Proteins are essential parts in living organisms. They participate in most of the cellular processes such as gene expression, signal transmission, catalysis of chemical reactions, … Due to their large range of possible functions, the study of proteins interests other fields in addition to biology. Proteins are pharmaceutical targets and drugs, their catalytic properties are widely used in biotechnology, and they are used as components of nano-devises in the rising field of bionanotechnology. Although the properties of natural proteins can be directly exploited, new, designed proteins, with novel functions or improved activities, are of major interest in all these application areas. Protein design may involve the remodeling of a known protein scaffold in order to modify the protein function/activity, or, in the most general case, the complete (de novo) design of new protein structures to fulfill a particular function. The problem is extremely challenging since the number of possible combinations of amino acids to be tested is astronomically large. Experimentally testing all the possible sequences is practically impossible. Therefore, computational protein design methods have been developed for over a decade. In addition to the intrinsic combinatorial complexity of the protein design problem, computational methods have to face the natural flexibility of proteins (i.e. proteins are flexible molecules that fluctuate between nearly isoenergetic states). Indeed, the protein design problem is even more challenging if dynamical aspects (e.g. allosteric shifts, loop motions, ...) are considered in addition to static aspects (e.g. positional arrangement of catalytic residues for enzyme activity). Due to all these difficulties, and despite great advances in recent years, computational protein design remains a largely open problem. In particular, improvements in models and algorithms are essential to better explore the protein sequence combinatorial space while taking into account protein flexibility. Besides, accurate and computationally efficient energy functions, able to better account for interactions with solvent and entropy change, are necessary. The goal of this project is to yield advances in a general methodology for protein design, and to develop suitable computational design tools that will lead the development of new proteins for applications in biotechnology, biomolecular nanotechnology, molecular medicine and synthetic biology. The methodological breakthrough expected from this interdisciplinary project builds on the combination of cutting-edge methods in computational biology with efficient algorithms originating from robotics. Among all the possible applications of the methods developed in this project, special attention will be given to enzyme design for applications in biotechnology such as the production of high-valued molecules, the development of eco-friendly bioprocesses and the valorization of renewable carbon resources. Such applications are of high interest to the pre-industrial demonstrator Toulouse White Biotech (TWB), supporter of our project, and to the Competitive Cluster AgriMip. The achievement of the project relies on the complementary expertise of four partners: LAAS-CNRS for robotics and computer science, BIOS-Polytechnique and LISBP-INSA for computational biology & protein engineering, and Kineo CAM, a company specialized in software development for computer-aided design and manufacturing.

ADVICE aims at increasing the number of HEVs up to 10% of all vehicles registered in the mid-term range. This will be achieved by focusing on a market segment called “premium class”, which covers medium class, upper medium class and luxury vehicles up to SUVs. This segment is facing severe problems in reaching European environmental exhaust targets, when running on fossil fuel only, not the least due to the considerable vehicle weight. In ADVICE three physical demonstrator vehicles are built, ranging from mild-hybrid, plug-in-hybrid to full-hybrid and – concerning fuel type – from gasoline to diesel-driven. In addition, it will be shown that the whole range in between these demonstrator vehicles can be well covered by means of validated simulation, yielding a complete coverage of the whole “premium class” segment. ADVICE aims for a reduction of exhaust and CO2 emissions on WLTP of 20% and a 25% increase in electric driving range for P-HEVs at a maximum premium cost of 5% for HEV (15% for P-HEV) with respect to the best in-class non-hybrid diesel vehicles. Particular attention is devoted to optimum driveability and drive performance, which are essential when purchasing a “premium class” vehicle and thus crucial to achieve the market penetration aimed at. These objectives will be accomplished by: * Architecture-level hybrid powertrain solutions, suited to be modularly applied to different segments to increase their volumes while reducing costs * Advanced predictive control strategies and model predictive control strategies, taking the entire vehicle into account (not only the hybrid part) * Novel optimised approaches in the aftertreatment system * Newly developed high-temperature electronics, enabling novel strategies and approaches for energy- and thermal-management * Multi-core processor architectures, enabling sophisticated control strategies and models processed on-board the vehicles ADVICE results will be verified through vehicle validator independent tests

In the long haul transport sector, the reduction of real driving emissions and fuel consumption is the main societal challenge. The LONGRUN project will contribute to lower the impacts by developing different engines, drivelines and demonstrator vehicles with 10% energy saving (TtW) and related CO2, 30% lower emission exhaust (NOx, CO and others), and 50% Peak Thermal Efficiency. A second achievement will be the multiscale simulation framework to support the design and development of efficient powertrains, including hybrids for both trucks and coaches. With the proposed initiatives a leading position in hybrid powertrain technology and Internal Combustion Engine operating on renewable fuels in Europe will be guaranteed. A single solution is not enough to achieve these targets. The LONGRUN project brings together leading OEMs of trucks and coaches and their suppliers and research partners, to develop a set of innovations and applications, and to publish major roadmaps for technology and fuels in time for the revision of the CO2 emission standards for heavy duty vehicles in 2022 to support decision making with most recent and validated results and to make recommendations for future policies. The OEMs will develop 8 demonstrators (3 engines, 1 hybrid drivelines, 2 coaches and 3 trucks); within them technical sub-systems and components will be demonstrated, including electro-hybrid drives, optimised ICEs and aftertreatment systems for alternative and renewable fuels, electric motors, smart auxiliaries, on-board energy recuperation and storage devices and power electronics. This includes concepts for connected and digitalised fleet management, predictive maintenance and operation in relation to electrification where appropriate to maximise the emissions reduction potential. The 30 partners will accelerate the transition from fossil-based fuels to alternative and renewable fuels and to a strong reduction of fossil-based CO2 and air pollutant emissions in Europe

A consortium of industrial and academic leading players covering the entire value chain of road transport has joined forces to commonly address the need to prove feasible and environmental-friendly cases of alternative fuels to fossil diesel for road transport, acknowledging the importance of reducing GHG emissions (beyond EURO 6) with affordable developments. Commercial vehicles using Optimised Liquid biofuels and HVO Drivetrains (COLHD) has the ambition to enable EU purchasers to buy high performance, clean, safe, affordable HDVs, specifically designed to run on alternative renewable fuels, and be able to conveniently run them through EU transport infrastructure. To do so, COLHD will follow a 3-tiered approach, working on technology, infrastructure and removal of additional barriers. COLHD will optimize and further develop 3 DDF powertrains running on biogas (LBM or LBP) and 2nd generation biofuels (HVO), evaluating the several benefits under testing in the LNG Blue Corridors infrastructure. Therefore, COHLD will allow proving oil substitution on the short and medium term, addressing different markets and ranges. Aiming at finally establish a EU market for AF HDVs, COLHD will co-develop cross-wise activities involving all key target audiences: raising awareness of general public, organising workshops with fleet operators and constantly assessing the EC on required policy directives.