Experimental evidence of replica symmetry breaking in random lasers

Spin-glass theory is one of the leading paradigms of complex physics and describes condensed matter, neural networks and biological systems, ultracold atoms, random photonics, and many other research fields. According to this theory, identical systems under identical conditions may reach different states and provide different values for observable quantities. This effect is known as Replica Symmetry Breaking and is revealed by the shape of the probability distribution function of an order parameter named the Parisi overlap. However, a direct experimental evidence in any field of research is still missing. Here we investigate pulse-to-pulse fluctuations in random lasers, we introduce and measure the analogue of the Parisi overlap in independent experimental realizations of the same disordered sample, and we find that the distribution function yields evidence of a transition to a glassy light phase compatible with a replica symmetry breaking.Comment: 10 pages, 5 figure

A framework for temporal and spatial rockfall early warning using micro-seismic monitoring

Rockfall risk is usually characterized by a high frequency of occurrence, difficulty in prediction (given high velocity, lack of noticeable forerunners, abrupt collapse, and complex mechanism), and a relatively high potential vulnerability, especially against people and communication routes. Considering that larger rockfalls and rockslides are generally anticipated by an increased occurrence of events, in this study, a framework based on microseismic monitoring is introduced for a temporal and spatial rockfall early warning. This approach is realized through the detection, classification, and localization of all the rockfalls recorded during a 6-month-long microseismic monitoring performed in a limestone quarry in central Italy. Then, in order to provide a temporal warning, an observable quantity of accumulated energy, associated to the rockfall rolling and bouncing and function of the number and volume of events in a certain time window, has been defined. This concept is based on the material failure method developed by Fukuzono-Voight. As soon as the first predicted time of failure and relative warning time are declared, all the rockfalls occurred in a previous time window can be located in a topographic map to find the rockfall susceptible area and thus to complement the warning with spatial information. This methodology has been successfully validated in an ex post analysis performed in the aforementioned quarry, where a large rockfall was forecasted with a lead time of 3 min. This framework provides a novel way for rockfall spatiotemporal early warning, and it could be helpful for activating traffic lights and closing mountain roads or other transportation lines using the knowledge of the time and location of a failure. Since this approach is not based on the detection of the triggering events (like for early warnings based on rainfall thresholds), it can be used also for earthquake-induced failures

Joint detection and classification of rockfalls in a microseismic monitoring network

A rockfall (RF) is a ubiquitous geohazard that is difficult to monitor or predict and poses a significant risk for people and transportation in several hilly and mountainous environments. The seismic signal generated by RF carries abundant physical and mechanical information. Thus, signals can be used by researchers to reconstruct the event location, onset time, volume and trajectory, and develop an efficient early warning system. Therefore, the precise automatic detection and classification of RF events are important objectives for scientists, especially in seismic monitoring arrays. An algorithm called DESTRO (DEtection and STorage of ROckfalls) aimed at combining seismic event automatic detection and classification was implemented ad hoc within the MATLAB environment. In event detection, the STA/LTA (short-time-average through long-time-average) method combined with other parameters, such as the minimum duration of an RF and the minimum interval time between two continuous seismic events is used. Furthermore, nine significant features based on the frequency, amplitude, seismic waveform, duration and multiple station attributes are newly proposed to classify seismic events in a RF environment. In particular, a three-step classification method is proposed for the discrimination of five different source types: RFs, earthquakes (EQs), tremors, multispike events (MSs) and subordinate MS events. Each component (vertical, east–west and north–south) at each station within the monitoring network is analysed, and a three-step classification is performed. At a given time, the event series detected from each component are integrated and reclassified component by component and station by station into a final event-type series as an output result. By this algorithm, a case study of the seven-month-long seismic monitoring of a former quarry in Central Italy was investigated by means of four triaxial velocimeters with continuous acquisition at a sampling rate of 200 Hz. During this monitoring period, a human-induced RF simulation was performed, releasing 95 blocks (in which 90 blocks validated) of different sizes from the benches of the quarry. Consequently, 64.9 per cent of EQs within 100 km were confirmed in a one-month monitoring period, 88 blocks in the RF simulation were classified correctly as RF events and 2 blocks were classified as MSs given their small energy. Finally, an ad hoc section of the algorithm was designed specifically for RF classification combined with EQ recognition. The algorithm could be applied in slope seismic monitoring to monitor the dynamic states of rock masses, as well as in slope instability forecasting and risk evaluation in EQ-prone areas

Landslide mapping and characterization through Infrared Thermography (IRT): Suggestions for a methodological approach from some case studies

In this paper, the potential of Infrared Thermography (IRT) as a novel operational tool for landslide surveying, mapping and characterization was tested and demonstrated in different case studies, by analyzing various types of instability processes (rock slide/fall, roto-translational slide-flow). In particular, IRT was applied, both from terrestrial and airborne platforms, in an integrated methodology with other geomatcs methods, such as terrestrial laser scanning (TLS) and global positioning systems (GPS), for the detection and mapping of landslides’ potentially hazardous structural and morphological features (structural discontinuities and open fractures, scarps, seepage and moisture zones, landslide drainage network and ponds). Depending on the study areas’ hazard context, the collected remotely sensed data were validated through field inspections, with the purpose of studying and verifying the causes of mass movements. The challenge of this work is to go beyond the current state of the art of IRT in landslide studies, with the aim of improving and extending the investigative capacity of the analyzed technique, in the framework of a growing demand for effective Civil Protection procedures in landslide geo-hydrological disaster managing activities. The proposed methodology proved to be an effective tool for landslide analysis, especially in the field of emergency management, when it is often necessary to gather all the required information in dangerous environments as fast as possible, to be used for the planning of mitigation measures and the evaluation of hazardous scenarios. Advantages and limitations of the proposed method in the field of the explored applications were evaluated, as well as general operative recommendations and future perspectives

Disease Activity and Progression in Multiple Sclerosis: New Evidences and Future Perspectives

Multiple sclerosis (MS) is a chronic, debilitating, autoimmune-mediated, inflammatory disease of the central nervous system (CNS), in which a combination of inflammation, demyelination and axonal degeneration takes place with extreme highly interpersonal variability [...]