Dynamic escape game

We introduce Dynamic Escape Game (DEC), a tool that provides emergency evacuation plans in situations where some of the escape paths may become unavailable at runtime. We formalize the setting as a reachability two-player turn-based game where the universal player has the power of inhibiting at runtime some moves to the existential player. Thus, the universal player can change the structure of the game arena along a play. DEC uses a graphical interface to depict the game and displays a winning play whenever it exists

Solving parity games: Explicit vs symbolic

In this paper we provide a broad investigation of the symbolic approach for solving Parity Games. Specifically, we implement in a fresh tool, called, four symbolic algorithms to solve Parity Games and compare their performances to the corresponding explicit versions for different classes of games. By means of benchmarks, we show that for random games, even for constrained random games, explicit algorithms actually perform better than symbolic algorithms. The situation changes, however, for structured games, where symbolic algorithms seem to have the advantage. This suggests that when evaluating algorithms for parity-game solving, it would be useful to have real benchmarks and not only random benchmarks, as the common practice has been

Pain-motor integration in the primary motor cortex in Parkinson's disease

In Parkinson's disease (PD), the influence of chronic pain on motor features has never been investigated. We have recently designed a technique that combines nociceptive system activation by laser stimuli and primary motor cortex (M1) activation through transcranial magnetic stimulation (TMS), in a laser-paired associative stimulation design (Laser-PAS). In controls, Laser-PAS induces long-term changes in motor evoked potentials reflecting M1 long-term potentiation-like plasticity, arising from pain-motor integration

Serum Compounds of Energy Metabolism Impairment Are Related to Disability, Disease Course and Neuroimaging in Multiple Sclerosis

Multiple sclerosis (MS) is characterized by primary inflammation, demyelination, and progressive neurodegeneration. A biochemical MS feature is neuronal mitochondrial dysfunction, compensated by anaerobic metabolism increase, likely aggravating progression of neurodegeneration. Here, we characterized a pragmatic serum profile of compounds related to mitochondrial energy metabolism of potential clinical use. Blood samples of 518 well characterized (disability, disease course) MS patients and 167 healthy controls were analyzed for serum purines, pyrimidines, creatinine, and lactate. Nine of the 15 compounds assayed, hypoxanthine, xanthine, uric acid, inosine, uracil, β-pseudouridine, uridine, creatinine, and lactate, differed significantly between MS patients and controls (p < 0.0001). Using these nine compounds, a unifying Biomarker Score was calculated. Controls and MS patients had mean Biomarker Scores of 0.4 ± 0.7 and 4.4 ± 1.9, respectively (p < 0.00001). The Biomarker Score was higher in patients with progressive (6.0 ± 1.8 than with relapsing remitting disease course (3.6 ± 1.5, p < 0.00001). High association between the Biomarker Score and increase in disability (EDSS) was also observed. Additionally, in 50 patients who underwent magnetic resonance imaging (MRI), increase in the Biomarker Score correlated to neuroanatomical alterations. These results, obtained in a large cohort of MS patients evaluated for serum metabolic compounds connected to energy metabolism, demonstrated that the Biomarker Score might represent a pragmatic, resource saving, easy to obtain, laboratory tool useful to monitor MS patients and predict at an early stage who will switch from an RR to a progressive disease course. For the first time, it was also clearly shown a link between mitochondrial dysfunction and MRI lesions characteristic of MS

LTLf Synthesis Under Environment Specifications

In this communication we present recent advances in the field of synthesis for agent goals specified in Linear Temporal Logic on finite traces under environment specifications. In synthesis, environment specifications are constraints on the environments that rule out certain environment behavior. To solve synthesis of LTLf goals under environment specifications, we could reduce the problem to LTL synthesis. Unfortunately, while synthesis in LTLf and in LTL have the same worst-case complexity (both are 2EXPTIME-complete), the algorithms available for LTL synthesis are much harder in practice than those for LTLf synthesis. We report recent results showing that when the environment specifications are in form of fairness, stability, or GR(1) formulas, we can avoid such a detour to LTL and keep the simplicity of LTLf synthesis. Furthermore, even when the environment specifications are specified in full LTL we can partially avoid this detour

Explicit and Symbolic Approaches for Parity Games

In this paper, we review a broad investigation of the symbolic approach for solving Parity Games. Specifically, we implement in a tool, called SymPGSolver, four symbolic algorithms to solve Parity Games and compare their performances to the corresponding explicit versions for different classes of games. By means of benchmarks, we show that for random games, even for constrained random games, explicit algorithms actually perform better than symbolic algorithms. The situation changes, however, for structured games, where symbolic algorithms seem to have the advantage. This suggests that when evaluating algorithms for parity-game solving, it would be useful to have real benchmarks and not only random benchmarks, as the common practice has been