more accurate recharge data, pumping-induced streamflow depletion, natural stream losses, and groundwater evapotranspiration need to be accounted for in the revised safe-yield policies. Furthermore, the choice of the 90% flow-duration statistic as a measure of baseflow needs to be reevaluated, as it significantly underestimates mean baseflow estimated from baseflow separation computer programs; moreover, baseflow estimation needs to be refined and validated. ?? 2000 International Association for Mathematical Geology.

Statistical properties of two sine waves in Gaussian noise.

NASA Technical Reports Server (NTRS)

Esposito, R.; Wilson, L. R.

1973-01-01

A detailed study is presented of some statistical properties of a stochastic process that consists of the sum of two sine waves of unknown relative phase and a normal process. Since none of the statistics investigated seem to yield a closed-form expression, all the derivations are cast in a form that is particularly suitable for machine computation. Specifically, results are presented for the probability density function (pdf) of the envelope and the instantaneous value, the moments of these distributions, and the relative cumulative density function (cdf).

A Novel Approach for Forecasting Crop Production and Yield Using Remotely Sensed Satellite Images

NASA Astrophysics Data System (ADS)

Singh, R. K.; Budde, M. E.; Senay, G. B.; Rowland, J.

2017-12-01

Forecasting crop production in advance of crop harvest plays a significant role in drought impact management, improved food security, stabilizing food grain market prices, and poverty reduction. This becomes essential, particularly in Sub-Saharan Africa, where agriculture is a critical source of livelihoods, but lacks good quality agricultural statistical data. With increasing availability of low cost satellite data, faster computing power, and development of modeling algorithms, remotely sensed images are becoming a common source for deriving information for agricultural, drought, and water management. Many researchers have shown that the Normalized Difference Vegetation Index (NDVI), based on red and near-infrared reflectance, can be effectively used for estimating crop production and yield. Similarly, crop production and yield have been closely related to evapotranspiration (ET) also as there are strong linkages between production/yield and transpiration based on plant physiology. Thus, we combined NDVI and ET information from remotely sensed images for estimating total production and crop yield prior to crop harvest for Niger and Burkina Faso in West Africa. We identified the optimum time (dekads 23-29) for cumulating NDVI and ET and developed a new algorithm for estimating crop production and yield. We used the crop data from 2003 to 2008 to calibrate our model and the data from 2009 to 2013 for validation. Our results showed that total crop production can be estimated within 5% of actual production (R2 = 0.98) about 30-45 days before end of the harvest season. This novel approach can be operationalized to provide a valuable tool to decision makers for better drought impact management in drought-prone regions of the world.

Propagation of Significant Figures.

ERIC Educational Resources Information Center

Schwartz, Lowell M.

1985-01-01

Shows that the rules of thumb for propagating significant figures through arithmetic calculations frequently yield misleading results. Also describes two procedures for performing this propagation more reliably than the rules of thumb. However, both require considerably more calculational effort than do the rules. (JN)

Statistical optimization of polysaccharide production by submerged cultivation of Lingzhi or Reishi medicinal mushroom, Ganoderma lucidum (W.Curt.: Fr.) P. Karst. MTCC 1039 (Aphyllophoromycetideae).

PubMed

Baskar, Gurunathan; Sathya, Shree Rajesh K Lakshmi Jai; Jinnah, Riswana Begum; Sahadevan, Renganathan

2011-01-01

Response surface methodology was employed to optimize the concentration of four important cultivation media components such as cottonseed oil cake, glucose, NH4Cl, and MgSO4 for maximum medicinal polysaccharide yield by Lingzhi or Reishi medicinal mushroom, Ganoderma lucidum MTCC 1039 in submerged culture. The second-order polynomial model describing the relationship between media components and polysaccharide yield was fitted in coded units of the variables. The higher value of the coefficient of determination (R2 = 0.953) justified an excellent correlation between media components and polysaccharide yield, and the model fitted well with high statistical reliability and significance. The predicted optimum concentration of the media components was 3.0% cottonseed oil cake, 3.0% glucose, 0.15% NH4Cl, and 0.045% MgSO4, with the maximum predicted polysaccharide yield of 819.76 mg/L. The experimental polysaccharide yield at the predicted optimum media components was 854.29 mg/L, which was 4.22% higher than the predicted yield.

The Brandeis Dice Problem and Statistical Mechanics

NASA Astrophysics Data System (ADS)

van Enk, Steven J.

2014-11-01

Jaynes invented the Brandeis Dice Problem as a simple illustration of the MaxEnt (Maximum Entropy) procedure that he had demonstrated to work so well in Statistical Mechanics. I construct here two alternative solutions to his toy problem. One, like Jaynes' solution, uses MaxEnt and yields an analog of the canonical ensemble, but at a different level of description. The other uses Bayesian updating and yields an analog of the micro-canonical ensemble. Both, unlike Jaynes' solution, yield error bars, whose operational merits I discuss. These two alternative solutions are not equivalent for the original Brandeis Dice Problem, but become so in what must, therefore, count as the analog of the thermodynamic limit, M-sided dice with M → ∞. Whereas the mathematical analogies between the dice problem and Stat Mech are quite close, there are physical properties that the former lacks but that are crucial to the workings of the latter. Stat Mech is more than just MaxEnt.

Climate-Driven Crop Yield and Yield Variability and Climate Change Impacts on the U.S. Great Plains Agricultural Production.

PubMed

Kukal, Meetpal S; Irmak, Suat

2018-02-22

Climate variability and trends affect global crop yields and are characterized as highly dependent on location, crop type, and irrigation. U.S. Great Plains, due to its significance in national food production, evident climate variability, and extensive irrigation is an ideal region of investigation for climate impacts on food production. This paper evaluates climate impacts on maize, sorghum, and soybean yields and effect of irrigation for individual counties in this region by employing extensive crop yield and climate datasets from 1968-2013. Variability in crop yields was a quarter of the regional average yields, with a quarter of this variability explained by climate variability, and temperature and precipitation explained these in singularity or combination at different locations. Observed temperature trend was beneficial for maize yields, but detrimental for sorghum and soybean yields, whereas observed precipitation trend was beneficial for all three crops. Irrigated yields demonstrated increased robustness and an effective mitigation strategy against climate impacts than their non-irrigated counterparts by a considerable fraction. The information, data, and maps provided can serve as an assessment guide for planners, managers, and policy- and decision makers to prioritize agricultural resilience efforts and resource allocation or re-allocation in the regions that exhibit risk from climate variability.

Specific yield: compilation of specific yields for various materials

USGS Publications Warehouse

Johnson, A.I.

1967-01-01

Specific yield is defined as the ratio of (1) the volume of water that a saturated rock or soil will yield by gravity to (2) the total volume of the rock or soft. Specific yield is usually expressed as a percentage. The value is not definitive, because the quantity of water that will drain by gravity depends on variables such as duration of drainage, temperature, mineral composition of the water, and various physical characteristics of the rock or soil under consideration. Values of specific yields nevertheless offer a convenient means by which hydrologists can estimate the water-yielding capacities of earth materials and, as such, are very useful in hydrologic studies. The present report consists mostly of direct or modified quotations from many selected reports that present and evaluate methods for determining specific yield, limitations of those methods, and results of the determinations made on a wide variety of rock and soil materials. Although no particular values are recommended in this report, a table summarizes values of specific yield, and their averages, determined for 10 rock textures. The following is an abstract of the table. [Table

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

USDA-ARS?s Scientific Manuscript database

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

Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

2017-04-01

West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were

Yielding and flow of colloidal glasses.

PubMed

Petekidis, Georgios; Vlassopoulos, Dimitris; Pusey, Peter N

2003-01-01

We investigate the yielding and flow of hard-sphere colloidal glasses by combining rheological measurements with the technique of light scattering echo. The polymethylmethacrylate particles used are sufficiently polydisperse that crystallization is suppressed. Creep and recovery measurements show that the glasses can tolerate surprisingly large strains, up to at least 15%, before yielding irreversibly. We attribute this behaviour to 'cage elasticity', the ability of a particle and its cage of neighbours to retain their identity under quite large distortion. Results from light scattering echo, which measures the extent of irreversible particle rearrangement under oscillatory shear, support the notion of cage elasticity. In the lower concentration glasses we find that particle trajectories are partly reversible under strains which significantly exceed the yield strain.

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

NASA Technical Reports Server (NTRS)

Zhang, Ping; Anderson, Bruce; Tan, Bin; Barlow, Mathew; Myneni, Ranga

2011-01-01

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

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

PubMed

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 < .001). Means of software machine-derived values differed significantly from actual PLT yield, 4.72 × 10 11 vs.6.12 × 10 11 , respectively, (P < .001). The following equation was developed to adjust these values: actual PLT yield= 0.221 + (1.254 × theoretical platelet yield). ROC curve model showed an optimal apheresis device software prediction cut-off of 4.65 × 10 11 to obtain a DP, with a sensitivity of 82.2%, specificity of 93.3%, and an area under the curve (AUC) of 0.909. Trima Accel v6.0 software consistently underestimated PLT yields. 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.

MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

PubMed Central

Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

2014-01-01

Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a

Validation of markers with non-additive effects on milk yield and fertility in Holstein and Jersey cows.

PubMed

Aliloo, Hassan; Pryce, Jennie E; González-Recio, Oscar; Cocks, Benjamin G; Hayes, Ben J

2015-07-22

It has been suggested that traits with low heritability, such as fertility, may have proportionately more genetic variation arising from non-additive effects than traits with higher heritability, such as milk yield. Here, we performed a large genome scan with 408,255 single nucleotide polymorphism (SNP) markers to identify chromosomal regions associated with additive, dominance and epistatic (pairwise additive × additive) variability in milk yield and a measure of fertility, calving interval, using records from a population of 7,055 Holstein cows. The results were subsequently validated in an independent set of 3,795 Jerseys. We identified genomic regions with validated additive effects on milk yield on Bos taurus autosomes (BTA) 5, 14 and 20, whereas SNPs with suggestive additive effects on fertility were observed on BTA 5, 9, 11, 18, 22, 27, 29 and the X chromosome. We also confirmed genome regions with suggestive dominance effects for milk yield (BTA 2, 3, 5, 26 and 27) and for fertility (BTA 1, 2, 3, 7, 23, 25 and 28). A number of significant epistatic effects for milk yield on BTA 14 were found across breeds. However on close inspection, these were likely to be associated with the mutation in the diacylglycerol O-acyltransferase 1 (DGAT1) gene, given that the associations were no longer significant when the additive effect of the DGAT1 mutation was included in the epistatic model. In general, we observed a low statistical power (high false discovery rates and small number of significant SNPs) for non-additive genetic effects compared with additive effects for both traits which could be an artefact of higher dependence on linkage disequilibrium between markers and causative mutations or smaller size of non-additive effects relative to additive effects. The results of our study suggest that individual non-additive effects make a small contribution to the genetic variation of milk yield and fertility. Although we found no individual mutation with large dominance

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

The effect of high concentrations of glufosinate ammonium on the yield components of transgenic spring wheat (Triticum aestivum L.) constitutively expressing the bar gene.

