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M. Yasin, A. Mahmood, A. Ali, M. Aziz, M.M. Javaid, Z. Iqbal and A. Tanveer

Abstract

Achene yield, oil contents and protein contents are vital yield attributes of sunflower crop. To acquaint the impact of NP rates and planting patterns on the production potential of autumn sunflower hybrid Hysun-33 and fertilizer use efficiency a field experiment was executed in 2005. Treatments comprised of four NP combinations viz. 0-0, 50-35, 100-70 and 150-105 NP kg ha-1 and two planting patterns viz. bed sowing with 75 cm wide beds separated by 20 cm furrows and bed sowing with 60 cm wide beds separated by 25 cm furrows. Treatment 150-105 NP kg ha-1 with 75 cm wide beds separated by 20 cm furrows was found to be supercilious as it exhibited significant lofty achene yield (3360.00 kg ha-1), number of achene head-1 (1267.02), 1000-achene weight (68.65 g), biological yield (11166.6 kg ha-1) and harvest index (30.09%). Contrastingly, treatment 0-0 N-P kg ha-1 with 60 cm wide bed separated by 25 cm plant spacing bestowed the minimum grain yield. Frail increase in oil contents with gradual increase in fertilizer levels but it did not procure at a level of significance. Superior protein contents (27.71%) were revealed in treatment 150-105 N-P kg ha-1 with 75 cm wide bed separated by 20 cm plant spacing.

Open access

Jia-Bao Liu, Jing Zhao, Shaohui Wang, M. Javaid and Jinde Cao

Abstract

A topological index is a numeric quantity associated with a network or a graph that characterizes its whole structural properties. In [Javaid and Cao, Neural Computing and Applications, DOI 10.1007/s00521-017-2972-1], the various degree-based topological indices for the probabilistic neural networks are studied. We extend this study by considering the calculations of the other topological indices, and derive the analytical closed formulas for these new topological indices of the probabilistic neural network. Moreover, a comparative study using computer-based graphs has been carried out first time to clarify the nature of the computed topological descriptors for the probabilistic neural networks. Our results extend some known conclusions.

Open access

A. Raheem, M. Javaid and A.Q. Baig

Abstract

Enomoto, Llado, Nakamigawa and Ringel (1998) defined the concept of a super (a, 0)-edge-antimagic total labeling and proposed the conjecture that every tree is a super (a, 0)-edge-antimagic total graph. In the support of this conjecture, the present paper deals with different results on super (a, d)-edge-antimagic total labeling of subdivided stars for d ∈ {0, 1, 2, 3}.

Open access

M. Javaid, M. Abbas, Jia-Bao Liu, W. C. Teh and Jinde Cao

Abstract

A topological property or index of a network is a numeric number which characterises the whole structure of the underlying network. It is used to predict the certain changes in the bio, chemical and physical activities of the networks. The 4-layered probabilistic neural networks are more general than the 3-layered probabilistic neural networks. Javaid and Cao [Neural Comput. and Applic., DOI 10.1007/s00521-017-2972-1] and Liu et al. [Journal of Artificial Intelligence and Soft Computing Research, 8(2018), 225-266] studied the certain degree and distance based topological indices (TI’s) of the 3-layered probabilistic neural networks. In this paper, we extend this study to the 4-layered probabilistic neural networks and compute the certain degree-based TI’s. In the end, a comparison between all the computed indices is included and it is also proved that the TI’s of the 4-layered probabilistic neural networks are better being strictly greater than the 3-layered probabilistic neural networks.