Low dose of Rotigotine in post-stroke patients with vascular parkinsonism and obstructive sleep apnoea syndrome, effects on quality of life and rehabilitation therapy

Stroke is a frequent cause of disability in U.S.A. (200.000/ year). Aim: The aim of this study is to underline the effect of low dose of Rotigotine patches 2 mg/24 h, a complete dopamine agonist with continuous dopaminergic stimulation through the transdermal administration, in elderly with recent stroke and vascular Parkinsonism about quality of life and adherence to rehabilitation therapy. Methods: We have enrolled 6 elderly patients (3 males and 3 females, range age 60 – 95 years) with recent ischemic and vascular Parkinsonism. We have evaluated quality of life and cognitive function with UPDRS part III, MMSE, ADL, IADL and Morinsky Scale. At the same time we have evaluated the adherence to therapy and timing of rehabilitation therapy before and post-administration of Rotigotine 2 mg/24 hours. Conclusion: In conclusion, Rotigotine could be a new useful approach in the treatment of elderly patients with recent ischemic and hemorrhagic stroke correlated with vascular Parkinsonism which can lead to an akinesia with the need to start rehabilitation therapy. Our preliminary data gives comfortable results but, at this time, we have enrolled only few patients to give conclusive results

Changes in the state of ice buildup on a composite plate: ultrasonic monitoring and assessment.

From airplane wings to overhead power lines, through large blades of wind turbines, a buildup of ice can cause problems ranging from low performance to catastrophic failure. Therefore, it is of the utmost importance to control or prevent ice formation, especially on the critical areas of the structures. However, de-icing and anti-icing countermeasures can result energetically expensive and harmful to the environment. In addition, excessive use thereof will reduce the life of an ice protection system (IPS) and introduce fatigue to the controlled structures. Therefore, in order to manage properly the available resources, it is desirable to have an IPS that can both detect ice formation and monitor the ice thickness on critical surfaces. This would allow the IPS to operate when it is necessary. Ultrasonic guided-wave-based techniques have proved to be reliable for ice detection but approaches to assess ice state over time have not been reported yet. The present work investigates the interaction of ultrasonic waves, propagating in a composite plate, with an ice mass changing state, as it melts. The use of a metric is discussed as indicator of ice condition variation

PRIN Project 2010-11 “Active and recent geodynamics of Calabrian Arc and accretionary complex in the Ionian Sea”: new constraints from geological, geodetic and seismological data

This contribution illustrates the preliminary results of our Research Unit in the PRIN Project 2010-11, which focuses on active and recent geodynamics of Calabrian Arc. The integration of the new geological, geodetic and seismological data supports the inferred recent plate boundary reorganization in the central-southern Mediterranean, where the regional GNNS velocity fields point to a deceleration or cessation of Calabrian Arc migration, and to extension along the axis of the Calabrian Arc, accommodated by normal faulting (e.g. Capo Vaticano and Messina Straits (Aloisi et al., 2012; Pepe et al., 2014; Spampinato et al., 2014). The study of the lateral borders of the Arc revealed that oblique strike-slip displacement has occurred during its southeastwards migration. Active dextral transtension is occurring along the NNW-striking Aeolian-Tindari Letojanni fault system, forming the southern boundary of the Arc. It joins to the north other two boundaries characterized by different tectonic regimes, a contractional belt in the southern Tyrrhenian sea, where a tectonic inversion has occurred since the middle Pleistocene, and the extensional one in northeastern Sicily and western Calabria (Palano et al., 2012; Barreca et al., 2014a). Along the northern boundary of the Arc, the so-called Pollino line (onshore) and Sibari Line (offshore), active deformation has been documented on folds growing above blind oblique thrust ramps extending offshore, controlling the present morphobathymetric pattern (Santoro et al., 2013). Although external to the Calabrian Arc, we also devoted attention to the front of the Maghrebian thrust belt in western Sicily where we presented the first evidence of historical co-seismic deformation on a thrust array running from the Belice area to the Sicily Channel (Barreca et al., 2014b). Morphotectonic analysis and fault numeric modeling of uplifted Pleistocene marine terraces and Holocene paleo-shorelines has documented that most of the uplift along the Calabrian Arc is related to regional processes and the residual to coseismic displacement on major faults, both transpressional and transtensional, at the borders, and extensional along the chain axis

Exploring waste-collection fleet data: challenges in a real-world use case from multiple data providers

In the age of connected vehicles, large amounts of data can be collected while driving through a variety of on-board sensors. The information collected can be used for various types of data-driven analytics that can be of great benefit to both vehicle owners, e.g., to reduce costs by means of predictive maintenance, and to society as a whole, e.g., to optimize mobility behavior. Prior to any real-world data analysis, an investigation and characterization of the available data is of utmost importance in order to evaluate the quality and quantity of the data and to set the right expectations. In this paper, we focus on the data exploration and characterization step, which is necessary to avoid inconsistencies in the collected parameters and to enable valid, data-driven modeling. The proposed data exploration considers both the frequency of samples and their values for all monitored parameters. A specific cross-provider data comparison is performed to compare values collected for the same vehicle at the same time from different fleet monitoring data providers. The study is applied to a real-world use case with months of data from dozens of vehicles deployed in the waste collection service managed by SEA, Soluzioni Eco Ambientali, in Italy. The analyzes uncover unexpected behaviors in the measurements and lead to their early identification, bringing great benefits to the company operating the fleet by improving data collection and enabling a safe modeling phase

