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The CROP95-M18 seismic profile was acquired in 1995 as part of the "CROsta Profonda" project, a regional survey carried out to explore the deeper structures of the Earth's crust in Italy. Although the high energy of the source allowed a high penetration depth, the vintage stacked section showed some areas of low signal-to-noise ratio, due to the acquisition in shallow water environments and related reverberations of surface and guided-waves. To improve the quality of the image, we reprocessed the 2D seismic line with the up-to-date processing techniques by adopting a specific workflow in time domain up to pre-stack time migration. In addition, we created an accurate interval velocity model by combining the coherency inversion technique and reflection tomography. This resulted in depth migration of the uppermost part of the profile (to a depth of 9 km), which was confirmed by the stratigraphy of the Amanda 1bis well. The reprocessing significantly improved the image of the profile and enabled new information on the seismo-stratigraphy to be gleaned from the vintage data. This was particularly important for science and research, as new seismic data with high penetration depths, such as the CROP profiles, are currently difficult to acquire. [ABSTRACT FROM AUTHOR]

Interferometric stacking is a useful technique to detect active slope deformation over vast mountainous area. Compared to the analysis of single interferograms, the stacking approach improves the signal to noise ratio and deformation signals become clearer. In this work, we used stacked interferograms to detect active slow-moving landslides during the years 2015 to 2019 over a 1200 km2 portion of the Northern Apennines of Italy. C-band Sentinel 1 SAR images were used to create short temporal baseline (6 to 24 days) interferograms which limit decorrelation and maximize the range of measurable displacement rates. Then we operated a further selection of interferograms based on coherence and visual inspection, before stacking over multiple time scales (1 month to years). The products of the analysis are ground displacement maps where the presence of residual noise is inversely proportional to the duration of the stack and the deformation signal is clearly recognized. Results show that only a small fraction of the mapped landslide deposits are experiencing deformation that can be detected by differential interferometry. In particular, we identified 118 InSAR deformation signals corresponding to ongoing gravitational slope deformations over the 9916 landslides mapped in the area. Active movements are mostly located on landslides that have undergone catastrophic reactivation in relatively recent times. Annual interferometric stacks proved better suited to detect active slope movements, while <15 % of our deformation signals can only be detected by inspecting monthly stacks. Active slow-moving landslides show variable displacement rates in monthly stacks. Periods of dormancy alternate to accelerations that may lead to actual catastrophic failures or, more often, determine finite periods of sustained slow movement before the displacement rates drop below the detection limit. We compared the evolutionary trends of the phenomena to the occurrence of rainfall events. For this purpose, we use the probability of landslide occurrence which is associated with a rainfall event based on a territorial alert threshold. Results show that, at increasing landslide occurrence probabilities, an increasing fraction of actively deforming landslides can be detected by InSAR. [ABSTRACT FROM AUTHOR]

In this paper we report the observations of HD189733b, Kepler-41b, Kepler-42b, GJ 436b, WASP-77ab, HAT-P-32b and EPIC 211818569 as measured at the Osservatorio Polifunzionale del Chianti, a new astro-nomical site in Italy. Commissioning observing runs have been done in order to test capabilities, systematics and limits of the system and to improve its accuracy. For this purpose, a software algorithm has been developed to estimate the differential photometric error of any transit observation, so that the integration time can be chosen to reach optimal signal-to-noise ratios, and to obtain a picture of what kind of transits this setup can reveal. Currently, the system is able to reach an accuracy of about 1 mmag and so it is ready for the much needed exoplanetary transit follow-up. [ABSTRACT FROM AUTHOR]

