Explaining exchange rate dynamics: the uncovered equity return parity condition

By employing Lucas’ (1982) model, this study proposes an arbitrage relationship – the Uncovered Equity Return Parity (URP) condition – to explain the dynamics of exchange rates. When expected equity returns in a country/region are lower than expected equity returns in another country/region, the currency associated with the market offering lower returns is expected to appreciate. First, we test the URP assuming that investors are risk neutral and next we relax this hypothesis. The resulting risk premia are proxied by economic variables, which are related to the business cycle. We employ differentials in corporate earnings’ growth rates, short-term interest rate changes, annual inflation rates, and net equity flows. The URP explains a large fraction of the variability of some European currencies vis-à-vis the US dollar. When confronted with the naïve random walk model, the URP for the EUR/USD performs better in terms of forecasts for a set of alternative statistics. JEL Classification: D82, G14, G15asset pricing, foreign exchange markets, GMM, random walk, UIP

The uncovered return parity condition

This paper proposes an equilibrium relationship between expected exchange rate changes and differentials in expected returns on risky assets. We show that when expected returns on a risky asset in a certain economy are higher than the returns that are expected from investing in a risky asset in another economy, then the currency corresponding to the economy whose asset offers higher returns is expected to depreciate. Due to its similarity with Uncovered Interest Parity (UIP), we call this equilibrium condition “Uncovered Return Parity” (URP). However, in the URP condition returns’ differentials are not known ex ante, while in the UIP they are. The paper finds empirical support in favour of URP for certain markets over some sample periods. JEL Classification: F30, F31, G12, C32GMM, stochastic discount factor, Uncovered interest parity, Uncovered Return Parity

Modeling and Recognition of Smart Grid Faults by a Combined Approach of Dissimilarity Learning and One-Class Classification

Detecting faults in electrical power grids is of paramount importance, either from the electricity operator and consumer viewpoints. Modern electric power grids (smart grids) are equipped with smart sensors that allow to gather real-time information regarding the physical status of all the component elements belonging to the whole infrastructure (e.g., cables and related insulation, transformers, breakers and so on). In real-world smart grid systems, usually, additional information that are related to the operational status of the grid itself are collected such as meteorological information. Designing a suitable recognition (discrimination) model of faults in a real-world smart grid system is hence a challenging task. This follows from the heterogeneity of the information that actually determine a typical fault condition. The second point is that, for synthesizing a recognition model, in practice only the conditions of observed faults are usually meaningful. Therefore, a suitable recognition model should be synthesized by making use of the observed fault conditions only. In this paper, we deal with the problem of modeling and recognizing faults in a real-world smart grid system, which supplies the entire city of Rome, Italy. Recognition of faults is addressed by following a combined approach of multiple dissimilarity measures customization and one-class classification techniques. We provide here an in-depth study related to the available data and to the models synthesized by the proposed one-class classifier. We offer also a comprehensive analysis of the fault recognition results by exploiting a fuzzy set based reliability decision rule

Il divieto dei patti successori tra norma imperativa, profili di tutela dei legittimari e frode alla legge

Scopo dell’indagine è quello di verificare quale possa essere, nel tempo attuale, l’effettivo ambito di applicazione del divieto dei patti successori, alla luce di una sempre più avvertita spinta verso la "contrattualizzazione" della successione a causa di morte. A partire dalla genesi storica del divieto e sulla base di un'analisi separata delle tre diverse categorie di patti sulle successioni future, viene in particolare affrontato il problema, da sempre discusso, del fondamento giustificativo della norma contenuta nell'art. 458 c.c. L'ambito della indagine viene poi allargato, anche in chiave critica, alla ricerca di possibili punti di contatto tra il divieto in parola e altri fondamentali istituti: la c.d. legittima (e la tutela dei legittimari), da un lato, e la clausola generale della frode alla legge, dall'altro

Investigation of the Stark Effect on a Centrosymmetric Quantum Emitter in Diamond

Quantum emitters in diamond are leading optically-accessible solid-state qubits. Among these, Group IV-vacancy defect centers have attracted great interest as coherent and stable optical interfaces to long-lived spin states. Theory indicates that their inversion symmetry provides first-order insensitivity to stray electric fields, a common limitation for optical coherence in any host material. Here we experimentally quantify this electric field dependence via an external electric field applied to individual tin-vacancy (SnV) centers in diamond. These measurements reveal that the permanent electric dipole moment and polarizability are at least four orders of magnitude smaller than for the diamond nitrogen vacancy (NV) centers, representing the first direct measurement of the inversion symmetry protection of a Group IV defect in diamond. Moreover, we show that by modulating the electric-field-induced dipole we can use the SnV as a nanoscale probe of local electric field noise, and we employ this technique to highlight the effect of spectral diffusion on the SnV.Comment: 6 pages, 4 figure

A Cross-Sectional Survey on Burnout Prevalence and Profile in the Sicilian Population of Ambulance Driver-Rescuers

