The comprehension of molecular recognition phenomena demands the understanding of the energetic and kinetic processes involved. General equations valid for the thermodynamic analysis of any observable that is assessed as a function of the concentration of the involved compounds are described, together with their implementation in the AFFINImeter software.Here, a maximum of three different molecular species that can interact with each other to form an enormous variety of supramolecular complexes are considered. The corrections currently employed to take into account the effects of dilution, volume displacement, concentration errors and those due to external factors, especially in the case of ITC measurements, are included. The methods used to fit the model parameters to the experimental data, and to generate the uncertainties are described in detail. A simulation tool and the so called kinITC analysis to get kinetic information from calorimetric experiments are also presented. An example of how to take advantage of the AFFINImeter software for the global multi-temperature analysis of a system exhibiting cooperative 1:2 interactions is presented and the results are compared with data previously published. Some useful recommendations for the analysis of experiments aimed at studying molecular interactions are provided.

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While most research papers on computer architectures include some performance measurements, these performance numbers tend to be distrusted. Up to the point that, after so many research articles on data cache architectures, for instance, few researchers have a clear view of what are the best data cache mechanisms. To illustrate the usefulness of a fair quantitative comparison, we have picked a target architecture component for which lots of optimizations have been proposed (data caches), and we have implemented most of the hardware data cache optimizations of the past 4 years in top conferences. Then we have ranked the different mechanisms, or more precisely, we have examined the impact of benchmark selection, process model precision,. . . on ranking, and obtained some surprising results. This study is part of a broader effort, called MicroLib, aimed at promoting the disclosure and sharing of simulator models.

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We coin the term Protocols for Loanable Funds (PLFs) to refer to protocols which establish distributed ledger-based markets for loanable funds. PLFs are emerging as one of the main applications within Decentralized Finance (DeFi), and use smart contract code to facilitate the intermediation of loanable funds. In doing so, these protocols allow agents to borrow and save programmatically. Within these protocols, interest rate mechanisms seek to equilibrate the supply and demand for funds. In this paper, we review the methodologies used to set interest rates on three prominent DeFi PLFs, namely Compound, Aave and dYdX. We provide an empirical examination of how these interest rate rules have behaved since their inception in response to differing degrees of liquidity. We then investigate the market efficiency and inter-connectedness between multiple protocols, examining first whether Uncovered Interest Parity holds within a particular protocol and second whether the interest rates for a particular token market show dependence across protocols, developing a Vector Error Correction Model for the dynamics.

International audienceWhen integrating mixed critical systems on a multi/many-core, one challenge is to ensure predictability for high crit-icality tasks and an increased utilization for low criticality tasks. In this paper, we address this problem when several high criticality tasks with different deadlines, periods and offsets are concurrently executed on the system. We pro-pose a distributed run-time WCET controller that works as follows: (1) locally, each critical task regularly checks if the interferences due to the low criticality tasks can be toler-ated, otherwise it decides their suspension; (2) globally, a master suspends and restarts the low criticality tasks based on the received requests from the critical tasks. Our ap-proach has been implemented as a software controller on a real multi-core COTS system with significant gains 1

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