Implementation of the RESTK algorithm based on Markov's Inequality from  Vilardell, Sergi, Serra, Isabel, Mezzetti, Enrico, Abella, Jaume, Cazorla, Francisco  J. and Del Castillo, J. (2022). "Using Markov's Inequality with Power-Of-k Function for Probabilistic WCET Estimation". In 34th Euromicro Conference on Real-Time Systems (ECRTS 2022). Leibniz International Proceedings in Informatics (LIPIcs) 231 20:1-20:24. <doi:10.4230/LIPIcs.ECRTS.2022.20>. This work has been supported by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 772773).

Flexible framework for ecological restoration planning. It aims to identify priority areas for restoration efforts using optimization algorithms (based on Justeau-Allaire et al. 2021 <doi:10.1111/1365-2664.13803>). Priority areas can be identified by maximizing landscape indices, such as the effective mesh size (Jaeger 2000 <doi:10.1023/A:1008129329289>), or the integral index of connectivity (Pascual-Hortal & Saura 2006 <doi:10.1007/s10980-006-0013-z>). Additionally, constraints can be used to ensure that priority areas exhibit particular characteristics (e.g., ensure that particular places are not selected for restoration, ensure that priority areas form a single contiguous network). Furthermore, multiple near-optimal solutions can be generated to explore multiple options in restoration planning. The package leverages the 'Choco-solver' software to perform optimization using constraint programming (CP) techniques (<https://choco-solver.org/>).

A random-effects stochastic model that allows quick detection of 
  clonal dominance events from clonal tracking data collected in gene therapy studies. Starting from the Ito-type equation describing the dynamics of cells duplication, death and differentiation at clonal level, we first considered its local linear approximation as the base model. 
  The parameters of the base model, which are inferred using a maximum likelihood approach, 
  are assumed to be shared across the clones. Although this assumption makes inference easier, 
  in some cases it can be too restrictive and does not take into account possible scenarios of clonal dominance. 
  Therefore we extended the base model by introducing random effects for the clones. 
  In this extended formulation the dynamic parameters are estimated using a tailor-made 
  expectation maximization algorithm. Further details on the methods can be found in L. Del Core et al., (2022) <doi:10.1101/2022.05.31.494100>.