1,720,958 research outputs found
Investigating the effects of interactions of environmental factors on grain quality using statistical techniques
Get PDFThe increasing carbon dioxide [CO2] in the atmosphere increases crop productivity. However, the grain quality of cereals and pulses are substantially decreased and consequently compromise human health. CO2, temperature, water and nitrogen are considered as the most critical factors influencing crop production. These environmental variables significantly affect grain yield and grain protein concentrations, which are key determinants of grain quality. Consequently, they affect human and animal nutrition. A more detailed understanding of how these environmental factors contribute towards the grain protein content is essential for addressing global nutrient security in the changing climate.
In this thesis, meta-analysis techniques were employed to investigate the effect of elevated [CO2] (e[CO2]) on protein, zinc (Zn) and iron (Fe) concentrations of major food crops including wheat, rice, soybean, field peas and corn considering different levels of temperature, water and nitrogen (N). Each crop, had decreased protein, Zn and Fe concentrations when grown at e[CO2] concentration compared ambient [CO2] (a[CO2]) concentration. However, the responses of protein, Zn, and Fe concentrations to e[CO2] were modified by water stress and N. There was an increase in Fe concentration in soybean under medium N and wet conditions but nonsignificant. The reductions in protein concentrations for wheat and rice were ~5%–10%, and the reductions in Zn and Fe concentrations were ~3%–12%. For soybean, there was a small and nonsignificant increase of 0.37% in its protein concentration under medium N and dry water, while Zn and Fe concentrations were reduced by ~2%–5%. The protein concentration of field peas decreased by 1.7%, and the reductions in Zn and Fe concentrations were ~4%–10%. The reductions in protein, Zn, and Fe concentrations of corn were ~5%–10%. Bias in the dataset was assessed using a regression test and rank correlation.
Also, randomized trials were carried out based on the conditions of the factorial experiments to show the effect of [e[CO2]], water, N, and their interactions on protein, Zn and Fe of wheat crop. To determine the effects of interactions of CO2, water and N on protein, Zn and Fe, the designed experiments are implemented in Matlab to investigate all possible possibilities for primary, binary and triple interactions. These results suggested that high [CO2] concentrations under various levels of environmental conditions affect protein, Zn and Fe concentrations in wheat crop negatively, with protein, Zn and Fe were decreased by 4.5%, 3.5%, 4.1%, respectively, during the three-year experimental period.
The outcomes of this project will inform experts and decision-makers about the effects of CO2, temperature, water and nitrogen on grain quality, and enable the investigation of suitable solutions
Using Mathematical Techniques to Analyse Biomedical Data: A K-complexes EEG Signal Classification Study
Get PDFThis paper endeavored to characterize the design, elaboration, and investigation of the execution of the K-complexes classification method in Electroencephalogram (EEG) signals. To solve many-aims optimization issues for the high dimensionality of every database, a mechanism for feature extraction that depends on merging the Discrete Fourier Transform (Discrete-FT) with Covariance Matrix (Cov-matrix) has been suggested. An EEG signal was split into comparatively little intervals and segments as the first step of the model design. For every EEG segment, Discrete-FT was applied. The Cov-matrix were employed to figure out the most efficient input features to represent the EEG signal. As the input to diverse classifiers, for instance, K-means and the Naïve Bayes algorithm, the extracted features were used. The suggested procedure equips a high rate of accuracy, ~94% when the outcomes were compared with current studies. In conclusion, results exhibited that the submitted process can evolve the classification of K-complexes in EEG signals. Compared with other methods, the proposed method supplied the best outcomes. Furthermore, the presented method can have functional applications to assist physicians in classifying transient events in sleep stages more precisely than the current methods. The new procedure can be utilized for several medical data species, such as restless legs syndrome, epilepsy, Focal and Non-Focal, etc
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Variations on the Author
Get PDF“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
Get PDFWe 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
Get PDFWe 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
1st International Conference on Quantitative, Social, Biomedical and Economic Issues 2017 (ICQSBEI2017)
No full textAs meta-analysis is an effective tool for assisting decision-makers, there has been a recent increase in demand for its use to solve controversies regarding important human life issues. Meta-analysis allows a thematic appraisal of evidence, which can lead to a resolution of suspicions and disagreements. Carbon dioxide, temperature, and nitrogen are considered as the most important factors influencing crop production. These environmental variables significantly affect grain yield and grain protein concentrations, which are key determinants of grain quality. Consequently, they affect human and animal nutrition. A more detailed understanding of how these environmental factors contribute towards the grain protein content is essential for addressing global nutrient security in the changing climate. To our knowledge, there have been no studies conducted to assess the effect of CO2, temperature and nitrogen supply on grain protein and grain yield using meta-analysis. In addition, performance evaluations were mainly conducted in previous studies through traditional statistical measures, and only the combined effect of CO2, temperature and nitrogen on grain protein and grain yield were analysed. Therefore, this study focuses on estimating the effects of CO2, temperature and nitrogen on grain protein and grain yield using meta-analysis. In this work, a new approach based on the dplyr package in R is proposed for organizing and categorizing the research data for meta-analysis. The performances of the proposed methods are evaluated using various measurements, such as the Cochran's Q statistic and its p-value, I2 statistic, and
tau-squared. Overall, the aim of this study was to reveal the significance and reliability of a meta-analysis in analysing the effects of carbon dioxide, temperature and nitrogen on the quality of agricultural crops. The results indicated that the protein concentration was decreased by 0.62% and grain yield was increased by 0.52% under elevated carbon dioxide, ambient temperature and low nitrogen. In contrast, protein concentration was reduced by 0.65% and grain yield was increased by 0.78% under the elevated carbon dioxide, ambient temperature and medium nitrogen. We concluded that meta-analysis can be used to study the effects of CO2, temperature and nitrogen on grain protein concentration and grain yield. The outcomes of this project will inform experts and decision-makers about the effects of CO2, temperature and nitrogen on grain quality, and enable the investigation of suitable solution
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