To evaluate the site response using both empirical approaches (e.g. standard spectral ratio, ground motion models (GMMs), generalized inversion techniques, etc.) and numerical 1-D/2-D analyses, the definition of the reference motion, that is the ground motion recorded at stations unaffected by site-effects due to topographic, stratigraphic or basin effects, is needed. The main objective of this work is to define a robust strategy to identify the seismic stations that can be considered as reference rock sites, using six proxies for the site response: three proxies are related to the analysis of geophysical and seismological data (the repeatable site term from the residual analysis, the resonance frequencies from horizontal-to-vertical spectral ratios on noise or earthquake signals, the average shear wave velocity in the first 30 m); the remaining ones concern geomorphological and installation features (outcropping rocks or stiff soils, flat topography and absence of interaction with structures). We introduce a weighting scheme to take into account the availability and the quality of the site information, as well as the fulfillment of the criterion associated to each proxy. We also introduce a hierarchical index, to take into account the relevance of the proposed proxies in the description of the site effects, and an acceptance threshold for reference rock sites identification. The procedure is applied on a very large data set, composed by accelerometric and velocimetric waveforms, recorded in Central Italy in the period 2008–2018. This data set is composed by more than 30 000 waveforms relative to 450 earthquakes in the magnitude range 3.2–6.5 and recorded by more than 450 stations. A total of 36 out of 133 candidate stations are identified as reference sites: the majority of them are installed on rock with flat topography, but this condition is not sufficient to guarantee the absence of amplifications, especially at high frequencies. Seismological analyses are necessary to exclude stations affected by resonances. We test the impact of using these sites by calibrating a GMMs. The results show that for reference rock sites the median predictions are reduced down to about 45 per cent at short periods in comparison to the generic rock motions. [ABSTRACT FROM AUTHOR]

Automated systems for detecting deformation in satellite interferometric synthetic aperture radar (InSAR) imagery could be used to develop a global monitoring system for volcanic and urban environments. Here, we explore the limits of a convolutional neural networks for detecting slow, sustained deformations in wrapped interferograms. Using synthetic data, we estimate a detection threshold of 3.9 cm for deformation signals alone and 6.3 cm when atmospheric artifacts are considered. Overwrapping reduces this to 1.8 and 5.2 cm, respectively, as more fringes are generated without altering signal to noise ratio. We test the approach on time series of cumulative deformation from Campi Flegrei and Dallol, where overwrapping improves classification performance by up to 15%. We propose a mean‐filtering method for combining results of different wrap parameters to flag deformation. At Campi Flegrei, deformation of 8.5 cm/year was detected after 60 days and at Dallol, deformation of 3.5 cm/year was detected after 310 days. This corresponds to cumulative displacements of 3 and 4 cm consistent with estimates based on synthetic data. Key Points: We adapt a pretrained convolutional neural networks for detecting slow, steady deformation in InSAR imagesSynthetic tests show the detection threshold is 6.3 cm in volcanic environments but is reduced to 5.0 cm by decreasing wrapping intervalWe demonstrate the method on cumulative time series of interferograms from Campi Flegrei, Italy (8.5 cm/yearr) and Dallol, Ethopia (3.5 cm/year) [ABSTRACT FROM AUTHOR]

The PRISMA satellite mission launched on March 22nd, 2019 is one of the latest spaceborne imaging spectroscopy mission for Earth Observation. The PRISMA satellite comprises a high-spectral resolution VNIR-SWIR imaging spectrometer and a panchromatic camera. In summer 2019, first operations during the commissioning phase were mainly devoted to acquisitions in specific areas for evaluating instrument functioning, in-flight performance, and mission data product accuracy. A field and airborne campaign was carried out over an agriculture area in Italy to collect in-situ multi-source spectroscopy measurements at different scales simultaneously with PRISMA. The spectral, radiometric and spatial performance of PRISMA Level 1 Top-Of-Atmosphere radiance (LTOA) product were analyzed. The in-situ surface reflectance measurements over different landcovers were propagated to LTOA using MODTRAN5 radiative transfer simulations and compared with satellite observations. Overall, this work offers a first quantitative evaluation about the PRISMA mission performance and imaging spectroscopy LTOA data product consistency. Our results show that the spectral smile is less than 5 nm, the average spectral resolution is 13 nm and 11 nm (VNIR and SWIR respectively) and it varies ±2 nm across track. The radiometric comparison between PRISMA and field/airborne spectroscopy shows a difference lower than 5% for NIR and SWIR, whereas it is included in the 2–7% range in the VIS. The estimated instrument signal to noise ratio (SNR) is ≈400–500 in the NIR and part of the SWIR (<1300 nm), lower SNR values were found at shorter (<700 nm) and longer wavelengths (>1600 nm). The VNIR-to-SWIR spatial co-registration error is below 8 m and the spatial resolution is 37.11 m and 38.38 m for VNIR and SWIR respectively. The results are in-line with the expectations and mission requirements and indicate that acquired images are suitable for further scientific applications. However, this first assessment is based on data from a rural area and this cannot be fully exhaustive. Further studies are needed to confirm the performance for other land cover types like snow, inland and coastal waters, deserts or urban areas. • The PRISMA mission is successfully operating and collecting data after the launch. • In-situ simultaneous field/airborne spectroscopy data were compared to PRISMA. • PRISMA spectral resolution is 13–11 nm (VNIR-SWIR), smile is lower of 5 nm. • A radiometric difference of 2–7% was observed between PRISMA and in-situ data. • VNIR-to-SWIR spatial co-registration error is lower of 8 m. [ABSTRACT FROM AUTHOR]

