Is global seismicity signed by the Markowitz wobble ?

For the past 108 years the worldwide occurrence of large seismic events shows a significant cyclic temporal pattern of about 34 years. The spectral analysis of the irregular Earth's polar motion over the last 108 years filtered from the secular drifts shows that both LOD and polhody are affected by the same significant periodicity. The third amplitude of polar motion at decadal periodicity in the terrestrial reference frame, after the Chandler and annual, is known as Markowitz wobble. The spectral coherence between the seismicity and polar motion is high at long periods, reaching saturation value at about 20 years. No significant delay is shown by the cross-correlation analysis between LOD, polhody and seismicity. If we accept the idea that global seismicity and polar motion are both signed by the Markowitz wobble, we can infer that they could be modulated by the same cause. Recent models hypothesize a gravitational and inertial coupling between the mantle and an inner core able to reproduce the Markowitz wobble on the polar motion. However, if the wobble signature on seismicity will be confirmed, this interpretation should probably be revise

A Comparison of MCMC Sampling for Probabilistic Logic Programming

Markov Chain Monte Carlo (MCMC) methods are a class of algorithms used to perform approximate inference in probabilistic models. When direct sampling from a probability distribution is difficult, MCMC algorithms provide accurate results by constructing a Markov chain that gradually approximates the desired distribution. In this paper we describe and compare the performances of two MCMC sampling algorithms, Gibbs sampling and Metropolis Hastings sampling, with rejection sampling for probabilistic logic programs. In particular, we analyse the relation between execution time and number of samples and how fast each algorithm converges

Normal fault earthquakes or graviquakes

Earthquakes are dissipation of energy throughout elastic waves. Canonically is the elastic energy accumulated during the interseismic period. However, in crustal extensional settings, gravity is the main energy source for hangingwall fault collapsing. Gravitational potential is about 100 times larger than the observed magnitude, far more than enough to explain the earthquake. Therefore, normal faults have a different mechanism of energy accumulation and dissipation (graviquakes) with respect to other tectonic settings (strike-slip and contractional), where elastic energy allows motion even against gravity. The bigger the involved volume, the larger is their magnitude. The steeper the normal fault, the larger is the vertical displacement and the larger is the seismic energy released. Normal faults activate preferentially at about 60° but they can be shallower in low friction rocks. In low static friction rocks, the fault may partly creep dissipating gravitational energy without releasing great amount of seismic energy. The maximum volume involved by graviquakes is smaller than the other tectonic settings, being the activated fault at most about three times the hypocentre depth, explaining their higher b-value and the lower magnitude of the largest recorded events. Having different phenomenology, graviquakes show peculiar precursor

Exploiting Parameters Learning for Hyper-parameters Optimization in Deep Neural Networks

In the last years, the Hyper-parameter Optimization (HPO) research field has gained more and more attention. Many works have focused on finding the best combination of the Deep Neural Network's (DNN's) hyper-parameters (HPs) or architecture. The state-of-the-art algorithm in terms of HPO is Bayesian Optimization (BO). This is because it keeps track of past results obtained during the optimization and uses this experience to build a probabilistic model mapping HPs to a probability density of the objective function. BO builds a surrogate probabilistic model of the objective function, finds the HPs values that perform best on the surrogate model and updates it with new results. In this work, a system was developed, called Symbolic DNN-Tuner which logically evaluates the results obtained from the training and the validation phase and, by applying symbolic tuning rules, fixes the network architecture, and its HPs, therefore improving performance. Symbolic DNN-Tuner improve BO applied to DNN by adding an analysis of the results of the network on training and validation sets. This analysis is performed by exploiting rule-based programming, and in particular by using Probabilistic Logic Programming (PLP)

Current geodetic deformation of the Colli Albani volcano: a review

The quiescent Colli Albano volcano is presently characterised by moderate intensity earthquakes, seismic swarms, gas emissions and ongoing uplift that reflects the current evidences of its residual activity. An uplift of ~30 cm over the last 43 years was recently detected by levelling surveys performed in the time span 1950-1993 along a levelling line that crosses the highest elevation area of the western flank of the volcano. Space based GPS and Synthetic Aperture Radar Interferometry geodetic observations confirm that this uplift is distributed in a wide area around the craters of Albano and Nemi, where the most recent volcanic activity occurred. GPS data from continuous monitoring stations indicate that both horizontal and vertical deformations do occur and that can be addressed to a shallow magmatic source. All the geodetic observations are in agreement and highlight that the Colli Albani is still a potentially active volcano. Being located in a densely populated area close to Rome, the volcano should deserve the same monitoring and hazard assessment effort of any active volcano within urbanized areas. Here we review the geodetic results obtained during the last decades for the Colli Albani volcano