A Comparative Evaluation of Deep Learning Techniques for Photovoltaic Panel Detection From Aerial Images

Solar energy production has significantly increased in recent years in the European Union (EU), accounting for 12% of the total in 2022. The growth in solar energy production can be attributed to the increasing adoption of solar photovoltaic (PV) panels, which have become cost-effective and efficient means of energy production, supported by government policies and incentives. The maturity of solar technologies has also led to a decrease in the cost of solar energy, making it more competitive with other energy sources. As a result, there is a growing need for efficient methods for detecting and mapping the locations of PV panels. Automated detection can in fact save time and resources compared to manual inspection. Moreover, the resulting information can also be used by governments, environmental agencies and other companies to track the adoption of renewable sources or to optimize energy distribution across the grid. However, building effective models to support the automated detection and mapping of solar photovoltaic (PV) panels presents several challenges, including the availability of high-resolution aerial imagery and high-quality, manually-verified labels and annotations. In this study, we address these challenges by first constructing a dataset of PV panels using very-high-resolution (VHR) aerial imagery, specifically focusing on the region of Piedmont in Italy. The dataset comprises 105 large-scale images, providing more than 9,000 accurate and detailed manual annotations, including additional attributes such as the PV panel category. We first conduct a comprehensive evaluation benchmark on the newly constructed dataset, adopting various well-established deep-learning techniques. Specifically, we experiment with instance and semantic segmentation approaches, such as Rotated Faster RCNN and Unet, comparing strengths and weaknesses on the task at hand. Second, we apply ad-hoc modifications to address the specific issues of this task, such as the wide range of scales of the installations and the sparsity of the annotations, considerably improving upon the baseline results. Last, we introduce a robust and efficient post-processing polygonization algorithm that is tailored to PV panels. This algorithm converts the rough raster predictions into cleaner and more precise polygons for practical use. Our benchmark evaluation shows that both semantic and instance segmentation techniques can be effective for detecting and mapping PV panels. Instance segmentation techniques are well-suited for estimating the localization of panels, while semantic solutions excel at surface delineation. We also demonstrate the effectiveness of our ad-hoc solutions and post-processing algorithm, which can provide an improvement up to +10% on the final scores, and can accurately convert coarse raster predictions into usable polygons

Seismotectonics of the active thrust front in southwestern Sicily: hints on the Belice and Selinunte seismogenic sources

We present a seismotectonic model of the active thrust front in western Sicily, which includes the area hit by the 1968 Belice earthquake sequence. The ~40 km long South-WEstern Sicilian Thrust (SWEST) is formed by two aligned albeit non-parallel fault arrays, the Granitola-Castelevetrano Thrust System (GCTS) in the west and the Partanna- Poggioreale Thrust System (PPTS) in the east. The ~NE-SW trending, NW-dipping GCTS straddles from the Pelagian coastline to Castelvetrano, is ~18 km long and composed of two segments, with the northern, ~12 km long one showing geodetic and geologic evidence of active deformation (Barreca et al., 2014). The segment is marked by a sharp gradient in Differential SAR interferometry (DinSAR and STAMPs) and GPS velocity fields. Geologic evidence include an up to 60 m high, and up to 15° steep scarp, which is the fore-limb of a broad fold involving Lower Pleistocene shore calcarenites, and cm-scale reverse displacement of an ancient road dated as early Bronze-Hellenistic age. Inversion of fault slip-lineation data from structures displacing the archaeological remains yields a ~N110°E shortening axis, consistent with the geodetic shortening direction estimated from GPS differential velocities. The ~ENE-WSW trending PPTS stretches from Partanna to the macro-seismic area of the 1968 earthquake sequence and is composed of two ~10 km long segments limited by relay ramps. Although geologic and geodetic evidence of deformation are less clear than for the GCTS, we nonetheless observe a gradient in interferometry data for the western segment, and evidence of slow deformation (creep?) in historical to recent (last ~400 yr?) man-made structures. Integration of geologic, geodetic and seismology data suggests the active folds and thrusts are the uppermost expression of steep (45°) crustal ramps (Monaco et al., 1996) which upthrust the Saccense platform at depth. Based on macroseismic and seismological evidence (Monaco et al., 1996), we contend that the PPTS was partly activated during the 1968 sequence, and that rupture stopped at the junction with the GCTS. The current geodetic strain accumulation on the GCTS, on the other hand, suggests that the fault array has been significantly loaded, and that its last important co-seismic event could have been caused the 4th–5th century A.D. destruction of Selinunte (Bottari et al., 2009)