PubMed

Áy, Zoltán; Mihály, Róbert; Cserháti, Mátyás; Kótai, Éva; Pauk, János

2012-01-01

We present an experiment done on a bar(+) wheat line treated with 14 different concentrations of glufosinate ammonium-an effective component of nonselective herbicides-during seed germination in a closed experimental system. Yield components as number of spikes per plant, number of grains per spike, thousand kernel weight, and yield per plant were thoroughly analysed and statistically evaluated after harvesting. We found that a concentration of glufosinate ammonium 5000 times the lethal dose was not enough to inhibit the germination of transgenic plants expressing the bar gene. Extremely high concentrations of glufosinate ammonium caused a bushy phenotype, significantly lower numbers of grains per spike, and thousand kernel weights. Concerning the productivity, we observed that concentrations of glufosinate ammonium 64 times the lethal dose did not lead to yield depression. Our results draw attention to the possibilities implied in the transgenic approaches.

Hydrostatic Stress Effect On the Yield Behavior of Inconel 100

NASA Technical Reports Server (NTRS)

Allen, Phillip A.; Wilson, Christopher D.

2002-01-01

Classical metal plasticity theory assumes that hydrostatic stress has no effect on the yield and postyield behavior of metals. Recent reexaminations of classical theory have revealed a significant effect of hydrostatic stress on the yield behavior of notched geometries. New experiments and nonlinear finite element analyses (FEA) of Inconel 100 (IN 100) equal-arm bend and double-edge notch tension (DENT) test specimens have revealed the effect of internal hydrostatic tensile stresses on yielding. Nonlinear FEA using the von Mises (yielding is independent of hydrostatic stress) and the Drucker-Prager (yielding is linearly dependent on hydrostatic stress) yield functions was performed. In all test cases, the von Mises constitutive model, which is independent of hydrostatic pressure, overestimated the load for a given displacement or strain. Considering the failure displacements or strains, the Drucker-Prager FEMs predicted loads that were 3% to 5% lower than the von Mises values. For the failure loads, the Drucker Prager FEMs predicted strains that were 20% to 35% greater than the von Mises values. The Drucker-Prager yield function seems to more accurately predict the overall specimen response of geometries with significant internal hydrostatic stress influence.

RESPECT-ED: Rates of Pulmonary Emboli (PE) and Sub-Segmental PE with Modern Computed Tomographic Pulmonary Angiograms in Emergency Departments: A Multi-Center Observational Study Finds Significant Yield Variation, Uncorrelated with Use or Small PE Rates.

PubMed

Mountain, David; Keijzers, Gerben; Chu, Kevin; Joseph, Anthony; Read, Catherine; Blecher, Gabriel; Furyk, Jeremy; Bharat, Chrianna; Velusamy, Karthik; Munro, Andrew; Baker, Kylie; Kinnear, Frances; Mukherjee, Ahses; Watkins, Gina; Buntine, Paul; Livesay, Georgia; Fatovich, Daniel

2016-01-01

Overuse of CT Pulmonary Angiograms (CTPA) for diagnosing pulmonary embolism (PE), particularly in Emergency Departments (ED), is considered problematic. Marked variations in positive CTPA rates are reported, with American 4-10% yields driving most concerns. Higher resolution CTPA may increase sub-segmental PE (SSPE) diagnoses, which may be up to 40% false positive. Excessive use and false positives could increase harm vs. benefit. These issues have not been systematically examined outside America. To describe current yield variation and CTPA utilisation in Australasian ED, exploring potential factors correlated with variation. A retrospective multi-centre review of consecutive ED-ordered CTPA using standard radiology reports. ED CTPA report data were inputted onto preformatted data-sheets. The primary outcome was site level yield, analysed both intra-site and against a nominated 15.3% yield. Factors potentially associated with yield were assessed for correlation. Fourteen radiology departments (15 ED) provided 7077 CTPA data (94% ≥64-slice CT); PE were reported in 1028 (yield 14.6% (95%CI 13.8-15.4%; range 9.3-25.3%; site variation p <0.0001) with four sites significantly below and one above the 15.3% target. Admissions, CTPA usage, PE diagnosis rates and size of PE were uncorrelated with yield. Large PE (≥lobar) were 55% (CI: 52.1-58.2%) and SSPE 8.8% (CI: 7.1-10.5%) of positive scans. CTPA usage (0.2-1.5% adult attendances) was correlated (p<0.006) with PE diagnosis but not SSPE: large PE proportions. We found significant intra-site CTPA yield variation within Australasia. Yield was not clearly correlated with CTPA usage or increased small PE rates. Both SSPE and large PE rates were similar to higher yield historical cohorts. CTPA use was considerably below USA 2.5-3% rates. Higher CTPA utilisation was positively correlated with PE diagnoses, but without evidence of increased proportions of small PE. This suggests that increased diagnoses seem to be of

RESPECT-ED: Rates of Pulmonary Emboli (PE) and Sub-Segmental PE with Modern Computed Tomographic Pulmonary Angiograms in Emergency Departments: A Multi-Center Observational Study Finds Significant Yield Variation, Uncorrelated with Use or Small PE Rates

PubMed Central

Chu, Kevin; Joseph, Anthony; Read, Catherine; Blecher, Gabriel; Furyk, Jeremy; Bharat, Chrianna; Velusamy, Karthik; Munro, Andrew; Baker, Kylie; Kinnear, Frances; Mukherjee, Ahses; Watkins, Gina; Buntine, Paul; Livesay, Georgia

2016-01-01

Introduction Overuse of CT Pulmonary Angiograms (CTPA) for diagnosing pulmonary embolism (PE), particularly in Emergency Departments (ED), is considered problematic. Marked variations in positive CTPA rates are reported, with American 4–10% yields driving most concerns. Higher resolution CTPA may increase sub-segmental PE (SSPE) diagnoses, which may be up to 40% false positive. Excessive use and false positives could increase harm vs. benefit. These issues have not been systematically examined outside America. Aims To describe current yield variation and CTPA utilisation in Australasian ED, exploring potential factors correlated with variation. Methods A retrospective multi-centre review of consecutive ED-ordered CTPA using standard radiology reports. ED CTPA report data were inputted onto preformatted data-sheets. The primary outcome was site level yield, analysed both intra-site and against a nominated 15.3% yield. Factors potentially associated with yield were assessed for correlation. Results Fourteen radiology departments (15 ED) provided 7077 CTPA data (94% ≥64-slice CT); PE were reported in 1028 (yield 14.6% (95%CI 13.8–15.4%; range 9.3–25.3%; site variation p <0.0001) with four sites significantly below and one above the 15.3% target. Admissions, CTPA usage, PE diagnosis rates and size of PE were uncorrelated with yield. Large PE (≥lobar) were 55% (CI: 52.1–58.2%) and SSPE 8.8% (CI: 7.1–10.5%) of positive scans. CTPA usage (0.2–1.5% adult attendances) was correlated (p<0.006) with PE diagnosis but not SSPE: large PE proportions. Discussion/ Conclusions We found significant intra-site CTPA yield variation within Australasia. Yield was not clearly correlated with CTPA usage or increased small PE rates. Both SSPE and large PE rates were similar to higher yield historical cohorts. CTPA use was considerably below USA 2.5–3% rates. Higher CTPA utilisation was positively correlated with PE diagnoses, but without evidence of increased proportions

Applications of quantum entropy to statistics

NASA Astrophysics Data System (ADS)

Silver, R. N.; Martz, H. F.

This paper develops two generalizations of the maximum entropy (ME) principle. First, Shannon classical entropy is replaced by von Neumann quantum entropy to yield a broader class of information divergences (or penalty functions) for statistics applications. Negative relative quantum entropy enforces convexity, positivity, non-local extensivity and prior correlations such as smoothness. This enables the extension of ME methods from their traditional domain of ill-posed in-verse problems to new applications such as non-parametric density estimation. Second, given a choice of information divergence, a combination of ME and Bayes rule is used to assign both prior and posterior probabilities. Hyperparameters are interpreted as Lagrange multipliers enforcing constraints. Conservation principles are proposed to act statistical regularization and other hyperparameters, such as conservation of information and smoothness. ME provides an alternative to hierarchical Bayes methods.

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

Seasonal drought predictability in Portugal using statistical-dynamical techniques

NASA Astrophysics Data System (ADS)

Ribeiro, A. F. S.; Pires, C. A. L.

2016-08-01

Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical-dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R2 and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.

Evaluating statistical and clinical significance of intervention effects in single-case experimental designs: an SPSS method to analyze univariate data.

PubMed

Maric, Marija; de Haan, Else; Hogendoorn, Sanne M; Wolters, Lidewij H; Huizenga, Hilde M

2015-03-01

Single-case experimental designs are useful methods in clinical research practice to investigate individual client progress. Their proliferation might have been hampered by methodological challenges such as the difficulty applying existing statistical procedures. In this article, we describe a data-analytic method to analyze univariate (i.e., one symptom) single-case data using the common package SPSS. This method can help the clinical researcher to investigate whether an intervention works as compared with a baseline period or another intervention type, and to determine whether symptom improvement is clinically significant. First, we describe the statistical method in a conceptual way and show how it can be implemented in SPSS. Simulation studies were performed to determine the number of observation points required per intervention phase. Second, to illustrate this method and its implications, we present a case study of an adolescent with anxiety disorders treated with cognitive-behavioral therapy techniques in an outpatient psychotherapy clinic, whose symptoms were regularly assessed before each session. We provide a description of the data analyses and results of this case study. Finally, we discuss the advantages and shortcomings of the proposed method. Copyright © 2014. Published by Elsevier Ltd.

SPATIO-TEMPORAL MODELING OF AGRICULTURAL YIELD DATA WITH AN APPLICATION TO PRICING CROP INSURANCE CONTRACTS

PubMed Central

Ozaki, Vitor A.; Ghosh, Sujit K.; Goodwin, Barry K.; Shirota, Ricardo

2009-01-01

This article presents a statistical model of agricultural yield data based on a set of hierarchical Bayesian models that allows joint modeling of temporal and spatial autocorrelation. This method captures a comprehensive range of the various uncertainties involved in predicting crop insurance premium rates as opposed to the more traditional ad hoc, two-stage methods that are typically based on independent estimation and prediction. A panel data set of county-average yield data was analyzed for 290 counties in the State of Paraná (Brazil) for the period of 1990 through 2002. Posterior predictive criteria are used to evaluate different model specifications. This article provides substantial improvements in the statistical and actuarial methods often applied to the calculation of insurance premium rates. These improvements are especially relevant to situations where data are limited. PMID:19890450

Measurement of fission yields and isomeric yield ratios at IGISOL

NASA Astrophysics Data System (ADS)

Pomp, Stephan; Mattera, Andrea; Rakopoulos, Vasileios; Al-Adili, Ali; Lantz, Mattias; Solders, Andreas; Jansson, Kaj; Prokofiev, Alexander V.; Eronen, Tommi; Gorelov, Dimitri; Jokinen, Ari; Kankainen, Anu; Moore, Iain D.; Penttilä, Heikki; Rinta-Antila, Sami

2018-03-01

Data on fission yields and isomeric yield ratios (IYR) are tools to study the fission process, in particular the generation of angular momentum. We use the IGISOL facility with the Penning trap JYFLTRAP in Jyväskylä, Finland, for such measurements on 232Th and natU targets. Previously published fission yield data from IGISOL concern the 232Th(p,f) and 238U(p,f) reactions at 25 and 50 MeV. Recently, a neutron source, using the Be(p,n) reaction, has been developed, installed and tested. We summarize the results for (p,f) focusing on the first measurement of IYR by direct ion counting. We also present first results for IYR and relative yields for Sn and Sb isotopes in the 128-133 mass range from natU(n,f) based on γ-spectrometry. We find a staggering behaviour in the cumulative yields for Sn and a shift in the independent fission yields for Sb as compared to current evaluations. Plans for the future experimental program on fission yields and IYR measurements are discussed.

