Mnemicity vs. Temporality: Distinguishing between components of episodic representations

Human beings regularly 'mentally travel' to past and future times in memory and imagination. In theory, whether an event is remembered or imagined (its ‘mnemicity’) underspecifies whether it is oriented towards the past or the future (its ‘temporality’). However, it remains unclear to what extent the temporal orientation of such episodic simulations is cognitively represented separately from their status as memories or imagination. To address this question, we investigated whether episodic simulations are more easily distinguishable in memory by virtue of their temporal orientation or their mnemicity. In three experiments (N = 360), participants were asked to generate and later recall events differing along the lines of temporal orientation (past/future) and mnemicity (remembered/imagined). Across all of our experiments, we consistently found that participants were more likely to confuse in recall event simulations that shared the same temporal orientation rather than the same mnemicity. These results show that the temporal orientation of episodic representations can be cognitively represented separately from their mnemicity and have implications for debates about the role of temporality in episodic simulation.

Certificate pricing using Discrete Event Simulations and System Dynamics theory

The study proposes an innovative application of Discrete Event Simulations (DES) and System Dynamics (SD) theory to the pricing of a certain kind of certificates very popular among private investors and, more generally, in the context of wealth management. The paper shows how numerical simulation software mainly used in traditional engineering, such as industrial and mechanical engineering, can be successfully adapted to the risk analysis of structured financial products. The article can be divided into three macro-sections: in the first part a synthetic overview of the most widespread option pricing models in the quantitative finance branch is given to the readers together with the fundamental technical-instrumental background of the implemented DES and SD simulator. After dealing with some of the most popular models adopted for Equity and Equity index options, which are the most common underlying assets for the certificates structuring, we move, in the second part, to describe how the mathematical models can be integrated into a general simulation environment able to provide both DES and SD extensively used in the engineering field. The core stochastic differential equation (SDE) will therefore be translated, together with all its input parameters, into a visual block model which allows an immediate quantitative analysis of how market parameters and the other model variables can change over time. The possibility for the structurer to observe how the variables evolve day-by-day gives a strong sensitivity to evaluate how the price and the associated risk measures can be directly affected. The third part of the study compares the results obtained from the simulator designed by the authors with the more traditional pricing approaches, which consist in programming Matlab® codes for the numerical integration of the core stochastic dynamics through a Euler-Maruyama scheme. The comparison includes a price check using the Bloomberg® DLIB pricing module and a check directly against the valuation provided by the counterparty. In this section, real market cases will therefore be examined with a complete quantitative analysis of two of the most widespread categories of certificates in wealth management: Multi-asset Barrier Reverse Convertible with Issuer Callability and Multi-asset Express Certificate with conditional memory fixed coupon.

Cut-Off Lows and Extreme Precipitation in Eastern Spain: Current and Future Climate

This study presents a seasonal synoptic climatology of cut-off lows (COLs) that produced extreme precipitation in the Valencia region of Spain during 1998–2018 and uses simulations with the Weather Research and Forecasting (WRF) model to study how extreme COL precipitation may change in a future warmer climate. COLs were shown to be the main producer of extreme precipitation in the Valencia region, especially during the transition seasons. The strongest raining COL events occurred during September–November. Six-day composites of thermodynamic and dynamic fields and precipitation show that COLs that produce extreme precipitation in this region remain stationary over Spain for 2–3 days and tend to produce precipitation over the Valencia region for at least two consecutive days. In the low levels these COLs are characterized by low pressure over the Mediterranean sea and winds with an easterly, onshore component thus fueling precipitation. Comparison of current and future climate ensembles of WRF simulations of 14 September–November extreme precipitation producing COL events suggest that in a warmer climate extreme COL precipitation may increase by as much as 88% in northeastern Spain and 61% in the adjoining Mediterranean Sea. These projected increases in extreme COL precipitation in the northeast of Spain present additional challenges to a region where COL flooding already has significant socio-economic impacts. Additionally, about half of the future climate COL event simulations showed increases in precipitation in the Valencian region of eastern Spain. These results provide important nuance to projections of a decreasing trend of total precipitation in the Iberian Peninsula as the climate warms.

Probabilistic Model for the Lifetime Prediction of IoT Devices

The development of new electronics and communications technologies allows the Internet of Things (IoT) concepts to be put into practice. A large amount of information is expected to travel over the internet from intelligent objects to many different kinds of software and cloud computing applications. However, there are still several challenges to be overcome. Among them, management of devices energy consumption is intriguing. Therefore, a model to estimate the range of probabilities of the energy spent by IoT equipment is presented in this work. The results include the formulation of probability distributions and discrete event simulations. The proposed method can be applied to design and evaluate IoT applications.