Narrow Results

This paper examines the effects of anticipated and unanticipated uncertainty on macroeconomic fluctuations and investigates the optimal macroeconomic policy portfolio. Our empirical findings indicate that both anticipated and unanticipated uncertainty shocks result in a reduction in gross corporate output, while the negative impact of the former is relatively smaller. By developing a multi-sector DSGE model, we further find that anticipated uncertainty shocks lead to a relatively smaller rise in the risk premium for corporate lending, and a smaller decrease of corporate lending, investment, and output. The policy analysis reveals that monetary policy can effectively dampen the fluctuations of macroeconomic variables like output, but its impact on financial variables such as risk premiums and asset prices is limited. On the other hand, macroprudential policy can directly tackle the root causes of uncertainty shocks and alleviate their adverse effects. The combination of these two policies facilitates a balance between the policy objectives of managing systemic risks and mitigating macroeconomic fluctuations.

In this paper a Traffic Cellular Automata (TCA) simulation of a highly congested round-about in Mauritius is performed. The simulations are performed using a multi-cell model that includes anticipation and probability randomization. The simulation model is first calibrated to match actual traffic count statistics taken at the round-about. The topology of the round-about is then modified and the TCA model is used to predict the impact on the congestion level of different changes made. The simulation results enable the assessment of the impact on the traffic density and travel time of the different modifications made. It has been found that the construction of a flyover bridge at the round-about will be the most convenient solution to alleviate congestion and improve the flux significantly.

The Routing Information Protocol (RIP) and Enhanced Interior Gateway Routing Protocol (EIGRP) algorithms are widely used in the field of telecommunications for transmission of data over computer networks. Traffic Cellular Automata (TCA) is a technique that has proved to be very efficient in simulating large-scale road traffic networks. In this paper a multicell TCA model that includes anticipation and probability randomization has been hybridized with the RIP and EIGRP algorithms. Simulation was performed on a small network and the performance of these two algorithms compared and analyzed. The results show that the EIGRP algorithm, through an adaptive routing of vehicles, achieves reduced travel times, more space-headway and lower traffic densities.

The present study examined rats' ability to anticipate undetectable wider gaps between rungs produced when they stepped on and dislodged damaged rungs while they traversed a slightly inclined elevated ladder. Rats in the first of three experiments reduced running speeds when they encountered four evenly spaced damaged rungs either always placed on the first or second half of the ladder (the break-a-way (BW) phase) but quickly recovered to their baseline (BL) levels when damaged rungs where replaced with intact rungs (the recovery phase). Rats previously exposed to damaged rungs over the first half of the ladder increased their speeds above BL on its second "safer" half during the recovery phase, a delayed "relief-like" positive contrast effect. In Experiment 2, other rats decreased their speeds more as they approached a single damaged rung at a fixed location when it occurred before than after the mid-point of the ladder. Although they quickly recovered to BL speeds on the portion of the ladder after the damaged rung or replaced intact rung, they never showed any "relief-like"/escape effects. Rats also reduced their likelihood of dislodging the damaged rung with a fore paw over extended BW training. In the third experiment rats encountered a more easily dislodged damaged rung that was signaled by a closer intact rung on half the trials. Under these conditions rats displayed a more reliable positive contrast "relief-like" effect. We discussed how traditional associative and cognitive theories of aversive conditioning account for these findings and their relationship to normal changes in dopamine production and possible effects of reduced production from the substantia nigra pars compacta (SNpc) in the Basal ganglia in rodent models of Parkinson's disease.

In this paper, a day-ahead anticipation of complex network vulnerability for an intentional threat of an attack or a shock is carried out. An ecological observer is introduced for that reason, which is a watch in the intentional multiverse, tiled by cells; dynamics of the intentional threat for a day-ahead is characterized by a space-time cell; spreading of the intentional threat is derived from its energy; duration of the intentional threat is found by the self-assembling of a space-time cell; the lower bound of probability is assessed to anticipate for a day-ahead the intentional threat; it is indicated that this vulnerability anticipation for a day-ahead is right when the intentional threat leads to dimension doubling of the complex network.