Performance studies of GooFit on GPUs vs RooFit on CPUs while estimating the statistical significance of a new physical signal

NASA Astrophysics Data System (ADS)

Di Florio, Adriano

2017-10-01

In order to test the computing capabilities of GPUs with respect to traditional CPU cores a high-statistics toy Monte Carlo technique has been implemented both in ROOT/RooFit and GooFit frameworks with the purpose to estimate the statistical significance of the structure observed by CMS close to the kinematical boundary of the J/ψϕ invariant mass in the three-body decay B + → J/ψϕK +. GooFit is a data analysis open tool under development that interfaces ROOT/RooFit to CUDA platform on nVidia GPU. The optimized GooFit application running on GPUs hosted by servers in the Bari Tier2 provides striking speed-up performances with respect to the RooFit application parallelised on multiple CPUs by means of PROOF-Lite tool. The considerable resulting speed-up, evident when comparing concurrent GooFit processes allowed by CUDA Multi Process Service and a RooFit/PROOF-Lite process with multiple CPU workers, is presented and discussed in detail. By means of GooFit it has also been possible to explore the behaviour of a likelihood ratio test statistic in different situations in which the Wilks Theorem may or may not apply because its regularity conditions are not satisfied.

Effect size and statistical power in the rodent fear conditioning literature - A systematic review.

PubMed

Carneiro, Clarissa F D; Moulin, Thiago C; Macleod, Malcolm R; Amaral, Olavo B

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science.

Diagnostic Yield of CT-Guided Percutaneous Transthoracic Needle Biopsy for Diagnosis of Anterior Mediastinal Masses.

PubMed

Petranovic, Milena; Gilman, Matthew D; Muniappan, Ashok; Hasserjian, Robert P; Digumarthy, Subba R; Muse, Victorine V; Sharma, Amita; Shepard, Jo-Anne O; Wu, Carol C

2015-10-01

The purpose of this study was to evaluate the diagnostic yield and accuracy of CT-guided percutaneous biopsy of anterior mediastinal masses and assess prebiopsy characteristics that may help to select patients with the highest diagnostic yield. Retrospective review of all CT-guided percutaneous biopsies of the anterior mediastinum conducted at our institution from January 2003 through December 2012 was performed to collect data regarding patient demographics, imaging characteristics of biopsied masses, presence of complications, and subsequent surgical intervention or medical treatment (or both). Cytology, core biopsy pathology, and surgical pathology results were recorded. A per-patient analysis was performed using two-tailed t test, Fisher's exact test, and Pearson chi-square test. The study cohort included 52 patients (32 men, 20 women; mean age, 49 years) with mean diameter of mediastinal mass of 6.9 cm. Diagnostic yield of CT-guided percutaneous biopsy was 77% (40/52), highest for thymic neoplasms (100% [11/11]). Non-diagnostic results were seen in 12 of 52 patients (23%), primarily in patients with lymphoma (75% [9/12]). Fine-needle aspiration yielded the correct diagnosis in 31 of 52 patients (60%), and core biopsy had a diagnostic rate of 77% (36/47). None of the core biopsies were discordant with surgical pathology. There was no statistically significant difference between the diagnostic and the nondiagnostic groups in patient age, lesion size, and presence of necrosis. The complication rate was 3.8% (2/52), all small self-resolving pneumothoraces. CT-guided percutaneous biopsy is a safe diagnostic procedure with high diagnostic yield (77%) for anterior mediastinal lesions, highest for thymic neoplasms (100%), and can potentially obviate more invasive procedures.

Do Serum Creatinine Levels Show Clinically Significant Fluctuations on Serial Determinations on the Siemens Advia 1800 Analyzer?

PubMed

Levitan, Daniel; Harper, Aaron E; Sun, Yi; Scarpa Carniello, Jose V; Momeni, Amir; Kagan, Joshua; Alexis, Herol; Eid, Ikram; Harris, Loretta; Marshal, Barbara; Tafani, Edlira; Pincus, Matthew

2017-01-01

The goal of this work was to determine whether there are clinically significant fluctuations in the level of serum creatinine on serial determinations, especially in the borderline range (1.1-1.3 mg/dl), after specimen storage. Sixty-one serum samples were analyzed. They were divided into three categories based on the initial serum creatinine measurement: low (≤1.0 mg/dl), borderline (1.1-1.3 mg/dl), and high (≥1.4 mg/dl). The specimens were stored at 4°C and run on the Siemens Advia 1800 chemistry analyzer on days 1, 3, and 11. Statistical comparisons of the three groups were made using the unpaired t-test, yielding a two-tailed P-value for each group comparison. The P-values ranged from 0.0829 to 0.3892, indicating no statistically significant difference between the standard deviations of each group. Mild-to-moderate fluctuations in precision occur in successive serum creatinine determinations. The overwhelming majority of these fluctuations should not affect clinical decision making. © 2016 Wiley Periodicals, Inc.

Factors Affecting Firm Yield and the Estimation of Firm Yield for Selected Streamflow-Dominated Drinking-Water-Supply Reservoirs in Massachusetts

USGS Publications Warehouse

Waldron, Marcus C.; Archfield, Stacey A.

2006-01-01

Factors affecting reservoir firm yield, as determined by application of the Massachusetts Department of Environmental Protection's Firm Yield Estimator (FYE) model, were evaluated, modified, and tested on 46 streamflow-dominated reservoirs representing 15 Massachusetts drinking-water supplies. The model uses a mass-balance approach to determine the maximum average daily withdrawal rate that can be sustained during a period of record that includes the 1960s drought-of-record. The FYE methodology to estimate streamflow to the reservoir at an ungaged site was tested by simulating streamflow at two streamflow-gaging stations in Massachusetts and comparing the simulated streamflow to the observed streamflow. In general, the FYE-simulated flows agreed well with observed flows. There were substantial deviations from the measured values for extreme high and low flows. A sensitivity analysis determined that the model's streamflow estimates are most sensitive to input values for average annual precipitation, reservoir drainage area, and the soil-retention number-a term that describes the amount of precipitation retained by the soil in the basin. The FYE model currently provides the option of using a 1,000-year synthetic record constructed by randomly sampling 2-year blocks of concurrent streamflow and precipitation records 500 times; however, the synthetic record has the potential to generate records of precipitation and streamflow that do not reflect the worst historical drought in Massachusetts. For reservoirs that do not have periods of drawdown greater than 2 years, the bootstrap does not offer any additional information about the firm yield of a reservoir than the historical record does. For some reservoirs, the use of a synthetic record to determine firm yield resulted in as much as a 30-percent difference between firm-yield values from one simulation to the next. Furthermore, the assumption that the synthetic traces of streamflow are statistically equivalent to the

Statistical analysis of target acquisition sensor modeling experiments

NASA Astrophysics Data System (ADS)

Deaver, Dawne M.; Moyer, Steve

2015-05-01

The U.S. Army RDECOM CERDEC NVESD Modeling and Simulation Division is charged with the development and advancement of military target acquisition models to estimate expected soldier performance when using all types of imaging sensors. Two elements of sensor modeling are (1) laboratory-based psychophysical experiments used to measure task performance and calibrate the various models and (2) field-based experiments used to verify the model estimates for specific sensors. In both types of experiments, it is common practice to control or measure environmental, sensor, and target physical parameters in order to minimize uncertainty of the physics based modeling. Predicting the minimum number of test subjects required to calibrate or validate the model should be, but is not always, done during test planning. The objective of this analysis is to develop guidelines for test planners which recommend the number and types of test samples required to yield a statistically significant result.

Optimization of grapevine yield by applying mathematical models to obtain quality wine products

NASA Astrophysics Data System (ADS)

Alina, Dobrei; Alin, Dobrei; Eleonora, Nistor; Teodor, Cristea; Marius, Boldea; Florin, Sala

2016-06-01

Relationship between the crop load and the grape yield and quality is a dynamic process, specific for wine cultivars and for fresh consumption varieties. Modeling these relations is important for the improvement of technological works. This study evaluated the interrelationship of crop load (B - buds number) and several production parameters (Y - yield; S - sugar; A - acidity; GaI - Glucoacidimetric index; AP - alcoholic potential; F - flavorings, WA - wine alcohol; SR - sugar residue, in Muscat Ottonel wine cultivar and Y - yield; S - sugar; A - acidity; GaI - Glucoacidimetric Index; CP - commercial production; BS - berries size in the Victoria table grape cultivar). In both varieties have been identified correlations between the independent variable (B - buds number as a result of pruning and training practices) and quality parameters analyzed (r = -0.699 for B vsY relationship; r = 0.961 for the relationship B vs S; r = -0.959 for B vs AP relationship; r = 0.743 for the relationship Y vs S, p <0.01, in the Muscat Ottonel cultivar, respectively r = -0.907 for relationship B vs Y; r = -0.975 for B vs CP relationship; r = -0.971 for relationship B vs BS; r = 0.990 for CP vs BS relationship in the Victoria cultivar. Through regression analysis were obtained models that describe the variation concerning production and quality parameters in relation to the independent variable (B - buds number) with statistical significance results.

Quantitative Research on the Relationship between Yield of Winter Wheat and Agroclimatological Resources—the Case Study from Yanzhou District, Shandong Province, China

NASA Astrophysics Data System (ADS)

Yan, Maoling; Liu, Pingzeng; Zhang, Chao; Zheng, Yong; Wang, Xizhi; Zhang, Yan; Chen, Weijie; Zhao, Rui

2018-01-01

Agroclimatological resources provide material and energy for agricultural production. This study is aimed to analyze the impact of selected climate factors change on wheat yield over the different growth period applied quantitatively method, by comparing two different time division modules of wheat growth cycle- monthly empirical-statistical multiple regression models ( From October to June of next year ) and growth stage empirical-statistical multiple regression models (Including sowing stage, seedling stage, tillering stage, overwintering period, regreening period, jointing stage, heading stage, maturity stage) analysis of relationship between agrometeorological data and growth stage records and winter wheat production in Yanzhou, Shandong Province of China. Correlation analysis(CA)was done for 35 years (from 1981 to 2015) between crop yield and corresponding weather parameters including daily mean temperature, sunshine duration, and average daily precipitation selected from 18 different meteorological factors. The results shows that the greatest impact on the winter wheat yield is the precipitation overwintering period in this area, each 1mm increase in daily mean rainfall was associated with 201.64 kg/hm2 lowered output. Moreover, the temperature and sunshine duration in heading period and maturity stage also exert significant influence on the output, every 1°C increase in daily mean temperature was associated with 199.85kg/hm2 adding output, every 1h increase in mean sunshine duration was associated with 130.68kg/hm2 reduced output. Comparing with the results of experiment which using months as step sizes and using farming as step sizes was in better agreement with the fluctuation in meteorological yield, offered a better explanation on the growth mechanism of wheat. Eventually the results indicated that 3 factors affects the yield during different growing periods of wheat in different extent and provided more specific reference to guide the agricultural

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

NASA Astrophysics Data System (ADS)

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.

