1,720,959 research outputs found
Attività nitrato riduttasica e assimilazione di K, Ca e Mg in lattuga cv "Iceberg" allevata in presenza di "compost" azoto-organici
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
High accuracy of genome-enabled prediction of belowground and physiological traits in barley seedlings
No full textIn plants, the study of belowground traits is gaining momentum due to their importance on yield formation and the uptake of water and
nutrients. In several cereal crops, seminal root number and seminal root angle are proxy traits of the root system architecture at the mature
stages, which in turn contributes to modulating the uptake of water and nutrients. Along with seminal root number and seminal root angle,
experimental evidence indicates that the transpiration rate response to evaporative demand or vapor pressure deficit is a key physiological
trait that might be targeted to cope with drought tolerance as the reduction of the water flux to leaves for limiting transpiration rate at high
levels of vapor pressure deficit allows to better manage soil moisture. In the present study, we examined the phenotypic diversity of seminal
root number, seminal root angle, and transpiration rate at the seedling stage in a panel of 8-way Multiparent Advanced Generation
Inter-Crosses lines of winter barley and correlated these traits with grain yield measured in different site-by-season combinations. Second,
phenotypic and genotypic data of the Multiparent Advanced Generation Inter-Crosses population were combined to fit and cross-validate
different genomic prediction models for these belowground and physiological traits. Genomic prediction models for seminal root number
were fitted using threshold and log-normal models, considering these data as ordinal discrete variable and as count data, respectively,
while for seminal root angle and transpiration rate, genomic prediction was implemented using models based on extended genomic best
linear unbiased predictors. The results presented in this study show that genome-enabled prediction models of seminal root number, seminal
root angle, and transpiration rate data have high predictive ability and that the best models investigated in the present study include
first-order additive additive epistatic interaction effects. Our analyses indicate that beyond grain yield, genomic prediction models might
be used to predict belowground and physiological traits and pave the way to practical applications for barley improvement
Genomic prediction of grain yield in a barley MAGIC population modelling genotype per environment interaction
Full text linkMulti-parent Advanced Generation Inter-crosses (MAGIC) lines have mosaic genomes
that are generated shuffling the genetic material of the founder parents following predefined
crossing schemes. In cereal crops, these experimental populations have been
extensively used to investigate the genetic bases of several traits and dissect the genetic
bases of epistasis. In plants, genomic prediction models are usually fitted using either
diverse panels of mostly unrelated accessions or individuals of biparental families and
several empirical analyses have been conducted to evaluate the predictive ability of
models fitted to these populations using different traits. In this paper, we constructed,
genotyped and evaluated a barley MAGIC population of 352 individuals developed with
a diverse set of eight founder parents showing contrasting phenotypes for grain yield.
We combined phenotypic and genotypic information of this MAGIC population to fit
several genomic prediction models which were cross-validated to conduct empirical
analyses aimed at examining the predictive ability of these models varying the sizes
of training populations. Moreover, several methods to optimize the composition of the
training population were also applied to this MAGIC population and cross-validated to
estimate the resulting predictive ability. Finally, extensive phenotypic data generated in
field trials organized across an ample range of water regimes and climatic conditions
in the Mediterranean were used to fit and cross-validate multi-environment genomic
prediction models including GE interaction, using both genomic best linear unbiased
prediction and reproducing kernel Hilbert space along with a non-linear Gaussian Kernel.
Overall, our empirical analyses showed that genomic prediction models trained with a
limited number of MAGIC lines can be used to predict grain yield with values of predictive
ability that vary from 0.25 to 0.60 and that beyond QTL mapping and analysis of epistatic
effects, MAGIC population might be used to successfully fit genomic prediction models.
We concluded that for grain yield, the single-environment genomic prediction models
examined in this study are equivalent in terms of predictive ability while, in general,
multi-environment models that explicitly split marker effects in main and environmentalspecific
effects outperform simpler multi-environment models
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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