Full adoption of the most effective strategies to mitigate methane emissions by ruminants can help meet the 1.5 °C target by 2030 but not 2050

To meet the 1.5 °C target, methane (CH) from ruminants must be reduced by 11 to 30% by 2030 and 24 to 47% by 2050 compared to 2010 levels. A meta-analysis identified strategies to decrease product-based (PB; CH per unit meat or milk) and absolute (ABS) enteric CH emissions while maintaining or increasing animal productivity (AP; weight gain or milk yield). Next, the potential of different adoption rates of one PB or one ABS strategy to contribute to the 1.5 °C target was estimated. The database included findings from 430 peer-reviewed studies, which reported 98 mitigation strategies that can be classified into three categories: animal and feed management, diet formulation, and rumen manipulation. A random-effects meta-analysis weighted by inverse variance was carried out. Three PB strategies—namely, increasing feeding level, decreasing grass maturity, and decreasing dietary forage-to-concentrate ratio—decreased CH per unit meat or milk by on average 12% and increased AP by a median of 17%. Five ABS strategies—namely CH inhibitors, tanniferous forages, electron sinks, oils and fats, and oilseeds—decreased daily methane by on average 21%. Globally, only 100% adoption of the most effective PB and ABS strategies can meet the 1.5 °C target by 2030 but not 2050, because mitigation effects are offset by projected increases in CH due to increasing milk and meat demand. Notably, by 2030 and 2050, low- and middle-income countries may not meet their contribution to the 1.5 °C target for this same reason, whereas high-income countries could meet their contributions due to only a minor projected increase in enteric CH emissions.We thank the GLOBAL NETWORK project for generating part of the database. The GLOBAL NETWORK project (https://globalresearchalliance.org/research/livestock/collaborative-activities/global-research-project/; accessed 20 June 2020) was a multinational initiative funded by the Joint Programming Initiative on Food Security, Agriculture, and Climate Change and was coordinated by the Feed and Nutrition Network (https://globalresearchalliance.org/research/livestock/networks/feed-nutrition-network/; accessed 20 June 2020) within the Livestock Research Group of the Global Research Alliance on Agricultural GHG (https://globalresearchalliance.org; accessed 20 June 2020). We thank MitiGate, which was part of the Animal Change project funded by the EU under Grant Agreement FP7-266018 for sharing their database with us (http://mitigate.ibers.aber.ac.uk/, accessed 1 July 2017). Part of C.A., A.N.H., and S.C.M.’s time in the early stages of this project was funded by the Kravis Scientific Research Fund (New York) and a gift from Sue and Steve Mandel to the Environmental Defense Fund. Another part of C.A.’s work on this project was supported by the National Program for Scientific Research and Advanced Studies - PROCIENCIA within the framework of the "Project for the Improvement and Expansion of the Services of the National System of Science, Technology and Technological Innovation" (Contract No. 016-2019) and by the German Federal Ministry for Economic Cooperation and Development (issued through Deutsche Gesellschaft für Internationale Zusammenarbei) through the research “Programme of Climate Smart Livestock” (Programme 2017.0119.2). Part of A.N.H.’s work was funded by the US Department of Agriculture (Washington, DC) National Institute of Food and Agriculture Federal Appropriations under Project PEN 04539 and Accession no. 1000803. E.K. was supported by the Sesnon Endowed Chair Fund of the University of California, Davis

Switched LQR control: Design of a general framework

This thesis studies the Switched Linear Quadratic Regulator (SLQR) problem, over a hybrid (continuous and discrete) dynamical model known as "switched system". The problem is defined as computing the optimal continuous and discrete switching control to minimise a quadratic cost function that weights the states and the continuous controls. The original SLQR problem does not handle constraints on states, continuous or discrete controls, and there is no probabilistic behaviour. This thesis focuses on the discrete dynamics in a SLQR problem. The first part of the thesis describes the SLQR problem with discrete constraints, whereas the second part is dedicated to probabilistic switching behaviour. The problem with discrete constraints is described as finding the optimal hybrid switching policy that minimises a quadratic cost function, weighting states and continuous controls, without violating the discrete constraints. The problem with probabilistic switches is defined as finding the optimal hybrid switching policy that minimises an expected value of a quadratic cost function, weighting states and continuous controls. For the SLQR problem with discrete constraints a general relaxation framework is developed to simplify the representations of the value functions and the corresponding control strategies. It is shown that the closed loop performance of the obtained solution with the relaxation framework can be made arbitrarily close to the optimal solution. For the SLQR problem with probabilistic switches it is shown that a relaxation framework can only be developed when there are no discrete constraints involved. Finally, the thesis concludes with a few case studies to illustrate how the optimal hybrid control sequence is computed.Delft Centre for Systems and ControlMechanical, Maritime and Materials Engineerin

Staphylococcus epidermidis originating from titanium implants infects surrounding tissue and immune cells

Infection is a major cause of failure of inserted or implanted biomedical devices (biomaterials). During surgery, bacteria may adhere to the implant, initiating biofilm formation. Bacteria are also observed in and recultured from the tissue surrounding implants, and may even reside inside host cells. Whether these bacteria originate from biofilms is not known. Therefore, we investigated the fate of Staphylococcus epidermidis inoculated on the surface of implants as adherent planktonic cells or as a biofilm in mouse experimental biomaterial-associated infection. In order to discriminate the challenge strain from potential contaminating mouse microflora, we constructed a fully virulent green fluorescent S. epidermidis strain. S. epidermidis injected along subcutaneous titanium implants, pre-seeded on the implants or pre-grown as biofilm, were retrieved from the implants as well as the surrounding tissue in all cases after 4days, and in histology bacteria were observed in the tissue co-localizing with macrophages. Thus, bacteria adherent to or in a biofilm on the implant are a potential source of infection of the surrounding tissue, and antimicrobial strategies should prevent both biofilm formation and tissue colonizatio