Experimental design techniques are routinely used in the social and biological sinces to determine the relative performance of different strategies or factors. However, these techniques are largely unknown to the proc...
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Experimental design techniques are routinely used in the social and biological sinces to determine the relative performance of different strategies or factors. However, these techniques are largely unknown to the process control community. The aim of this paper is to give a brief summary of standard experiment design concepts, and to illustrate their use on a flotation level control problem. Common incorrect experiments are demonstrated and it is shown how grossly incorrect conclusions can be drawn from such experiments. Our contention is that greater use of these tools by the process control community would significantly enhance the validity of comparative trials.
Background: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the ...
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Background: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. Results: We describe OSAT (Optimal Sample Assignment Tool), a bioconductor package designed for automated sample-to-batch allocations in genomics experiments. Conclusions: OSAT is developed to facilitate the allocation of collected samples to different batches in genomics study. Through optimizing the even distribution of samples in groups of biological interest into different batches, it can reduce the confounding or correlation between batches and the biological variables of interest. It can also optimize the homogeneous distribution of confounding factors across batches. It can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideally balanced designs.
Background Field pea ( Pisum sativum L.) is an essential pulse crop which can offer highly nutritional food to human beings. But, the inadequate availability of nutrients such as Zn could pose a significant threat to ...
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Background Field pea ( Pisum sativum L.) is an essential pulse crop which can offer highly nutritional food to human beings. But, the inadequate availability of nutrients such as Zn could pose a significant threat to public health. Thus, there is a need to improve the food quality parameters and nutrient levels of the crop using biofortification thus, making it beneficial for human consumption. Methods This study evaluated the influence of zinc (Zn) foliar application on food quality parameters, yield, Zn concentration and its uptake along with the economics of field pea cultivation. In the experiment, different concentrations of ZnSO 4 ·7H 2 O and Zn-EDTA at the flowering and bud initiation stage were applied to the field pea. Results The foliar application of ZnSO 4 ·7H 2 O (1.0%) at the flowering and bud initiation stages (treatment T7) was highly efficient in increasing food quality parameters such as crude fibre, TSS, N, K and protein content with maximum values of 3.02, 20.5, 3.15, 3.41 and 14.97%, respectively. Also, the maximum yields of grain and straw in field pea for treatment T7 were 4840 kg ha −1 and 3275 kg ha −1 , respectively. Similarly, the maximum Zn concentration in grain (54.8 mg kg −1 ) and straw (52.5 mg kg −1 ) of field pea was observed in treatment T7. Additionally, Zn uptake by grain (214 g ha −1 ) and straw (167 g ha −1 ) was the maximum for the treatment T7 involving ZnSO 4 ·7H 2 O (1.0%). Whereas, grain Zn concentration and uptake decreased in the treatments involving the use of Zn-EDTA due to the formation of the complex resulting in the reduced availability of Zn to crop. Conclusion Therefore, the application of ZnSO 4 ·7H 2 O (1.0%) at the flowering and bud initiation stage significantly improved the food quality parameters, grain and straw yield, concentration of Zn and uptake over control and could be used to alleviate the Zn deficiency in field pea.
Two versions of a proposed nonparametric test are introduced for the mixed design consisting of a randomizedcompleteblock and a completely randomizeddesign. The proposed versions are designed to test for a nondecre...
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Two versions of a proposed nonparametric test are introduced for the mixed design consisting of a randomizedcompleteblock and a completely randomizeddesign. The proposed versions are designed to test for a nondecreasing trend. Both versions are a combination of Page's test and the Jonckheere-Terpstra test. It is noted that the randomizedcompleteblock portion could be replaced by a repeated measures design. A simulation study is conducted comparing the estimated powers of the two proposed test versions along with the estimated powers of Page's test including only the randomized complete block design portion. Three different underlying distributions are considered. Equal and unequal sample sizes for the completely randomizeddesign are used. When equal sample sizes are used, the sample size, n, is selected so that it is 1/8, 1/4, and 1/2 that of the number of blocks considered. The study considers a variety of increasing location parameter arrangements for three, four, and five populations. At least one of the proposed test versions generally has higher power than the Page's test which uses only the RCBD portion. This paper shows that both test versions can be written as linear combinations of Page's test and the Jonckheere-Terpstra test with differing weights.
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