Lessons from being challenged by COVID-19.

We present results of different approaches to model the evolution of the COVID-19 epidemic in Argentina, with a special focus on the megacity conformed by the city of Buenos Aires and its metropolitan area, including a total of 41 districts with over 13 million inhabitants. We first highlight the relevance of interpreting the early stage of the epidemic in light of incoming infectious travelers from abroad. Next, we critically evaluate certain proposed solutions to contain the epidemic based on instantaneous modifications of the reproductive number. Finally, we build increasingly complex and realistic models, ranging from simple homogeneous models used to estimate local reproduction numbers, to fully coupled inhomogeneous (deterministic or stochastic) models incorporating mobility estimates from cell phone location data. The models are capable of producing forecasts highly consistent with the official number of cases with minimal parameter fitting and fine-tuning. We discuss the strengths and limitations of the proposed models, focusing on the validity of different necessary first approximations, and caution future modeling efforts to exercise great care in the interpretation of long-term forecasts, and in the adoption of non-pharmaceutical interventions backed by numerical simulations.

Community structures and role detection in music networks.

We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the growth of the networks. In the similarity network, we find a strong correlation between clusters of artists and musical genres. On the other hand, the collaboration network shows two different kinds of communities: rather small structures related to music bands and geographic zones, and much bigger communities built upon collaborative clusters with a high number of participants related through the period the artists were active. Finally, we detect the leading artists inside their corresponding communities and analyze their roles in the network by looking at a few topological properties of the nodes.

Phantom reflexes: muscle contractions at a frequency not physically present in the input stimuli.

In the motor system, the periodic stimulation of one Ia-afferent input produces reflex muscle contractions at the input frequency. However, we observed that when two Ia monosynaptic reflex-afferent inputs are involved the periodic muscle contractions may occur at a frequency physically not present in the afferent inputs even when these inputs are sub-threshold. How can the muscles respond with such phantom reflex contractions at a frequency physically absent in the sub-threshold Ia-afferent input stimuli? Here we provide an explanation for this phenomenon in the cat spinal cord, that we termed "ghost motor response". We recorded monosynaptic reflexes in the L7 ventral root, intracellular potentials in the motoneurons, and the associated muscular contractions elicited by stimulation of the lateral and medial gastrocnemius nerves. By stimulating with periodic pulses of sub-threshold intensities and distinct frequencies of 2 and 3 Hz the lateral and medial gastrocnemius nerves, respectively, we observed monosynaptic responses and phantom reflex muscle contractions occurring at the fundamental frequency (1 Hz), which was absent in the input stimuli. Thus we observed a reflex ghost motor response at a frequency not physically present in the inputs. We additionally studied the inharmonic case for sub-threshold stimuli and observed muscular contractions occurring at much lower frequencies, which were also conspicuously absent in the inputs. This is the first experimental evidence of a phantom reflex response in the nervous system. The observed behavior was modeled by numerical simulations of a pool of neurons subjected to two different input pulses.

Local (in time) maximal lyapunov exponents of fragmenting drops

We analyze the dynamics of fragment formation in simulations of exploding three-dimensional Lennard-Jones hot drops, using the maximum local (in time) Lyapunov exponent (MLLE). The dependence of this exponent on the excitation energy of the system displays two different behaviors according to the stage of the dynamical evolution: one related to the highly collisional stage of the evolution, at early times, and the other related to the asymptotic state. We show that in the early, highly collisional, stage of the evolution the MLLE is an increasing function of the energy, as in an infinite-size system. On the other hand, at long times, the MLLE displays a maximum, depending mainly on the size of the resulting biggest fragment. We compare the time scale at which the MLLE's reach their asymptotic values with the characteristic time of fragment formation in phase space. Moreover, upon calculation of the maximum Lyapunov exponent (MLE) of the resulting fragments, we show that their dependence with the mass can be traced to bulk effects plus surface corrections. Using this information the asymptotic behavior of the MLLE can be understood and the fluctuations of the MLE of the whole system can be easily calculated. These fluctuations display a sudden increase for that excitation energy which produces a power-law-like asymptotic distribution of fragments.