The current study was conducted to determine the synergistic effects of dietary nano selenium (Nano Se) and vitamin C on growth, feeding, and physiological parameters of juvenile mahseer, Tor putitora. L-ascorbyl-2-polyphosphate (APP) was used as a source of vitamin C. Four semi-purified experimental diets were prepared. A basal diet kept without the supplementation of any micronutrient and the other three diets were formulated such that three different levels of APP (100, 200, and 300 mg kg−1) were used in combination with a pre-determined dose of Nano Se (0.68 mg kg−1). The results showed that both the micronutrients positively synergized the effects of each other. APP at the rate of 300 mg kg−1 showed strong interaction with Nano Se. The APP300 + Nano Se0.68 mg kg−1 diet supplemented diet significantly decreased (P< 0.05) the feed conversion ratio (FCR) while significantly increased (P< 0.05) the weight gain percentage (WG%), feed conversion efficiency (FCE%), specific growth rate (SGR), and serum growth hormone (GH) concentration. Similarly, the physiological parameters such as red blood cells count (RBCs), hemoglobin level (Hb), hematocrit value (Hct), and serum lysozyme activity were also significantly increased in group of fish fed diet supplemented with APP100 mg kg−1 in combination with Nano Se0.68 mg kg−1 as compared to the control group. The present results clearly indicated the beneficent synergistic effects of Nano Se and APP in mahseer fish. Moreover, the current finding also supported our hypothesis that Nano Se and APP potentiate positively the effect of each other when both the micronutrients are supplemented together in the same fish feed
To develop the theory of aggregation operators based on the Aczel-Alsina t-norm and t-conorm is a very challenging task for individuals, where the idea of Aczel-Alsina norms is the modified version of the algebraic norms. The main theme of this manuscript is to evaluate the Aczel-Alsina operational laws and Aczel-Alsina aggregation operators for complex single-valued neutrosophic (CSVN) information such as CSVN Aczel-Alsina weighted averaging (CSVNAAWA), CSVN Aczel-Alsina ordered weighted averaging (CSVNAAOWA), CSVN Aczel-Alsina hybrid averaging (CSVNAAHA), CSVN Aczel-Alsina weighted geometric (CSVNAAWG), CSVN Aczel-Alsina ordered weighted geometric (CSVNAAOWG), CSVN Aczel-Alsina hybrid geometric (CSVNAAHG) operators, idempotency, monotonicity, and boundedness. Additionally, in the presence of the above-derived operators, we illustrated a model of the MADM “multi-attribute decision-making” procedure for CSVN values. Finally, we employed various numerical examples to demonstrate the supremacy and efficiency of the discovered theory to compare it with various prevailing operators.