Tidal errors and deformations in regional GPS networks

At present, the tidal correction model described in the IERS 2003 Conventions should be applied in the processing of permanent networks: in brief, the model involves the computation of a first order tidal correction plus some corrective terms, as functions of space and time. In the BERNESE software, one of the main scientific softwares for GPS network processing, the IERS tidal model is implemented; in July 2004, a bug in the tidal correction routine was identified by one of the paper authors and corrected by the BERNESE staff: the error concerned a second order term, related to the semidiurnal tidal signal. An experimental analysis on the error effects in the results stemming from processing of regional networks has been carried out. A network of 8 European permanent GPS stations has been selected: the network choice ensures heterogeneity in the length and the orientation of the baselines. One year of data has been considered and two elaborations of the data have been performed using the BERNESE 4.2 SW, by applying the same processing strategy and, respectively, the wrong (old) and the right (corrected) tidal correction routine. The differences in the network results and the deformations caused by the error are discussed

Present geodynamics of the northern Adriatic plate

The northern Adriatic plate is surrounded and squeezed by three orogens (i.e. Apennines, Alps and Dinarides). Therefore, in the same area, the effects of three independent subduction zones coexist and overlap. This supports the evidence that plate boundaries are passive features. The northeastward migration of the Apennines subduction hinge determines the present-day faster subsidence rate in the western side of the northern Adriatic (>1 mm/yr). This is recorded also by the dip of the foreland regional monocline, and the increase SW-ward of the depth of the Tyrrhenian layer, as well as the increase in thickness of the Pliocene and Pleistocene sediments. These data indicate the dominant influence of the Apennines subduction and the related asymmetric subsidence in the northern Adriatic realm. The Dinarides front has been subsided by the Apennines subduction hinge, as shown by the eroded Dalmatian anticlines in the eastern Adriatic Sea. GPS data show the horizontal pattern of motion along the front of the three belts surrounding the northern Adriatic plate. Values of shortening along the prisms are in the order of 2-3 mm/yr (Northern Apennines), 1-2 mm/yr (Southern Alps) and <1mm/yr (Dinarides). The pattern of the new GPS velocities relative to Eurasia account for different tectonic domains and the estimated strain rates are within 0.1 μstrain/yr. The shortening directions tend to be perpendicular to the thrust belt fronts, as expected. The areas where the strain rate sharply decreases across a tectonic feature (e.g., the Ferrara salient) are considered structures seismically loading the brittle laye

Expectation Maximization in Deep Probabilistic Logic Programming

Probabilistic Logic Programming (PLP) combines logic and probability for representing and reasoning over domains with uncertainty. Hierarchical probability Logic Programming (HPLP) is a recent language of PLP whose clauses are hierarchically organized forming a deep neural network or arithmetic circuit. Inference in HPLP is done by circuit evaluation and learning is therefore cheaper than any generic PLP language. We present in this paper an Expectation Maximization algorithm, called Expectation Maximization Parameter learning for HIerarchical Probabilistic Logic programs (EMPHIL), for learning HPLP parameters. The algorithm converts an arithmetic circuit into a Bayesian network and performs the belief propagation algorithm over the corresponding factor graph

Probabilistic inference in SWI-Prolog

Probabilistic Logic Programming (PLP) emerged as one of the most prominent approaches to cope with real-world domains. The distribution semantics is one of most used in PLP, as it is followed by many languages, such as Independent Choice Logic, PRISM, pD, Logic Programs with Annotated Disjunctions (LPADs) and ProbLog. A possible system that allows performing inference on LPADs is PITA, which transforms the input LPAD into a Prolog program containing calls to library predicates for handling Binary Decision Diagrams (BDDs). In particular, BDDs are used to compactly encode explanations for goals and efficiently compute their probability. However, PITA needs mode-directed tabling (also called tabling with answer subsumption), which has been implemented in SWI-Prolog only recently. This paper shows how SWI-Prolog has been extended to include correct answer subsumption and how the PITA transformation has been changed to use SWI-Prolog implementation

Water level and volume estimations of the Albano and Nemi lakes (central Italy)

In April 2006 an airborne laser scanning (LIDAR) survey of the Albano and Nemi craters was carried out to obtain a high resolution digital terrain model (DTM) of the area. We have integrated the LIDAR survey of the craters and the recent bathymetry of the Albano lake to achieve a complete DTM, useful for morphological studies. In addition, with a GPS RTK survey (July 2007) we estimated the Albano and Nemi mean lake levels respectively at 288.16 m and 319.02 m (asl). Based on the integrated DTM and the newly estimated water level values, we evaluated about 21.7·106 m3 the water volume loss of the Albano lake from 1993 to 2007, with an average rate of about 1.6·106 m3/yr