Forty-seven samples of milk taken from goat and ovine farms in Calabria (southern Italy) between April and May 2010 were analysed. Analyses were carried out by ion chromatography (ICS 1000; Dionex). For method validation, RSDs (%) on retention times and on peak area were determined by considering a mixture of standard anions at the concentration level of 0.1–30 mg l−1for chloride, bromide, nitrite, nitrate, sulfate and phosphate. The higher RSDs were 1.4% and 2.2% for retention times and 2.4% and 3.7% for areas for intra- and inter-day repeatability, respectively. Good linearity was observed in each concentration range, with linear correlation coefficients (R2) better than 0.987. The LODs and LOQs were calculated experimentally as signal-to-noise ratios of 3 and 10, respectively. Analysis of the results obtained indicated that phosphates were the most abundant anion (1409–3050 mg l−1) followed by chloride (679–2568 mg l−1) and sulfates (25–341 mg l−1). Nitrates were found to be lower at 146 mg l−1(the maximum value observed). The values of anions found in this work are in agreement with those reported in the literature for cow's milk. There are no significant differences between ovine and goat's milk samples. The method used for this analysis of anions combines rapidity with high precision, accuracy and sensitivity; therefore, it is suitable for routine analysis. Moreover, one of the most obvious advantages of this technique is that multiple elements can be determined in one sample with no serial dilutions and the complete analysis can be performed by using only one instrument. [ABSTRACT FROM AUTHOR]

Local and regional earthquakes recorded in 2007 by two seismic arrays at Gran Sasso (Italy), one located at surface and one at 1.4 km depth, have been analyzed. Polarization properties of the seismic wavefield have been estimated at both arrays on a short sliding window and in several frequency bands. Array methods were also applied, and the estimated slowness and backazimuth were used to compute the stacking of phase shifted signals in order to improve the signal to noise ratio. Results of polarization computed over single station and array stacked signals have been compared between the two arrays. A well defined polarization azimuth, roughly perpendicular to the main massif ridges, is evident at surface in a broad frequency band. This is observed for earthquake body waves and coda waves. On the contrary, underground the same effect is slightly visible only at very low frequency. [ABSTRACT FROM AUTHOR]

This work deals with the reprocessing of the M12A CROP marine seismic profile, that crosses the northern Tyrrhenian Sea, south of Elba Island. The reprocessing was carried out to improve the visibility and resolution of the structures corresponding to the lower crust (two-way traveltimes lower than 4 s) that are located at depth. In this time window, we apply recently developed methodologies to enhance the signal-to-noise ratio, paying particular attention to the suppression of the short and long period reverberations and to the velocity model building for depth migration. The velocity field used for the depth conversion is iteratively updated by means of the migration velocity analysis on common image gathers. The final products of this work are time and post-stack, depthmigrated sections that can contribute to the understanding of the structural complexity of the investigated area. [ABSTRACT FROM AUTHOR]

Abstract: PRISMA (PRecursore IperSpettrale della Missione Applicativa) hyperspectral instrument is an advanced hyperspectral sensor including a panchromatic camera at medium resolution. The instrument is the focus of the new Earth observation mission that a consortium of Italian companies has started developing under contract of Italian Space Agency. Key features of the instrument are the very high requirement for signal-to-noise and the high quality of data that have to be provided. To meet these demanding figures the optical system has been based on a high transmittance optical system, including a single mirror telescope and two prism spectrometers based on an innovative concept to minimize number of optical elements, while high performance detectors have been chosen for the photon detection. To provide the required data quality for the entire mission lifetime an accurate calibration unit (radiometric and spectral) will be included in the instrument optomechanical assembly. The thermo-mechanical design of the instrument is based on innovative concepts, considering that the use of prism spectrometers implies a tight control of temperature variations to guarantee the stability of all instrument features once in orbit. The presented paper describes the concepts and design principle of the optomechanical assembly of the instrument, at the present status of development. [Copyright &y& Elsevier]

