Strategies of use of a specific immunoglobulin-rich egg yolk powder in weaning piglets

Two experiments were performed to determine the best strategy of use of the product TRACTcare® 4P (ITPSA) (TC, specific immunoglobulin-rich egg yolk powder within an energetic fatty acid matrix) in piglets from weaning and for 6 weeks, in diets without or with inclusion of antibiotics. Each trial was performed with 144 piglets in 24 pens, in a completely randomized design blocked by initial body weight. Feeds were formulated according to animal requirements in two periods. In the first trial no antibiotics were included in the feeds and no room disinfection from previous trial was performed; treatments were: 1) Negative control (NC); 2) NC+TC on top of the feed within the hopper for the first 3 days on trial (30 g/pig×day), and eventually if diarrhea appeared (TCOT); 3) NC+TC ad libitum provided in an extra hopper within the pen (TCAL); and 4) NC+TC at 5 g/kg added to the feed in the mixer (TC5). In the second trial, treatments were: 1) Positive control: basal diet that included 250 mg/kg amoxiciline (BD)+100 mg/kg colistine (AC); 2) BD+2 g/kg TC (TC2A); 3) BD+5 g/kg TC (TC5A); and 4) BD+8 g/kg TC (TC8A). In diets without antibiotics, the product TC at 5 g/kg in the feed numerically improved BW by 8% compared to Control animals, while G:F was almost identical between both groups. When antibiotics were used in the feed, replacement of colistin at 100 mg/kg for TC at 2 g/kg in feed numerically improved the performance compared to Positive control animals (for the whole trial period ADG 8% better: 390 g vs. 361 g; G:F 1% better: 0.748 kg/kg vs. 0.742 kg/kg), possibly due to the stimulation of feed consumption at weaning. In both trials, the lower number of dead and culled animals from TC5 and TC2A together with higher BW represented an advantage over Control treatments of 6% to 10% animals more and 15% to 17% total BW more at the end of the trial.

An efficient use of virtualization in grid/cloud environments

Grid is a hardware and software infrastructure that provides dependable, consistent, pervasive, and inexpensive access to high-end computational resources. Grid enables access to the resources but it does not guarantee any quality of service. Moreover, Grid does not provide performance isolation; job of one user can influence the performance of other user’s job. The other problem with Grid is that the users of Grid belong to scientific community and the jobs require specific and customized software environment. Providing the perfect environment to the user is very difficult in Grid for its dispersed and heterogeneous nature. Though, Cloud computing provide full customization and control, but there is no simple procedure available to submit user jobs as in Grid. The Grid computing can provide customized resources and performance to the user using virtualization. A virtual machine can join the Grid as an execution node. The virtual machine can also be submitted as a job with user jobs inside. Where the first method gives quality of service and performance isolation, the second method also provides customization and administration in addition. In this thesis, a solution is proposed to enable virtual machine reuse which will provide performance isolation with customization and administration. The same virtual machine can be used for several jobs. In the proposed solution customized virtual machines join the Grid pool on user request. Proposed solution describes two scenarios to achieve this goal. In first scenario, user submits their customized virtual machine as a job. The virtual machine joins the Grid pool when it is powered on. In the second scenario, user customized virtual machines are preconfigured in the execution system. These virtual machines join the Grid pool on user request. Condor and VMware server is used to deploy and test the scenarios. Condor supports virtual machine jobs. The scenario 1 is deployed using Condor VM universe. The second scenario uses VMware-VIX API for scripting powering on and powering off of the remote virtual machines. The experimental results shows that as scenario 2 does not need to transfer the virtual machine image, the virtual machine image becomes live on pool more faster. In scenario 1, the virtual machine runs as a condor job, so it easy to administrate the virtual machine. The only pitfall in scenario 1 is the network traffic.