Sex differences in discriminative power of volleyball game-related statistics.

PubMed

João, Paulo Vicente; Leite, Nuno; Mesquita, Isabel; Sampaio, Jaime

2010-12-01

To identify sex differences in volleyball game-related statistics, the game-related statistics of several World Championships in 2007 (N=132) were analyzed using the software VIS from the International Volleyball Federation. Discriminant analysis was used to identify the game-related statistics which better discriminated performances by sex. Analysis yielded an emphasis on fault serves (SC = -.40), shot spikes (SC = .40), and reception digs (SC = .31). Specific robust numbers represent that considerable variability was evident in the game-related statistics profile, as men's volleyball games were better associated with terminal actions (errors of service), and women's volleyball games were characterized by continuous actions (in defense and attack). These differences may be related to the anthropometric and physiological differences between women and men and their influence on performance profiles.

Apparent Yield Strength of Hot-Pressed SiCs

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

Daloz, William L; Wereszczak, Andrew A; Jadaan, Osama M.

2008-01-01

Apparent yield strengths (YApp) of four hot-pressed silicon carbides (SiC-B, SiC-N,SiC-HPN, and SiC-SC-1RN) were estimated using diamond spherical or Hertzian indentation. The von Mises and Tresca criteria were considered. The developed test method was robust, simple and quick to execute, and thusly enabled the acquisition of confident sampling statistics. The choice of indenter size, test method, and method of analysis are described. The compressive force necessary to initiate apparent yielding was identified postmortem using differential interference contrast (or Nomarski) imaging with an optical microscope. It was found that the YApp of SiC-HPN (14.0 GPa) was approximately 10% higher than themore » equivalently valued YApp of SiC-B, SiC-N, and SiC-SC-1RN. This discrimination in YApp shows that the use of this test method could be insightful because there were no differences among the average Knoop hardnesses of the four SiC grades.« less

On Statistical Analysis of Neuroimages with Imperfect Registration

PubMed Central

Kim, Won Hwa; Ravi, Sathya N.; Johnson, Sterling C.; Okonkwo, Ozioma C.; Singh, Vikas

2016-01-01

A variety of studies in neuroscience/neuroimaging seek to perform statistical inference on the acquired brain image scans for diagnosis as well as understanding the pathological manifestation of diseases. To do so, an important first step is to register (or co-register) all of the image data into a common coordinate system. This permits meaningful comparison of the intensities at each voxel across groups (e.g., diseased versus healthy) to evaluate the effects of the disease and/or use machine learning algorithms in a subsequent step. But errors in the underlying registration make this problematic, they either decrease the statistical power or make the follow-up inference tasks less effective/accurate. In this paper, we derive a novel algorithm which offers immunity to local errors in the underlying deformation field obtained from registration procedures. By deriving a deformation invariant representation of the image, the downstream analysis can be made more robust as if one had access to a (hypothetical) far superior registration procedure. Our algorithm is based on recent work on scattering transform. Using this as a starting point, we show how results from harmonic analysis (especially, non-Euclidean wavelets) yields strategies for designing deformation and additive noise invariant representations of large 3-D brain image volumes. We present a set of results on synthetic and real brain images where we achieve robust statistical analysis even in the presence of substantial deformation errors; here, standard analysis procedures significantly under-perform and fail to identify the true signal. PMID:27042168

Statistical Significance and Baseline Monitoring.

DTIC Science & Technology

1984-07-01

impacted at once........................... 24 6 Observed versus nominal a levels for multivariate tests of data sets (50 runs of 4 groups each...cumulative proportion of the observations found for each nominal level. The results of the comparisons of the observed versus nominal a levels for the...a values are always higher than nominal levels. Virtual- . .,ly all nominal a levels are below 0.20. In other words, the discriminant analysis models

The Statistical Fermi Paradox

NASA Astrophysics Data System (ADS)

Maccone, C.

In this paper is provided the statistical generalization of the Fermi paradox. The statistics of habitable planets may be based on a set of ten (and possibly more) astrobiological requirements first pointed out by Stephen H. Dole in his book Habitable planets for man (1964). The statistical generalization of the original and by now too simplistic Dole equation is provided by replacing a product of ten positive numbers by the product of ten positive random variables. This is denoted the SEH, an acronym standing for “Statistical Equation for Habitables”. The proof in this paper is based on the Central Limit Theorem (CLT) of Statistics, stating that the sum of any number of independent random variables, each of which may be ARBITRARILY distributed, approaches a Gaussian (i.e. normal) random variable (Lyapunov form of the CLT). It is then shown that: 1. The new random variable NHab, yielding the number of habitables (i.e. habitable planets) in the Galaxy, follows the log- normal distribution. By construction, the mean value of this log-normal distribution is the total number of habitable planets as given by the statistical Dole equation. 2. The ten (or more) astrobiological factors are now positive random variables. The probability distribution of each random variable may be arbitrary. The CLT in the so-called Lyapunov or Lindeberg forms (that both do not assume the factors to be identically distributed) allows for that. In other words, the CLT "translates" into the SEH by allowing an arbitrary probability distribution for each factor. This is both astrobiologically realistic and useful for any further investigations. 3. By applying the SEH it is shown that the (average) distance between any two nearby habitable planets in the Galaxy may be shown to be inversely proportional to the cubic root of NHab. This distance is denoted by new random variable D. The relevant probability density function is derived, which was named the "Maccone distribution" by Paul Davies in

Projected changes in significant wave height toward the end of the 21st century: Northeast Atlantic

NASA Astrophysics Data System (ADS)

Aarnes, Ole Johan; Reistad, Magnar; Breivik, Øyvind; Bitner-Gregersen, Elzbieta; Ingolf Eide, Lars; Gramstad, Odin; Magnusson, Anne Karin; Natvig, Bent; Vanem, Erik

2017-04-01

Wind field ensembles from six CMIP5 models force wave model time slices of the northeast Atlantic over the last three decades of the 20th and the 21st centuries. The future wave climate is investigated by considering the RCP4.5 and RCP8.5 emission scenarios. The CMIP5 model selection is based on their ability to reconstruct the present (1971-2000) extratropical cyclone activity, but increased spatial resolution has also been emphasized. In total, the study comprises 35 wave model integrations, each about 30 years long, in total more than 1000 years. Here annual statistics of significant wave height are analyzed, including mean parameters and upper percentiles. There is general agreement among all models considered that the mean significant wave height is expected to decrease by the end of the 21st century. This signal is statistically significant also for higher percentiles, but less evident for annual maxima. The RCP8.5 scenario yields the strongest reduction in wave height. The exception to this is the north western part of the Norwegian Sea and the Barents Sea, where receding ice cover gives longer fetch and higher waves. The upper percentiles are reduced less than the mean wave height, suggesting that the future wave climate has higher variance than the historical period.

Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.

PubMed

Liu, Hongcheng; Yao, Tao; Li, Runze; Ye, Yinyu

2017-11-01

This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S 3 ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S 3 ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S 3 ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

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

NASA Astrophysics Data System (ADS)

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 < 150 km) from these explosions. This methodology is then applied to data recorded from a large sample of the 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.

Teaching Statistics in Biology: Using Inquiry-based Learning to Strengthen Understanding of Statistical Analysis in Biology Laboratory Courses

PubMed Central

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754

Teaching statistics in biology: using inquiry-based learning to strengthen understanding of statistical analysis in biology laboratory courses.

PubMed

Metz, Anneke M

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.

Evidence for B{yields}K{eta}'{gamma} decays at Belle

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

Wedd, R.; Barberio, E.; Limosani, A.

2010-06-01

We present the results of a search for the radiative decay B{yields}K{eta}{sup '{gamma}} and find evidence for B{sup +{yields}}K{sup +{eta}'{gamma}} decays at the 3.3 standard deviation level with a partial branching fraction of (3.6{+-}1.2{+-}0.4)x10{sup -6}, where the first error is statistical and the second systematic. This measurement is restricted to the region of combined K{eta}{sup '} invariant mass less than 3.4 GeV/c{sup 2}. A 90% confidence level upper limit of 6.4x10{sup -6} is obtained for the partial branching fraction of the decay B{sup 0{yields}}K{sup 0{eta}'{gamma}} in the same K{eta}{sup '} invariant mass region. These results are obtained from a 605more » fb{sup -1} data sample containing 657x10{sup 6}BB pairs collected at the {Upsilon}(4S) resonance with the Belle detector at the KEKB asymmetric-energy e{sup +}e{sup -} collider.« less

Relations between volumetric measures of brain structure and attentional function in spina bifida: utilization of robust statistical approaches.

PubMed

Kulesz, Paulina A; Tian, Siva; Juranek, Jenifer; Fletcher, Jack M; Francis, David J

2015-03-01

Weak structure-function relations for brain and behavior may stem from problems in estimating these relations in small clinical samples with frequently occurring outliers. In the current project, we focused on the utility of using alternative statistics to estimate these relations. Fifty-four children with spina bifida meningomyelocele performed attention tasks and received MRI of the brain. Using a bootstrap sampling process, the Pearson product-moment correlation was compared with 4 robust correlations: the percentage bend correlation, the Winsorized correlation, the skipped correlation using the Donoho-Gasko median, and the skipped correlation using the minimum volume ellipsoid estimator. All methods yielded similar estimates of the relations between measures of brain volume and attention performance. The similarity of estimates across correlation methods suggested that the weak structure-function relations previously found in many studies are not readily attributable to the presence of outlying observations and other factors that violate the assumptions behind the Pearson correlation. Given the difficulty of assembling large samples for brain-behavior studies, estimating correlations using multiple, robust methods may enhance the statistical conclusion validity of studies yielding small, but often clinically significant, correlations. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Sodium bisulfite improves rhizome yield and quality in Paris polyphylla.

PubMed

Yu, Kun; Wang, Yan; Wei, Jian-Rong; Ma, Qing; Wang, Bu-Qiong; Yang, Chang-Hong; Wang, Ming-Hui; Yu, Dan; Li, Jia-Ru

2010-03-01

Rhizomes of the perennial herb Paris polyphylla have been used in traditional Chinese medicine for hundreds of years. Agricultural production of the rhizomes requires 7-10 years, which is too long to meet the demand of the medicinal industry. Therefore, studies on improving the yield of the herb and shortening the culturing period are imperative. The present work aimed to investigate the effect of sodium bisulfite (NaHSO (3)) on rhizome yield and quality, as well as some related metabolic features of P. polyphylla. The rhizome yield was improved by NaHSO (3) treatment in long-term experiments conducted during 2006 and 2007, with 2 mM NaHSO (3) giving the highest yield. HPLC analysis revealed that NaHSO (3) treatment increased the total saponin content (49 %), including three pennogenin glycosides and two diosgenin glycosides. In a short-term experiment, NaHSO (3) treatment resulted in an enhanced net photosynthetic rate (Pn) for about 4 days without significant changes in the chlorophyll or carotenoid content. The total soluble sugars and sucrose contents in the leaves also significantly increased after 2 mM NaHSO (3) treatment, whereas the starch content changed only slightly. The activities of the enzymes involved in ammonium assimilation (glutamine synthetase [GS] and glutamate dehydrogenase [GDH]) were not significantly influenced. In a long-term experiment, chlorophylls and carotenoids were not significantly affected, and neither was the starch content in leaves, but the total soluble sugars and sucrose contents in leaves increased significantly. The NaHSO (3) treatment significantly increased GS and GDH activities. These results indicate that NaHSO (3) treatment improved the rhizome yield in P. polyphylla, not only through enhancement of Pn but also by improving carbohydrate accumulation and ammonium assimilation. The increased saponin content after NaHSO (3) treatment was indicative of high rhizome quality. (c) Georg Thieme Verlag KG Stuttgart . New York.