Hydraulic fracture-induced microseismic events in producing oil and gas fields are usually small, and noise levels are high at the surface as a result of the heavy equipment in use. Similarly, in nonhydrocarbon settings, arrays for detecting local earthquakes will benefit from reduced noise levels and the ability to detect smaller events will be increased. We propose a frequency-dependent multichannel Wiener filtering technique with linear constraints that uses an adaptive least-squares method to remove coherent noise in seismic array data. The noise records on several reference channels are used to predict the noise on a primary channel and then can be subtracted from the observed data. On a test with an unconstrained version of this filter, maximal noise suppression leads to signal distortion. Two methods of imposing constraints then achieve signal preservation. In one case study, synthetic signals are added to noise from a pilot deployment of a hexagonal array (nine three-component seismometers, approximately 150 x 150 m) above a gas field; noise levels are suppressed by up to 11 dB (at 2-10 Hz). In a second case study, natural seismicity recorded at a dense array (∼ 10 m spacing) in Italy is used, where the application of the filter improves the signal- to-noise ratio (S/N) more than 20 dB (at 2-15 Hz) using 35 stations. In both cases, the performance of the multichannel Wiener filters is significantly better than stacking, especially at lower frequencies where stacking does not help to suppress the coherent noise. The unconstrained version of the filter yields the best improvement in signal-to-noise ratio, but the constrained filter is useful when waveform distortion is unacceptable. [ABSTRACT FROM AUTHOR]

We analyse the earthquakes catalogues for Italy, South California, and Greece across the COVID-19 lockdown period for each country. The results for Italy and Greece show that, even if the reduction of the signal to noise ratio has improved the earthquake detection capability, the completeness magnitude remains substantially unchanged, making the improved detection capability ineffective from the statistical point of view. A slight reduction (0.2) of the completeness magnitude is observed for South California, likely related to the relatively higher number of seismic stations located close to urban areas. Our findings suggest that—given the present configuration of the seismic network considered here—only an important decrease in the station spacing can produce a significant decrease of the completeness magnitude. [ABSTRACT FROM AUTHOR]

The aim of the study was to find the correlation between specific risk factors for hearing impairment as well as between risk factors and TEOAE screening results in neonates at risk for hearing impairment. Seventy-one newborns at risk for hearing impairment have been included in the study. Strong correlations between specific risk factors were found. Investigation of the relationship between specific risk factors and TEOAE signal-to-noise ratio (SNR) showed that in children with genetic risk factors, TORCH (toxoplasmosis, rubella, CMV, herpes virus, others) infections and in those treated with ototoxic drugs, the values of SNRs were significantly lower than in children at risk who did not present those factors. In case of hyperbilirubinaemic children the values of SNR were significantly higher than in the controls. In our opinion these relationships may be partially explained by the positive predictive values of these risk factors, but other intrinsic factors may also be involved. [ABSTRACT FROM AUTHOR]

The Italian Government has decreed a series of progressive restrictions to delay the COVID-19 pandemic diffusion in Italy since March 10, 2020, including limitation in individual mobility and the closure of social, cultural, economic and industrial activities. Here we show the lockdown effect in Northern Italy, the COVID-19 most affected area, as revealed by noise variation at seismic stations. The reaction to lockdown was slow and not homogeneous with spots of negligible noise reduction, especially in the first week. A fresh interpretation of seismic noise variations in terms of socio-economic indicators sheds new light on the lockdown efficacy pointing to the causes of such delay: the noise reduction is significant where non strategic activities prevails, while it is small or negligible where dense population and strategic activities are present. These results are crucial for the a posteriori interpretation of the pandemic diffusion and the efficacy of differently targeted political actions.

We develop a probabilistic framework based on the conjunction of states of information between data and model, to jointly retrieve earthquake source parameters and anelastic attenuation factor from inversion of displacement amplitude spectra. The evaluation of the joint probability density functions (PDFs) enables us to take into account between-parameter correlations in the final estimate of the parameters and related uncertainties. Following this approach, we first search for the maximum of the a-posteriori PDF through the basin hopping technique that couples a global exploration built on a Markov chain with a local deterministic maximization. Then we compute statistical indicators (mean, variance and correlation coefficients) on source parameters and anelastic attenuation through integration of the PDF in the vicinity of the maximum likelihood solution. Definition of quality criteria based on the signal to noise ratio and the similarity of the marginal PDFs with a Gaussian function enables us to the define the frequency domain for the inversion and to get rid of unconstrained solutions. We perform synthetic tests to assess theoretical correlations as a function of the signal to noise ratio and to define the minimum bandwidth around the corner frequency for consistent parameter resolution. As an application, we finally estimate the source parameters for the 2016-2017 Central Italy seismic sequence. We found that the classical scaling between the seismic moment and the corner frequency holds, with an average stress drop of 2.1 ± 0.3 MPa. However, the main events in the sequence exhibit a stress drop larger than the average value. Finally, the small seismic efficiency indicates a stress overshoot, possibly due to dynamic effects or large frictional efficiency. [ABSTRACT FROM AUTHOR]