Introduction: Burnout is present at a high rate in emergency medicine. The ambulance driver-rescuers, who furnish first aid to the victims, are the non-medical part of the Italian 118-service staff. There is a lack of research on burnout risk in Italian Emergency Medical Services and, particularly, for this category of workers. The two Italian studies, including a little group of ambulance driver-rescuers, reported inconsistent findings. Hypothesis: This survey investigated for the first time the prevalence and exact profile of burnout in a large sample of Italian driver-rescuers. As a secondary aim, the study described how the items of the Italian version of the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) cluster in components in this sample. Methods: This cross-sectional census survey was conducted from June 2015 through May 2016 and involved all the driver-rescuers operating in Sicily, the biggest and most southern region of Italy. The subjects received a classification according to different profiles of burnout by using the Italian version of the MBI-HSS (burnout, engagement, disengagement, over-extension, and work-inefficacy). In order to explore the existence of independent factors, a Principal Component Analysis (PCA) was conducted on the survey to obtain eigenvalues >one for each component in the data. Results: The final sample comprised 2,361 responders (96.6% of the initial sample). Of them, 29.8% were in burnout (95% confidence interval [CI], 27.8% to 31.8%) and 1.7% presented a severe form (95% CI, 1.1% to 2.3%); 30.0% were engaged in their work (95% CI, 21.0% to 34.8%), 24.7% of responders were disengaged (95% CI, 22.9% to 26.5%), 1.2% presented an over-extension profile (95% CI, 0.8% to 1.7%), and 12.6% felt work-inefficacy (95% CI, 11.3% to 14.1%). The factors loaded into a five-factor solution at PCA, explaining 48.1% of the variance and partially replicating the three-factor structure. The Emotional Exhaustion (EE) component was confirmed. New dimensions from Personal Accomplishment (PA) and Depersonalization (DP) sub-scales described empathy and disengagement with patients, respectively, and were responsible for the increased risk of burnout. Conclusions: These results endorse the importance of screening and psychological interventions for this population of emergency workers, where burnout could manifest itself more insidiously. It is also possible to speculate that sub-optimal empathy skills could be related to the disengagement and work-inefficacy feelings registered

Machine Learning-Based Classification to Disentangle EEG Responses to TMS and Auditory Input

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) offers an unparalleled opportunity to study cortical physiology by characterizing brain electrical responses to external perturbation, called transcranial-evoked potentials (TEPs). Although these reflect cortical post-synaptic potentials, they can be contaminated by auditory evoked potentials (AEPs) due to the TMS click, which partly show a similar spatial and temporal scalp distribution. Therefore, TEPs and AEPs can be difficult to disentangle by common statistical methods, especially in conditions of suboptimal AEP suppression. In this work, we explored the ability of machine learning algorithms to distinguish TEPs recorded with masking of the TMS click, AEPs and non-masked TEPs in a sample of healthy subjects. Overall, our classifier provided reliable results at the single subject level, even for signals where differences were not shown in previous works. Classification accuracy (CA) was lower at the group level, when different subjects were used for training and test phases, and when three stimulation conditions instead of two were compared. Lastly, CA was higher when average, rather than single-trial TEPs, were used. In conclusion, this proof-of-concept study proposes machine learning as a promising tool to separate pure TEPs from those contaminated by sensory input

Machine Learning-Based Classification to Disentangle EEG Responses to TMS and Auditory Input

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) offers an unparalleled opportunity to study cortical physiology by characterizing brain electrical responses to external perturbation, called transcranial-evoked potentials (TEPs). Although these reflect cortical post-synaptic potentials, they can be contaminated by auditory evoked potentials (AEPs) due to the TMS click, which partly show a similar spatial and temporal scalp distribution. Therefore, TEPs and AEPs can be difficult to disentangle by common statistical methods, especially in conditions of suboptimal AEP suppression. In this work, we explored the ability of machine learning algorithms to distinguish TEPs recorded with masking of the TMS click, AEPs and non-masked TEPs in a sample of healthy subjects. Overall, our classifier provided reliable results at the single-subject level, even for signals where differences were not shown in previous works. Classification accuracy (CA) was lower at the group level, when different subjects were used for training and test phases, and when three stimulation conditions instead of two were compared. Lastly, CA was higher when average, rather than single-trial TEPs, were used. In conclusion, this proof-of-concept study proposes machine learning as a promising tool to separate pure TEPs from those contaminated by sensory input

FUS affects circular RNA expression in murine embryonic stem cell-derived motor neurons

The RNA-binding protein FUS participates in several RNA biosynthetic processes and has been linked to the pathogenesis of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia. Here we report that FUS controls back-splicing reactions leading to circular RNA (circRNA) production. We identified circRNAs expressed in in vitro -derived mouse motor neurons (MNs) and determined that the production of a considerable number of these circRNAs is regulated by FUS. Using RNAi and overexpression of wild-type and ALS-asso- ciated FUS mutants, we directly correlate the modulation of circRNA biogenesis with alteration of FUS nuclear levels and with putative toxic gain of function activities. We also demonstrate that FUS regulates circRNA biogenesis by binding the introns flanking the back-splicing junctions and that this control can be reproduced with artificial constructs. Most circRNAs are conserved in humans and specific ones are deregulated in human-induced pluripotent stem cell-derived MNs carrying the FUS P525L mutation associated with AL