When is Chemical Similarity Significant? The Statistical Distribution of Chemical Similarity Scores and Its Extreme Values

PubMed Central

Baldi, Pierre

2010-01-01

As repositories of chemical molecules continue to expand and become more open, it becomes increasingly important to develop tools to search them efficiently and assess the statistical significance of chemical similarity scores. Here we develop a general framework for understanding, modeling, predicting, and approximating the distribution of chemical similarity scores and its extreme values in large databases. The framework can be applied to different chemical representations and similarity measures but is demonstrated here using the most common binary fingerprints with the Tanimoto similarity measure. After introducing several probabilistic models of fingerprints, including the Conditional Gaussian Uniform model, we show that the distribution of Tanimoto scores can be approximated by the distribution of the ratio of two correlated Normal random variables associated with the corresponding unions and intersections. This remains true also when the distribution of similarity scores is conditioned on the size of the query molecules in order to derive more fine-grained results and improve chemical retrieval. The corresponding extreme value distributions for the maximum scores are approximated by Weibull distributions. From these various distributions and their analytical forms, Z-scores, E-values, and p-values are derived to assess the significance of similarity scores. In addition, the framework allows one to predict also the value of standard chemical retrieval metrics, such as Sensitivity and Specificity at fixed thresholds, or ROC (Receiver Operating Characteristic) curves at multiple thresholds, and to detect outliers in the form of atypical molecules. Numerous and diverse experiments carried in part with large sets of molecules from the ChemDB show remarkable agreement between theory and empirical results. PMID:20540577

Estimation of rice yield affected by drought and relation between rice yield and TVDI

NASA Astrophysics Data System (ADS)

Hongo, C.; Tamura, E.; Sigit, G.

2016-12-01

Impact of climate change is not only seen on food production but also on food security and sustainable development of society. Adaptation to climate change is a pressing issue throughout the world to reduce the risks along with the plans and strategies for food security and sustainable development. As a key adaptation to the climate change, agricultural insurance is expected to play an important role in stabilizing agricultural production through compensating the losses caused by the climate change. As the adaptation, the Government of Indonesia has launched agricultural insurance program for damage of rice by drought, flood and pest and disease. The Government started a pilot project in 2013 and this year the pilot project has been extended to 22 provinces. Having the above as background, we conducted research on development of new damage assessment method for rice using remote sensing data which could be used for evaluation of damage ratio caused by drought in West Java, Indonesia. For assessment of the damage ratio, estimation of rice yield is a key. As the result of our study, rice yield affected by drought in dry season could be estimated at level of 1 % significance using SPOT 7 data taken in 2015, and the validation result was 0.8t/ha. Then, the decrease ratio in rice yield about each individual paddy field was calculated using data of the estimated result and the average yield of the past 10 years. In addition, TVDI (Temperature Vegetation Dryness Index) which was calculated from Landsat8 data in heading season indicated the dryness in low yield area. The result suggests that rice yield was affected by irrigation water shortage around heading season as a result of the decreased precipitation by El Nino. Through our study, it becomes clear that the utilization of remote sensing data can be promising for assessment of the damage ratio of rice production precisely, quickly and quantitatively, and also it can be incorporated into the insurance procedures.

Meteor trail footprint statistics

NASA Astrophysics Data System (ADS)

Mui, S. Y.; Ellicott, R. C.

Footprint statistics derived from field-test data are presented. The statistics are the probability that two receivers will lie in the same footprint. The dependence of the footprint statistics on the transmitter range, link orientation, and antenna polarization are examined. Empirical expressions for the footprint statistics are presented. The need to distinguish the instantaneous footprint, which is the area illuminated at a particular instant, from the composite footprint, which is the total area illuminated during the lifetime of the meteor trail, is explained. The statistics for the instantaneous and composite footprints have been found to be similar. The only significant difference lies in the parameter that represents the probability of two colocated receivers being in the same footprint. The composite footprint statistics can be used to calculate the space diversity gain of a multiple-receiver system. The instantaneous footprint statistics are useful in the evaluation of the interference probability in a network of meteor burst communication nodes.

Effect size and statistical power in the rodent fear conditioning literature – A systematic review

PubMed Central

Macleod, Malcolm R.

2018-01-01

Proposals to increase research reproducibility frequently call for focusing on effect sizes instead of p values, as well as for increasing the statistical power of experiments. However, it is unclear to what extent these two concepts are indeed taken into account in basic biomedical science. To study this in a real-case scenario, we performed a systematic review of effect sizes and statistical power in studies on learning of rodent fear conditioning, a widely used behavioral task to evaluate memory. Our search criteria yielded 410 experiments comparing control and treated groups in 122 articles. Interventions had a mean effect size of 29.5%, and amnesia caused by memory-impairing interventions was nearly always partial. Mean statistical power to detect the average effect size observed in well-powered experiments with significant differences (37.2%) was 65%, and was lower among studies with non-significant results. Only one article reported a sample size calculation, and our estimated sample size to achieve 80% power considering typical effect sizes and variances (15 animals per group) was reached in only 12.2% of experiments. Actual effect sizes correlated with effect size inferences made by readers on the basis of textual descriptions of results only when findings were non-significant, and neither effect size nor power correlated with study quality indicators, number of citations or impact factor of the publishing journal. In summary, effect sizes and statistical power have a wide distribution in the rodent fear conditioning literature, but do not seem to have a large influence on how results are described or cited. Failure to take these concepts into consideration might limit attempts to improve reproducibility in this field of science. PMID:29698451

Observation of B{sup 0}{yields}{lambda}{lambda}K{sup 0} and B{sup 0}{yields}{lambda}{lambda}K*{sup 0} at Belle

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

Chang, Y.-W.; Wang, M.-Z.; Chao, Y.

2009-03-01

We study the charmless decays B{yields}{lambda}{lambda}h, where h stands for {pi}{sup +}, K{sup +}, K{sup 0},K*{sup +}, or K*{sup 0}, using a 605 fb{sup -1} data sample collected at the {upsilon}(4S) resonance with the Belle detector at the KEKB asymmetric energy e{sup +}e{sup -} collider. We observe B{sup 0}{yields}{lambda}{lambda}K{sup 0} and B{sup 0}{yields}{lambda}{lambda}K*{sup 0} with branching fractions of (4.76{sub -0.68}{sup +0.84}(stat){+-}0.61(syst))x10{sup -6} and (2.46{sub -0.72}{sup +0.87}{+-}0.34)x10{sup -6}, respectively. The significances of these signals in the threshold-mass enhanced mass region, M{sub {lambda}}{sub {lambda}}<2.85 GeV/c{sup 2}, are 12.4{sigma} and 9.3{sigma}, respectively. We also update the branching fraction B(B{sup +}{yields}{lambda}{lambda}K{sup +})=(3.38{sub -0.36}{sup +0.41}{+-}0.41)x10{supmore » -6} with better accuracy, and report the following measurement or 90% confidence level upper limit in the threshold-mass-enhanced region: B(B{sup +}{yields}{lambda}{lambda}K*{sup +})=(2.19{sub -0.88}{sup +1.13}{+-}0.33)x10{sup -6} with 3.7{sigma} significance; B(B{sup +}{yields}{lambda}{lambda}{pi}{sup +})<0.94x10{sup -6}. A related search for B{sup 0}{yields}{lambda}{lambda}D{sup 0} yields a branching fraction B(B{sup 0}{yields}{lambda}{lambda}D{sup 0})=(1.05{sub -0.44}{sup +0.57}{+-}0.14)x10{sup -5}. This may be compared with the large, {approx}10{sup -4}, branching fraction observed for B{sup 0}{yields}ppD{sup 0}. The M{sub {lambda}}{sub {lambda}} enhancements near threshold and related angular distributions for the observed modes are also reported.« less

Wedgeleaf ceanothus canopy does not affect total herbage yield

Treesearch

Vernon J. Gaylord; Stanley E. Westfall

1971-01-01

A major browse plant in the central California foothills, wedgeleaf ceanothus (Ceanothus cuneatus) is used by a variety of animals. The canopy effect of the species was studied on the San Joaquin Experimental Range. Total herbage yield was not significantly affected by the canopy. But herbage yields of some individual species were affected by both...

Use of Taguchi methodology to enhance the yield of caffeine removal with growing cultures of Pseudomonas pseudoalcaligenes.

PubMed

Ashengroph, Morahem; Ababaf, Sajad

2014-12-01

Microbial caffeine removal is a green solution for treatment of caffeinated products and agro-industrial effluents. We directed this investigation to optimizing a bio-decaffeination process with growing cultures of Pseudomonas pseudoalcaligenes through Taguchi methodology which is a structured statistical approach that can be lowered variations in a process through Design of Experiments (DOE). Five parameters, i.e. initial fructose, tryptone, Zn(+2) ion and caffeine concentrations and also incubation time selected and an L16 orthogonal array was applied to design experiments with four 4-level factors and one 3-level factor (4(4) × 1(3)). Data analysis was performed using the statistical analysis of variance (ANOVA) method. Furthermore, the optimal conditions were determined by combining the optimal levels of the significant factors and verified by a confirming experiment. Measurement of residual caffeine concentration in the reaction mixture was performed using high-performance liquid chromatography (HPLC). Use of Taguchi methodology for optimization of design parameters resulted in about 86.14% reduction of caffeine in 48 h incubation when 5g/l fructose, 3 mM Zn(+2) ion and 4.5 g/l of caffeine are present in the designed media. Under the optimized conditions, the yield of degradation of caffeine (4.5 g/l) by the native strain of Pseudomonas pseudoalcaligenes TPS8 has been increased from 15.8% to 86.14% which is 5.4 fold higher than the normal yield. According to the experimental results, Taguchi methodology provides a powerful methodology for identifying the favorable parameters on caffeine removal using strain TPS8 which suggests that the approach also has potential application with similar strains to improve the yield of caffeine removal from caffeine containing solutions.

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

NASA Astrophysics Data System (ADS)

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.

Statistical lamb wave localization based on extreme value theory

NASA Astrophysics Data System (ADS)

Harley, Joel B.

2018-04-01

Guided wave localization methods based on delay-and-sum imaging, matched field processing, and other techniques have been designed and researched to create images that locate and describe structural damage. The maximum value of these images typically represent an estimated damage location. Yet, it is often unclear if this maximum value, or any other value in the image, is a statistically significant indicator of damage. Furthermore, there are currently few, if any, approaches to assess the statistical significance of guided wave localization images. As a result, we present statistical delay-and-sum and statistical matched field processing localization methods to create statistically significant images of damage. Our framework uses constant rate of false alarm statistics and extreme value theory to detect damage with little prior information. We demonstrate our methods with in situ guided wave data from an aluminum plate to detect two 0.75 cm diameter holes. Our results show an expected improvement in statistical significance as the number of sensors increase. With seventeen sensors, both methods successfully detect damage with statistical significance.