In recent years artificial intelligence methods for detecting anomalies and abnormalities in time series have been successfully employed due to good performances in terms of high accuracy and speed. The aim of this paper is to exploit a dataset of small earthquakes recorded by a temporary, local network of 10 seismic stations located in an area of 10 km^2 in central Italy. During one year of observation about 600 earthquakes with 0 < ML < 2 have been localised by an highly optimised picking routine and also verified by experienced analysts. The resulting dataset consists of 4300 waveforms with labelled seismic phases together with a series of 4300 randomly chosen waveforms containing seismic noise. The first step of our approach is to apply rolling mean and Savitzky-Golay filters to seismic waveforms in order to improve the signal to noise ratio in the dataset. In the second step Long Short Term Memory (LSTM) networks are trained to learn the seismic noise contained in the waveforms recordings so that seismic phases can be recognized as anomalies. The LSTM model is able to detect seismic phases with an efficiency of about 90%. An error vector is computed subtracting observed and LSTM predicted values, respectively. Then a multivariate Gaussian distribution is used to fit the error vector providing an improvement to the seismic phases detection. A final test is performed exploiting a subset of the original dataset where we combine 1000 seismic and 1000 noise waveforms. The designed anomaly detection algorithm is able to identify more than 98% of the seismic waveforms. [ABSTRACT FROM AUTHOR]

Purpose: The primary aim of this study was to develop and examine the potentials of a new speech-in-noise test in discriminating the favorable listening conditions targeted in the acoustical design of communication spaces. The test is based on the recognition and recall of disyllabic word sequences. A secondary aim was to compare the test with current speech-in-noise tests, assessing its benefits and limitations., Method: Young adults (19-40 years old), self-reporting normal hearing, were presented with the newly developed Words Sequence Test (WST; 16 participants, Experiment 1) and with a consonant confusion test and a sentence recognition test (Experiment 2, 36 participants randomly assigned to the 2 tests). Participants performing the WST were presented with word sequences of different lengths (from 2 up to 6 words). Two listening conditions were selected: (a) no noise and no reverberation, and (b) reverberant, steady-state noise (Speech Transmission Index: 0.47). The tests were presented in a closed-set format; data on the number of words correctly recognized (speech intelligibility, IS) and the response times (RTs) were collected (onset RT, single words' RT)., Results: It was found that a sequence composed of 4 disyllabic words ensured both the full recognition score in quiet conditions and a significant decrease in IS results when noise and reverberation degraded the speech signal. RTs increased with the worsening of the listening conditions and the number of words of the sequence. The greatest onset RT variation was found when using a sequence of 4 words. In the comparison with current speech-in-noise tests, it was found that the WST maximized the IS difference between the selected listening conditions as well as the RT increase., Conclusions: Overall, the results suggest that the new speech-in-noise test has good potentials in discriminating conditions with near-ceiling accuracy. As compared with current speech-in-noise tests, it appears that the WST with a 4-word sequence allows for a finer mapping of the acoustical design target conditions of public spaces through accuracy and onset RT data.

This work concerns speech intelligibility tests and measurements in three primary schools in Italy, one of which was conducted before and after an acoustical treatment. Speech intelligibility scores (IS) with different reverberation times (RT) and types of noise were obtained using diagnostic rhyme tests on 983 pupils from grades 2-5 (nominally 7-10 year olds), and these scores were then correlated with the Speech Transmission Index (STI). The grade 2 pupils understood fewer words in the lower STI range than the pupils in the higher grades, whereas an IS of ~97% was achieved by all the grades with a STI of 0.9. In the presence of traffic noise, which resulted the most interfering noise, a decrease in RT from 1.6 to 0.4 s determined an IS increase on equal A-weighted speech-to-noise level difference, S/N(A), which varied from 13% to 6%, over the S/N(A) range of -15 to +6 dB, respectively. In the case of babble noise, whose source was located in the middle of the classroom, the same decrease in reverberation time leads to a negligible variation in IS over a similar S/N(A) range., (© 2012 Acoustical Society of America.)