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An experiment was conducted to evaluate the effects of amaranth grain in pellet diet on performance, intestinal morphology of jejunum, and selected blood variables of broilers. A total of 400 seven-day-old Ross 308 male broilers were allocated to 4 treatments with 5 replicates of 20 birds in a completely randomized design. Experimental treatments were included 4 levels of amaranth grain (0% (control), 2%, 4%, and 6%) in the isonitrogenous and isocaloric pellet diets. During the experiment, body weight (BW) and feed intake (FI) were recorded weekly and average daily gain (ADG), feed conversion ratio (FCR), as well as European broiler index (EBI), were calculated. On day 42, blood sera and jejunal tissue samples were obtained from 6 birds per replicate to evaluate morphological variables including villus height, villus width, and crypt depth, as well as selected blood variables. Although intestinal morphology and average daily feed intake (ADFI) were not influenced by experimental treatments, birds receiving 2% amaranth grain showed higher BW, ADG, and EBI compared to the other treatments (p<0.05). Chickens fed with diets including various levels of amaranth grain showed the decreased low-density lipoprotein (LDL) and cholesterol concentrations in the blood sera and reduced relative weight of abdominal fat compared to the control (p<0.05). Dietary addition of amaranth grain up to the level of 2% could improve the performance of broiler chickens, decreased blood cholesterol and LDL levels, and relative weight of abdominal fat which may have healthful effects on the birds and broiler-meat-consumers.

Optimization of a vehicle fuzzy active suspension (AS) controller was previously performed on the basis of the amplitude of transmitted vibrations to the body. However, ride comfort depends strongly on the human sensitivity, which is a function of not only the amplitude but also the frequency contents of the transmitted vibrations. In this paper, genetic optimization of a fuzzy AS system based on the human sensitivity to the transmitted vibrations is presented. For this purpose, a fuzzy logic controller (FLC) is initially proposed for the AS system control. The FLC parameters are then tuned using a genetic algorithm (GA). The tuning process is first formulated as a single-objective optimization problem based on the human sensitivity and conventional r.m.s. amplitude criteria separately. The simulation results reveal that the optimization of a fuzzy AS based on the common r.m.s. amplitude criterion not only does not result in the optimal ride index, but also causes a considerable increase in the energy consumption. Moreover, in order to accommodate the conflicting characteristics of the AS system, the FLC parameters are tuned on the basis of a multi-objective fitness function incorporating human sensitivity, suspension travel, and energy consumption. The simulation results prove the effectiveness of the optimized FLC in hitting the simultaneous targets of ride comfort improvement as well as suspension travel and energy consumption reduction.