Genetic Parameters And Selection Response For Yield Traits In Bread Wheat Under Irrigated And Rainfed Environments

NASA Astrophysics Data System (ADS)

Khalil, Iftikhar Hussain; at-ur-Rahman, Hiday; Khan, Imran

2008-01-01

A set of 22 F5:7 experimental wheat lines along with four check cultivars (Dera-98, Fakhr-e-Sarhad, Ghaznavi-98 and Tatara) were evaluated as independent experiments under irrigated and rainfed environments using a randomized complete block design at NWFP Agricultural University, Peshawar during 2004-05. The two environments were statistically different for days to heading and spike length only. Highly significant genetic variability existed among the wheat lines (P<0.01) in the combined analysis across environments for all traits. Genotype×environment interactions were non-significant for all traits except 1000-grain weight indicating consistent performance of wheat genotypes across the two environments. Wheat lines and check cultivars were 2 to 5 days early in heading under rainfed environment compared to the irrigated. Plant height, spike length, 1000-grain weight, biological and grain yields were generally reduced under rainfed environment. Genetic variances were of greater magnitude than environmental variances for most of the traits in both environments. The heritability estimates were of higher magnitude (0.74 to 0.96) for days to heading, plant height, spike length, biological and grain yield, while medium (0.31 to 0.51) for 1000-grain weight. Selection differentials were negative for heading (-7.3 days in irrigated vs -9.4 days in rainfed) and plant height (-9.0 cm in irrigated vs -8.7 cm in rainfed) indicating possibility of selecting wheat genotypes with early heading and short plant stature. Positive selection differentials of 1.3 vs 1.6 cm for spike length, 3.8 vs 3.4 g for 1000-grain weight, 2488.2 vs 3139.7 kg ha-1 for biological yield and 691.6 vs 565.4 kg ha-1 for grain yield at 20% selection intensity were observed under irrigated and rainfed environments, respectively. Expected selection responses were 7.98 vs 8.91 days for heading, 8.20 vs 9.52 cm for plant height, 1.01 vs 1.61 cm for spike length, 2.12 vs 1.15 g for 1000-grain weight, 1655

Using NOAA/AVHRR based remote sensing data and PCR method for estimation of Aus rice yield in Bangladesh

NASA Astrophysics Data System (ADS)

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

2015-06-01

Rice is a dominant food crop of Bangladesh accounting about 75 percent of agricultural land use for rice cultivation and currently Bangladesh is the world's fourth largest rice producing country. Rice provides about two-third of total calorie supply and about one-half of the agricultural GDP and one-sixth of the national income in Bangladesh. Aus is one of the main rice varieties in Bangladesh. Crop production, especially rice, the main food staple, is the most susceptible to climate change and variability. Any change in climate will, thus, increase uncertainty regarding rice production as climate is major cause year-to-year variability in rice productivity. This paper shows the application of remote sensing data for estimating Aus rice yield in Bangladesh using official statistics of rice yield with real time acquired satellite data from Advanced Very High Resolution Radiometer (AVHRR) sensor and Principal Component Regression (PCR) method was used to construct a model. The simulated result was compared with official agricultural statistics showing that the error of estimation of Aus rice yield was less than 10%. Remote sensing, therefore, is a valuable tool for estimating crop yields well in advance of harvest, and at a low cost.

Streamwise evolution of statistical events and the triple correlation in a model wind turbine array

NASA Astrophysics Data System (ADS)

Viestenz, Kyle; Cal, Raúl Bayoán

2013-11-01

Hot-wire anemometry data, obtained from a wind tunnel experiment containing a 3 × 3 wind turbine array, are used to conditionally average the Reynolds stresses. Nine profiles at the centerline behind the array are analyzed to characterize the turbulent velocity statistics of the wake flow. Quadrant analysis yields statistical events occurring in the wake of the wind farm, where quadrants 2 and 4 produce ejections and sweeps, respectively. A balance between these quadrants is expressed via the ΔSo parameter, which attains a maximum value at the bottom tip and changes sign near the top tip of the rotor. These are then associated to the triple correlation term present in the turbulent kinetic energy equation of the fluctuations. The development of these various quantities is assessed in light of wake remediation, energy transport and possess significance in closure models. National Science Foundation: ECCS-1032647.

Statistical Modeling for Radiation Hardness Assurance: Toward Bigger Data

NASA Technical Reports Server (NTRS)

Ladbury, R.; Campola, M. J.

2015-01-01

New approaches to statistical modeling in radiation hardness assurance are discussed. These approaches yield quantitative bounds on flight-part radiation performance even in the absence of conventional data sources. This allows the analyst to bound radiation risk at all stages and for all decisions in the RHA process. It also allows optimization of RHA procedures for the project's risk tolerance.

The effects of planting methods and head pruning on seed yield and yield components of medicinal pumpkin (Cucurbita pepo subsp. Pepo convar. Pepo var. styriaca) at low temperature areas.

PubMed

Bahrami, R Nikkhah; Khodadadi, M; Pirivatlo, S Piry; Hassanpanah, D

2009-03-15

This experiment carried out to evaluate the effects of planting methods (seed sowing and transplanting) and head pruning (no pruning, pruning after 12th node and pruning after 16th node) on yield and yield components such as number of branches (sub-branches) per plant, fruits per plant, growth, fruit size, weight of fresh fruit, weight of seeds per fruit, number of seeds per fruit and seed yield of medicinal pumpkin. The experiment was carried out based of factorial experiment with Randomized Completely Blocks Design (RCBD) by three replications in Ardabil Agricultural and Natural Resources Researches Station at 2007. Seedlings were grown in heated greenhouse. When the climatic condition became suitable and seedlings were at the four leaves stage, both seeds and seedlings were planted at the same time in the farm. Maintenance operations were done during the growth season. Head pruning treatments were done the forecast time. The results showed that the planting methods had significant effect on the number of ripen fruits per plant, fruits diameter, weight of seeds per fruit, weight of 1000 seeds and seed yield and had no significant effect on the other traits. Also the results indicated that head pruning treatments had significant effects on the number of branches per plant, growth and seed yield and no significant on the other traits. In this experiment the most seed yield (997.8 kg ha(-1)) obtained from transplanting method with head pruning after 12th node and the least seed yield obtained from control.

Measurement of CP observables in B{sup {+-}{yields}D}{sub CP}K{sup {+-}}decays and constraints on the CKM angle {gamma}

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

Amo Sanchez, P. del; Lees, J. P.; Poireau, V.

Using the entire sample of 467x10{sup 6} {Upsilon}(4S){yields}BB decays collected with the BABAR detector at the PEP-II asymmetric-energy B factory at the SLAC National Accelerator Laboratory, we perform an analysis of B{sup {+-}}{yields}DK{sup {+-}}decays, using decay modes in which the neutral D meson decays to either CP-eigenstates or non-CP-eigenstates. We measure the partial decay rate charge asymmetries for CP-even and CP-odd D final states to be A{sub CP+}=0.25{+-}0.06{+-}0.02 and A{sub CP-}=-0.09{+-}0.07{+-}0.02, respectively, where the first error is the statistical and the second is the systematic uncertainty. The parameter A{sub CP+} is different from zero with a significance of 3.6 standardmore » deviations, constituting evidence for direct CP violation. We also measure the ratios of the charged-averaged B partial decay rates in CP and non-CP decays, R{sub CP+}=1.18{+-}0.09{+-}0.05 and R{sub CP-}=1.07{+-}0.08{+-}0.04. We infer frequentist confidence intervals for the angle {gamma} of the unitarity triangle, for the strong phase difference {delta}{sub B}, and for the amplitude ratio r{sub B}, which are related to the B{sup -}{yields}DK{sup -} decay amplitude by r{sub B}e{sup i({delta}{sub B}-{gamma})}=A(B{sup -}{yields}D{sup 0}K{sup -})/A(B{sup -}{yields}D{sup 0}K{sup -}). Including statistical and systematic uncertainties, we obtain 0.24

A Technology-Based Statistical Reasoning Assessment Tool in Descriptive Statistics for Secondary School Students

ERIC Educational Resources Information Center

Chan, Shiau Wei; Ismail, Zaleha

2014-01-01

The focus of assessment in statistics has gradually shifted from traditional assessment towards alternative assessment where more attention has been paid to the core statistical concepts such as center, variability, and distribution. In spite of this, there are comparatively few assessments that combine the significant three types of statistical…

The yield and post-yield behavior of high-density polyethylene

NASA Technical Reports Server (NTRS)

Semeliss, M. A.; Wong, R.; Tuttle, M. E.

1990-01-01

An experimental and analytical evaluation was made of the yield and post-yield behavior of high-density polyethylene, a semi-crystalline thermoplastic. Polyethylene was selected for study because it is very inexpensive and readily available in the form of thin-walled tubes. Thin-walled tubular specimens were subjected to axial loads and internal pressures, such that the specimens were subjected to a known biaxial loading. A constant octahederal shear stress rate was imposed during all tests. The measured yield and post-yield behavior was compared with predictions based on both isotropic and anisotropic models. Of particular interest was whether inelastic behavior was sensitive to the hydrostatic stress level. The major achievements and conclusions reached are discussed.

How to read a paper. Statistics for the non-statistician. II: "Significant" relations and their pitfalls.

PubMed

Greenhalgh, T

1997-08-16

It is possible to be seriously misled by taking the statistical competence (and/or the intellectual honesty) of authors for granted. Some common errors committed (deliberately or inadvertently) by the authors of papers are given in the final box.

Assessing the effects of changes in land use and climate on runoff and sediment yields from a watershed in the Loess Plateau of China.

PubMed

Zuo, Depeng; Xu, Zongxue; Yao, Wenyi; Jin, Shuangyan; Xiao, Peiqing; Ran, Dachuan

2016-02-15

The changes in runoff and sediment load in the Loess Plateau of China have received considerable attention owing to their dramatic decline during recent decades. In this paper, the impacts of land-use and climate changes on water and sediment yields in the Huangfuchuan River basin (HFCRB) of the Loess Plateau are investigated by combined usage of statistical tests, hydrological modeling, and land-use maps. The temporal trends and abrupt changes in runoff and sediment loads during 1954-2012 are detected by using non-parametric Mann-Kendall and Pettitt tests. The land-use changes between 1980 and 2005 are determined by using transition matrix analysis, and the effects of land-use and climate changes on water and sediment yields are assessed by using the Soil and Water Assessment Tool (SWAT) hydrological model and four scenarios, respectively. The results show significant decreasing trends in both annual runoff and sediment loads, whereas slightly decreasing and significantly increasing trends are detected for annual precipitation and air temperature, respectively. 1984 is identified as the dividing year of the study period. The land-use changes between 1980 and 2005 show significant effects of the Grain for Green Project in China. Both land-use change and climate change have greater impact on the reduction of sediment yield than that of water. Water and sediment yields in the upstream region show more significant decreases than those in the downstream region under different effects. The results obtained in this study can provide useful information for water resource planning and management as well as soil and water conservation in the Loess Plateau region. Copyright © 2015 Elsevier B.V. All rights reserved.

