Effects of dietary yeast autolysate (Saccharomyces cerevisiae) on performance,egg traits,egg cholesterol content,egg yolk fatty acid composition and humoral immune response of laying hens

BACKGROUND: The objective of this study was to determine the effects of dietary yeast autolysate on performance, egg traits, egg cholesterol content, egg yolk fatty acid composition, lipid oxidation of egg yolk, some blood parameters and humoral immune response of laying hens during a 16 week period. A total of 225 Hyline Brown laying hens, 22 weeks of age, were allocated equally to one control group and four treatment groups. Yeast autolysate (Saccharomyces cerevisiae, InteWall) was used at levels of 1, 2, 3 and 4 g kg^?1 in the diets of the first, second, third and fourth treatment groups respectively. RESULTS: Dietary treatments did not significantly affect body weight, feed intake and egg traits. Yeast autolysate supplementation increased egg production (P < 0.001) and egg weight (P < 0.001) and improved feed efficiency (P < 0.05). Yeast autolysate at levels of 2, 3 and 4 g kg^?1 decreased egg yolk cholesterol level as mg g^?1 yolk (P < 0.01) and blood serum levels of cholesterol and triglyceride (P < 0.05) and increased antibody titres to sheep red blood cells (P < 0.01). Total saturated fatty acids and the ratio of saturated/unsaturated fatty acids increased (P < 0.01) and total monounsaturated fatty acids (P < 0.001) decreased with yeast autolysate supplementation. CONCLUSION: Dietary yeast autolysate at levels of 2, 3 and 4 g kg^?1 had beneficial effects on performance, egg cholesterol content and humoral immune response. It is concluded that 2 g kg^?1 yeast autolysate will be enough to have beneficial effects in laying hens. Copyright © 2010 Society of Chemical Industry     

Rhodium‐Catalysed Alkoxycarbonylative Cyclisation Reactions of 1,6‐Enynes

The rhodium‐catalysed carbonylation of 1,6‐enynes possessing an electron‐deficient alkenyl moiety in an alcohol reagent in the presence of a rhodium complex proceeded stereo‐ and chemoselectively to afford exocyclic α,β‐enoates.     

TUM autonomous motorsport: An autonomous racing software for the Indy Autonomous Challenge

For decades, motorsport has been an incubator for innovations in the automotive sector and brought forth systems, like, disk brakes or rearview mirrors. Autonomous racing series such as Roborace, F1Tenth, or the Indy Autonomous Challenge (IAC) are envisioned as playing a similar role within the autonomous vehicle sector, serving as a proving ground for new technology at the limits of the autonomous systems capabilities. This paper outlines the software stack and approach of the TUM Autonomous Motorsport team for their participation in the IAC, which holds two competitions: A single-vehicle competition on the Indianapolis Motor Speedway and a passing competition at the Las Vegas Motor Speedway. Nine university teams used an identical vehicle platform: A modified Indy Lights chassis equipped with sensors, a computing platform, and actuators. All the teams developed different algorithms for object detection, localization, planning, prediction, and control of the race cars. The team from Technical University of Munich (TUM) placed first in Indianapolis and secured second place in Las Vegas. During the final of the passing competition, the TUM team reached speeds and accelerations close to the limit of the vehicle, peaking at around $270\text{km h}{}^{-1}$ and $28ms{}^{-2}$. This paper will present details of the vehicle hardware platform, the developed algorithms, and the workflow to test and enhance the software applied during the 2-year project. We derive deep insights into the autonomous vehicle's behavior at high speed and high acceleration by providing a detailed competition analysis. On the basis of this, we deduce a list of lessons learned and provide insights on promising areas of future work based on the real-world evaluation of the displayed concepts.