A comparison of economic performance between high-yielding temperate breeds and zebu-crossbreds on smallholder dairy farms in Southern Malawi with particular focus on reproductive performance.

PubMed

Gazzarin, Christian; Banda, M C; Lips, M

2018-04-23

As in other sub-Saharan African countries, purebred dairy genetics such as Holsteins were imported to Malawi. The study investigated their economic performance by comparing them with local Zebu-crossbreds based on 131 smallholder dairy farm observations from Southern Malawi. High-yielding purebred cows and crossbred cows showed no significant differences in lactation yield and calving interval. Looking at the farms' actual costs, by-products such as maize bran clearly dominated the cost structure for both breeds, but crossbreeds showed significantly lower concentrate costs. While there was no statistically significant difference in income for both breed types, a substantial share (23%) of farms under investigation shows negative incomes. Based on survey data, two typical farms were established representing standard costs with homogenous assumptions such as identical milk price. The comparison of typical farms covering the full dairy system clearly indicated that crossbred dairy cows outperformed purebreds. In addition, a simulation of a shorter calving interval for both typical farms revealed a substantial positive impact on income for both breed types with more than 30% increase. We conclude that focusing on crossbreds in combination with improved feeding and fertility management offers a more promising strategy for smallholder dairy farms in Southern Malawi than just acquiring high-yielding purebreds.

How to read a paper. Statistics for the non-statistician. II: "Significant" relations and their pitfalls.

PubMed Central

Greenhalgh, T.

1997-01-01

It is possible to be seriously misled by taking the statistical competence (and/or the intellectual honesty) of authors for granted. Some common errors committed (deliberately or inadvertently) by the authors of papers are given in the final box. PMID:9277611

An adapted yield criterion for the evolution of subsequent yield surfaces

NASA Astrophysics Data System (ADS)

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.

Texture analysis with statistical methods for wheat ear extraction

NASA Astrophysics Data System (ADS)

Bakhouche, M.; Cointault, F.; Gouton, P.

2007-01-01

In agronomic domain, the simplification of crop counting, necessary for yield prediction and agronomic studies, is an important project for technical institutes such as Arvalis. Although the main objective of our global project is to conceive a mobile robot for natural image acquisition directly in a field, Arvalis has proposed us first to detect by image processing the number of wheat ears in images before to count them, which will allow to obtain the first component of the yield. In this paper we compare different texture image segmentation techniques based on feature extraction by first and higher order statistical methods which have been applied on our images. The extracted features are used for unsupervised pixel classification to obtain the different classes in the image. So, the K-means algorithm is implemented before the choice of a threshold to highlight the ears. Three methods have been tested in this feasibility study with very average error of 6%. Although the evaluation of the quality of the detection is visually done, automatic evaluation algorithms are currently implementing. Moreover, other statistical methods of higher order will be implemented in the future jointly with methods based on spatio-frequential transforms and specific filtering.

First measurement of the ratio of branching fractions B({lambda}{sub b}{sup 0}{yields}{lambda}{sub c}{sup +}{mu}{sup -}{nu}{sub {mu}})/B({lambda}{sub b}{sup 0}{yields}{lambda}{sub c}{sup +}{pi}{sup -})

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

Aaltonen, T.; Maki, T.; Mehtala, P.

2009-02-01

This article presents the first measurement of the ratio of branching fractions B({lambda}{sub b}{sup 0}{yields}{lambda}{sub c}{sup +}{mu}{sup -}{nu}{sub {mu}})/B({lambda}{sub b}{sup 0}{yields}{lambda}{sub c}{sup +}{pi}{sup -}). Measurements in two control samples using the same technique B(B{sup 0}{yields}D{sup +}{mu}{sup -}{nu}{sub {mu}})/B(B{sup 0}{yields}D{sup +}{pi}{sup -}) and B(B{sup 0}{yields}D*(2010){sup +}{mu}{sup -}{nu}{sub {mu}})/B(B{sup 0}{yields}D*(2010){sup +}{pi}{sup -}) are also reported. The analysis uses data from an integrated luminosity of approximately 172 pb{sup -1} of pp collisions at {radical}(s)=1.96 TeV, collected with the CDF II detector at the Fermilab Tevatron. The relative branching fractions are measured to be (B({lambda}{sub b}{sup 0}{yields}{lambda}{sub c}{sup +}{mu}{sup -}{nu}{sub {mu}})/B({lambda}{sub b}{sup 0}{yields}{lambda}{sub c}{supmore » +}{pi}{sup -}))=16.6{+-}3.0(stat){+-}1.0(syst)(+2.6/-3.4)(PDG){+-}0.3 (EBR), (B(B{sup 0}{yields}D{sup +}{mu}{sup -}{nu}{sub {mu}})/B(B{sup 0}{yields}D{sup +}{pi}{sup -}))9.9{+-}1.0(stat){+-}0.6(syst){+-}0.4(PDG){+-}0.5(EBR), and (B(B{sup 0}{yields}D*(2010){sup +}{mu}{sup -}{nu}{sub {mu}})/B(B{sup 0}{yields}D*(2010){sup +}{pi}{sup -}))=16.5{+-}2.3(stat){+-} 0.6(syst){+-}0.5(PDG){+-}0.8(EBR). The uncertainties are from statistics (stat), internal systematics (syst), world averages of measurements published by the Particle Data Group or subsidiary measurements in this analysis (PDG), and unmeasured branching fractions estimated from theory (EBR), respectively. This article also presents measurements of the branching fractions of four new {lambda}{sub b}{sup 0} semileptonic decays: {lambda}{sub b}{sup 0}{yields}{lambda}{sub c}(2595){sup +}{mu}{sup -}{nu}{sub {mu}}, {lambda}{sub b}{sup 0}{yields}{lambda}{sub c}(2625){sup +}{mu}{sup -}{nu}{sub {mu}}, {lambda}{sub b}{sup 0}{yields}{sigma}{sub c}(2455){sup 0}{pi}{sup +}{mu}{sup -}{nu}{sub {mu}}, and {lambda}{sub b}{sup 0}{yields}{sigma}{sub c

A Statistical Approach for Testing Cross-Phenotype Effects of Rare Variants

PubMed Central

Broadaway, K. Alaine; Cutler, David J.; Duncan, Richard; Moore, Jacob L.; Ware, Erin B.; Jhun, Min A.; Bielak, Lawrence F.; Zhao, Wei; Smith, Jennifer A.; Peyser, Patricia A.; Kardia, Sharon L.R.; Ghosh, Debashis; Epstein, Michael P.

2016-01-01

Increasing empirical evidence suggests that many genetic variants influence multiple distinct phenotypes. When cross-phenotype effects exist, multivariate association methods that consider pleiotropy are often more powerful than univariate methods that model each phenotype separately. Although several statistical approaches exist for testing cross-phenotype effects for common variants, there is a lack of similar tests for gene-based analysis of rare variants. In order to fill this important gap, we introduce a statistical method for cross-phenotype analysis of rare variants using a nonparametric distance-covariance approach that compares similarity in multivariate phenotypes to similarity in rare-variant genotypes across a gene. The approach can accommodate both binary and continuous phenotypes and further can adjust for covariates. Our approach yields a closed-form test whose significance can be evaluated analytically, thereby improving computational efficiency and permitting application on a genome-wide scale. We use simulated data to demonstrate that our method, which we refer to as the Gene Association with Multiple Traits (GAMuT) test, provides increased power over competing approaches. We also illustrate our approach using exome-chip data from the Genetic Epidemiology Network of Arteriopathy. PMID:26942286

Whole blood transcriptional profiling comparison between different milk yield of Chinese Holstein cows using RNA-seq data.

PubMed

Bai, Xue; Zheng, Zhuqing; Liu, Bin; Ji, Xiaoyang; Bai, Yongsheng; Zhang, Wenguang

2016-08-22

The objective of this research was to investigate the variation of gene expression in the blood transcriptome profile of Chinese Holstein cows associated to the milk yield traits. We used RNA-seq to generate the bovine transcriptome from the blood of 23 lactating Chinese Holstein cows with extremely high and low milk yield. A total of 100 differentially expressed genes (DEGs) (p < 0.05, FDR < 0.05) were revealed between the high and low groups. Gene ontology (GO) analysis demonstrated that the 100 DEGs were enriched in specific biological processes with regard to defense response, immune response, inflammatory response, icosanoid metabolic process, and fatty acid metabolic process (p < 0.05). The KEGG pathway analysis with 100 DEGs revealed that the most statistically-significant metabolic pathway was related with Toll-like receptor signaling pathway (p < 0.05). The expression level of four selected DEGs was analyzed by qRT-PCR, and the results indicated that the expression patterns were consistent with the deep sequencing results by RNA-Seq. Furthermore, alternative splicing analysis of 100 DEGs demonstrated that there were different splicing pattern between high and low yielders. The alternative 3' splicing site was the major splicing pattern detected in high yielders. However, in low yielders the major type was exon skipping. This study provides a non-invasive method to identify the DEGs in cattle blood using RNA-seq for milk yield. The revealed 100 DEGs between Holstein cows with extremely high and low milk yield, and immunological pathway are likely involved in milk yield trait. Finally, this study allowed us to explore associations between immune traits and production traits related to milk production.

A Global Data Analysis for Representing Sediment and Particulate Organic Carbon Yield in Earth System Models

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

Tan, Zeli; Leung, L. Ruby; Li, Hongyi

Although sediment yield (SY) from water erosion is ubiquitous and its environmental consequences are well recognized, its impacts on the global carbon cycle remain largely uncertain. This knowledge gap is partly due to the lack of soil erosion modeling in Earth System Models (ESMs), which are important tools used to understand the global carbon cycle and explore its changes. This study analyzed sediment and particulate organic carbon yield (CY) data from 1081 and 38 small catchments (0.1-200 km27 ), respectively, in different environments across the globe. Using multiple statistical analysis techniques, we explored environmental factors and hydrological processes important formore » SY and CY modeling in ESMs. Our results show clear correlations of high SY with traditional agriculture, seismicity and heavy storms, as well as strong correlations between SY and annual peak runoff. These highlight the potential limitation of SY models that represent only interrill and rill erosion because shallow overland flow and rill flow have limited transport capacity due to their hydraulic geometry to produce high SY. Further, our results suggest that SY modeling in ESMs should be implemented at the event scale to produce the catastrophic mass transport during episodic events. Several environmental factors such as seismicity and land management that are often not considered in current catchment-scale SY models can be important in controlling global SY. Our analyses show that SY is likely the primary control on CY in small catchments and a statistically significant empirical relationship is established to calculate SY and CY jointly in ESMs.« less

Temperature Increase Reduces Global Yields of Major Crops in Four Independent Estimates

NASA Technical Reports Server (NTRS)

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe;

Regional yield predictions of malting barley by remote sensing and ancillary data

NASA Astrophysics Data System (ADS)

Weissteiner, Christof J.; Braun, Matthias; Kuehbauch, Walter

2004-02-01

Yield forecasts are of high interest to the malting and brewing industry in order to allow the most convenient purchasing policy of raw materials. Within this investigation, malting barley yield forecasts (Hordeum vulgare L.) were performed for typical growing regions in South-Western Germany. Multisensoral and multitemporal Remote Sensing data on one hand and ancillary meteorological, agrostatistical, topographical and pedological data on the other hand were used as input data for prediction models, which were based on an empirical-statistical modeling approach. Since spring barley production is depending on acreage and on the yield per area, classification is needed, which was performed by a supervised multitemporal classification algorithm, utilizing optical Remote Sensing data (LANDSAT TM/ETM+). Comparison between a pixel-based and an object-oriented classification algorithm was carried out. The basic version of the yield estimation model was conducted by means of linear correlation of Remote Sensing data (NOAA-AVHRR NDVI), CORINE land cover data and agrostatistical data. In an extended version meteorological data (temperature, precipitation, etc.) and soil data was incorporated. Both, basic and extended prediction systems, led to feasible results, depending on the selection of the time span for NDVI accumulation.

Temperature increase reduces global yields of major crops in four independent estimates

PubMed Central

Zhao, Chuang; Piao, Shilong; Wang, Xuhui; Lobell, David B.; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A.; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Peng, Shushi; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-01-01

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population. PMID:28811375

Temperature increase reduces global yields of major crops in four independent estimates.

PubMed

Zhao, Chuang; Liu, Bing; Piao, Shilong; Wang, Xuhui; Lobell, David B; Huang, Yao; Huang, Mengtian; Yao, Yitong; Bassu, Simona; Ciais, Philippe; Durand, Jean-Louis; Elliott, Joshua; Ewert, Frank; Janssens, Ivan A; Li, Tao; Lin, Erda; Liu, Qiang; Martre, Pierre; Müller, Christoph; Peng, Shushi; Peñuelas, Josep; Ruane, Alex C; Wallach, Daniel; Wang, Tao; Wu, Donghai; Liu, Zhuo; Zhu, Yan; Zhu, Zaichun; Asseng, Senthold

2017-08-29

Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO 2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multimethod analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region-specific adaptation strategies to ensure food security for an increasing world population.

Spatial relationships among cereal yields and selected soil physical and chemical properties.

PubMed

Lipiec, Jerzy; Usowicz, Bogusław

2018-08-15

Sandy soils occupy large area in Poland (about 50%) and in the world. This study aimed at determining spatial relationships of cereal yields and the selected soil physical and chemical properties in three study years (2001-2003) on low productive sandy Podzol soil (Podlasie, Poland). The yields and soil properties in plough and subsoil layers were determined at 72-150 points. The test crops were: wheat, wheat and barley mixture and oats. To explore the spatial relationship between cereal yields and each soil property spatial statistics was used. The best fitting models were adjusted to empirical semivariance and cross-semivariance, which were used to draw maps using kriging. Majority of the soil properties and crop yields exhibited low and medium variability (coefficient of variation 5-70%). The effective ranges of the spatial dependence (the distance at which data are autocorrelated) for yields and all soil properties were 24.3-58.5m and 10.5-373m, respectively. Nugget to sill ratios showed that crop yields and soil properties were strongly spatially dependent except bulk density. Majority of the pairs in cross-semivariograms exhibited strong spatial interdependence. The ranges of the spatial dependence varied in plough layer between 54.6m for yield×pH up to 2433m for yield×silt content. Corresponding ranges in subsoil were 24.8m for crop yield×clay content in 2003 and 1404m for yield×bulk density. Kriging maps allowed separating sub-field area with the lowest yield and soil cation exchange capacity, organic carbon content and pH. This area had lighter color on the aerial photograph due to high content of the sand and low content of soil organic carbon. The results will help farmers at identifying sub-field areas for applying localized management practices to improve these soil properties and further spatial studies in larger scale. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Quality evaluation of no-reference MR images using multidirectional filters and image statistics.

PubMed

Jang, Jinseong; Bang, Kihun; Jang, Hanbyol; Hwang, Dosik

2018-09-01

This study aimed to develop a fully automatic, no-reference image-quality assessment (IQA) method for MR images. New quality-aware features were obtained by applying multidirectional filters to MR images and examining the feature statistics. A histogram of these features was then fitted to a generalized Gaussian distribution function for which the shape parameters yielded different values depending on the type of distortion in the MR image. Standard feature statistics were established through a training process based on high-quality MR images without distortion. Subsequently, the feature statistics of a test MR image were calculated and compared with the standards. The quality score was calculated as the difference between the shape parameters of the test image and the undistorted standard images. The proposed IQA method showed a >0.99 correlation with the conventional full-reference assessment methods; accordingly, this proposed method yielded the best performance among no-reference IQA methods for images containing six types of synthetic, MR-specific distortions. In addition, for authentically distorted images, the proposed method yielded the highest correlation with subjective assessments by human observers, thus demonstrating its superior performance over other no-reference IQAs. Our proposed IQA was designed to consider MR-specific features and outperformed other no-reference IQAs designed mainly for photographic images. Magn Reson Med 80:914-924, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

Clinical and prognostic significance of muscle biopsy in sarcoidosis.

PubMed

Yanardag, Halil; Tetikkurt, Cuneyt; Bilir, Muammer

2018-04-30

The main objective of this study was to evaluate the influence of muscle involvement on the clinical features, prognostic outcome, extrapulmonary organ, and endobronchial involvement in sarcoidosis patients. The second aim was to assess the diagnostic yield of muscle biopsy for the histopathologic identification of sarcoidosis.  Fifty sarcoidosis patients participated in the study. The patients were classified into two groups according to the histopathologic presence of non-caseating granulomatous inflammatory pattern of the muscle biopsy samples and were evaluated retrospectively in regard to clinical features, prognosis, extrapulmonary, and endobronchial disease involvement. Pathologic examination of the muscle biopsy samples revealed non-caseating granulomas in eighteen and myositis in seven patients compatible with sarcoidosis. The diagnostic yield of muscle biopsy for demonstrating non-caseating granulomatous inflammation was fifty percent. Patients with muscle sarcoidosis showed a worse prognosis and a more severe extrapulmonary organ involvement than the patients without muscle disease. Muscle biopsy was not statistically significant to delineate diffuse endobronchial involvement while it was suggestive for endobronchial disease clinically. The results of our study reveal that muscle biopsy appears to be a useful diagnostic tool along with its safety and easy clinical applicability. It is a rewarding utility to predict the prognostic outcome and extrapulmonary involvement in sarcoidosis patients. Positive biopsy on the other hand confirms the identification of sarcoidosis in patients with single organ involvement carrying an equivocal diagnostic clinical pattern. Muscle biopsy may be considered as the initial step for the final diagnosis of sarcoidosis in such cases.

Hauser-Feshbach fission fragment de-excitation with calculated macroscopic-microscopic mass yields

NASA Astrophysics Data System (ADS)

Jaffke, Patrick; Möller, Peter; Talou, Patrick; Sierk, Arnold J.

2018-03-01

The Hauser-Feshbach statistical model is applied to the de-excitation of primary fission fragments using input mass yields calculated with macroscopic-microscopic models of the potential energy surface. We test the sensitivity of the prompt fission observables to the input mass yields for two important reactions, 235U(nth,f ) and 239Pu(nth,f ) , for which good experimental data exist. General traits of the mass yields, such as the location of the peaks and their widths, can impact both the prompt neutron and γ -ray multiplicities, as well as their spectra. Specifically, we use several mass yields to determine a linear correlation between the calculated prompt neutron multiplicity ν ¯ and the average heavy-fragment mass 〈Ah〉 of the input mass yields ∂ ν ¯/∂ 〈Ah〉 =±0.1 (n /f ) /u . The mass peak width influences the correlation between the total kinetic energy of the fission fragments and the total number of prompt neutrons emitted, ν¯T(TKE ) . Typical biases on prompt particle observables from using calculated mass yields instead of experimental ones are δ ν ¯=4 % for the average prompt neutron multiplicity, δ M ¯γ=1 % for the average prompt γ -ray multiplicity, δ ɛ¯nLAB=1 % for the average outgoing neutron energy, δ ɛ¯γ=1 % for the average γ -ray energy, and δ 〈TKE 〉=0.4 % for the average total kinetic energy of the fission fragments.

Non-contrast MDCT for Ureteral Calculi and Alternative Diagnoses: Yield in Adult Women vs in Adult Men.

PubMed

Fani, Parisa; Patlas, Michael N; Monteiro, Sandra; Katz, Douglas S

2018-02-02

To determine the yield of non-contrast multi-detector computed tomography (MDCT) of the abdomen and pelvis in diagnosing ureteral calculi as well as other alternative acute conditions in male vs in female adult patients presenting to the emergency department with new onset of symptoms. Our institutional review board approved a retrospective review of the official reports of the non-contrast MDCT examinations of the abdomen and pelvis performed on adults (18 years and older) presenting to our emergency department with a suspected ureteral calculus from October 1, 2011 to October 30, 2013. Patients with recently documented ureteral calculi, known urinary tract infection, malignancy, and trauma were excluded from the study. From a total of 1097 non-contrast MDCT examinations of the abdomen and pelvis over the 2-year period, 400 randomly selected examinations were reviewed (approximately one-third of all the examinations). We compared the prevalence of ureteral calculi between the male and female population. P values and confidence intervals were determined using software Stata 14. Other acute intra-abdominal and intra-pelvic findings amenable to prompt medical care were also documented and analyzed separately. The mean patient age was 55.2 years, with a range of 19-90 years. This included 170 female (mean age 56.8 years) and 230 male patients (mean age 54.2 years). Ureteral calculi were detected in 170 (42.5%) of the patients [111 males (48%) and 59 females (34.7%)] with a prevalence which was statistically significantly higher in the male patients compared to in the female patients (P < 0.01, confidence level of 95% and CI of 13.2-13.4). An alternative diagnosis was made based on the MDCT findings in 49 patient cases (12.25 %), including 26 females (15.29%) and 23 males (10.00%). There was no statistically significant difference in alternative acute findings in male compared to in female patients (P > 0.05). This was with the exception of acute pyelonephritis, which

Scaled test statistics and robust standard errors for non-normal data in covariance structure analysis: a Monte Carlo study.

PubMed

Chou, C P; Bentler, P M; Satorra, A

1991-11-01

Research studying robustness of maximum likelihood (ML) statistics in covariance structure analysis has concluded that test statistics and standard errors are biased under severe non-normality. An estimation procedure known as asymptotic distribution free (ADF), making no distributional assumption, has been suggested to avoid these biases. Corrections to the normal theory statistics to yield more adequate performance have also been proposed. This study compares the performance of a scaled test statistic and robust standard errors for two models under several non-normal conditions and also compares these with the results from ML and ADF methods. Both ML and ADF test statistics performed rather well in one model and considerably worse in the other. In general, the scaled test statistic seemed to behave better than the ML test statistic and the ADF statistic performed the worst. The robust and ADF standard errors yielded more appropriate estimates of sampling variability than the ML standard errors, which were usually downward biased, in both models under most of the non-normal conditions. ML test statistics and standard errors were found to be quite robust to the violation of the normality assumption when data had either symmetric and platykurtic distributions, or non-symmetric and zero kurtotic distributions.

Efficient SRAM yield optimization with mixture surrogate modeling

NASA Astrophysics Data System (ADS)