Implementazione di una nuova procedura per caratterizzare la forma di particelle mediante misure al CAMSIZER e algoritmi di clustering

In this work we present the calibration phase of a new procedure for the characterization of the shape of pyroclastic particles. This research has been granted by INGV of Catania, with funds deriving from the “Progetto Giovani”, in collaboration with Retsch Technology in Haan. The innovation of this procedure arises from the use of CAMSIZER (an instrument developed by the German leader company). This instrument permits to obtain very important information both on size and shape parameters of a high number of particles (hundreds of thousands data). Moreover, we used clustering and classification algorithms in order to group particles according to their morphologic characteristics. This calibration phase has been tested only on standard materials with regular geometries such as cubes, spheres and cylinders. In the future we will apply this methodology to volcanic ash particles that, as well-known, are characterized by irregular morphologies

Classes of exact wavefunctions for general time-dependent Dirac Hamiltonians in 1+1 dimensions

In this work we construct two classes of exact solutions for the most general time-dependent Dirac Hamiltonian in 1+1 dimensions. Some problems regarding to some formal solutions in the literature are discussed. Finally the existence of a generalized Lewis-Riesenfeld invariant connected with such solutions is discussed

Changes in Motor, Cognitive, and Behavioral Symptoms in Parkinson's Disease and Mild Cognitive Impairment During the COVID-19 Lockdown

Objective: The effects of the COVID-19 lockdown on subjects with prodromal phases of dementia are unknown. The aim of this study was to evaluate the motor, cognitive, and behavioral changes during the COVID-19 lockdown in Italy in patients with Parkinson's disease (PD) with and without mild cognitive impairment (PD-MCI and PD-NC) and in patients with MCI not associated with PD (MCInoPD). Methods: A total of 34 patients with PD-NC, 31 PD-MCI, and 31 MCInoPD and their caregivers were interviewed 10 weeks after the COVID-19 lockdown in Italy, and changes in cognitive, behavioral, and motor symptoms were examined. Modified standardized scales, including the Neuropsychiatric Inventory (NPI) and the Movement Disorder Society, Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts I and II, were administered. Multivariate logistic regression was used to evaluate associated covariates by comparing PD-NC vs. PD-MCI and MCInoPD vs. PD-MCI. Results: All groups showed a worsening of cognitive (39.6%), pre-existing (37.5%), and new (26%) behavioral symptoms, and motor symptoms (35.4%) during the COVID-19 lockdown, resulting in an increased caregiver burden in 26% of cases. After multivariate analysis, PD-MCI was significantly and positively associated with the IADL lost during quarantine (OR 3.9, CI 1.61–9.58), when compared to PD-NC. In the analysis of MCInoPD vs. PD-MCI, the latter showed a statistically significant worsening of motor symptoms than MCInoPD (OR 7.4, CI 1.09–45.44). Regarding NPI items, nighttime behaviors statistically differed in MCInoPD vs. PD-MCI (16.1% vs. 48.4%, p = 0.007). MDS-UPDRS parts I and II revealed that PD-MCI showed a significantly higher frequency of cognitive impairment (p = 0.034), fatigue (p = 0.036), and speech (p = 0.013) than PD-NC. On the contrary, PD-MCI showed significantly higher frequencies in several MDS-UPDRS items compared to MCInoPD, particularly regarding pain (p = 0.001), turning in bed (p = 0.006), getting out of bed (p = 0.001), and walking and balance (p = 0.003). Conclusion: The COVID-19 quarantine is associated with the worsening of cognitive, behavioral, and motor symptoms in subjects with PD and MCI, particularly in PD-MCI. There is a need to implement specific strategies to contain the effects of quarantine in patients with PD and cognitive impairment and their caregivers

State of the California current 2012-13: No such thing as an “average” year

This report reviews the state of the California Current System (CCS) between winter 2012 and spring 2013, and includes observations from Washington State to Baja California. During 2012, large-scale climate modes indicated the CCS remained in a cool, productive phase present since 2007. The upwelling season was delayed north of 42°N, but regions to the south, especially 33° to 36°N, experienced average to above average upwelling that persisted throughout the summer. Contrary to the indication of high production suggested by the climate indices, chlorophyll observed from surveys and remote sensing was below average along much of the coast. As well, some members of the forage assemblages along the coast experienced low abundances in 2012 surveys. Specifically, the concentrations of all lifestages observed directly or from egg densities of Pacific sardine, Sardinops sagax, and northern anchovy, Engraulis mordax, were less than previous years’ survey estimates. However, 2013 surveys and observations indicate an increase in abundance of northern anchovy. During winter 2011/2012, the increased presence of northern copepod species off northern California was consistent with stronger southward transport. Krill and small-fraction zooplankton abundances, where examined, were generally above average. North of 42°N, salps returned to typical abundances in 2012 after greater observed concentrations in 2010 and 2011. In contrast, salp abundance off central and southern California increased after a period of southward transport during winter 2011/2012. Reproductive success of piscivorous Brandt’s cormorant, Phalacrocorax penicillatus, was reduced while planktivorous Cassin’s auklet, Ptychoramphus aleuticus was elevated. Differences between the productivity of these two seabirds may be related to the available forage assemblage observed in the surveys. California sea lion pups from San Miguel Island were undernourished resulting in a pup mortality event perhaps in response to changes in forage availability. Limited biological data were available for spring 2013, but strong winter upwelling coastwide indicated an early spring transition, with the strong upwelling persisting into early summer

The Herschel Multi-tiered Extragalactic Survey: HerMES

The Herschel Multi-tiered Extragalactic Survey, HerMES, is a legacy program designed to map a set of nested fields totalling ~380 deg^2. Fields range in size from 0.01 to ~20 deg^2, using Herschel-SPIRE (at 250, 350 and 500 \mu m), and Herschel-PACS (at 100 and 160 \mu m), with an additional wider component of 270 deg^2 with SPIRE alone. These bands cover the peak of the redshifted thermal spectral energy distribution from interstellar dust and thus capture the re-processed optical and ultra-violet radiation from star formation that has been absorbed by dust, and are critical for forming a complete multi-wavelength understanding of galaxy formation and evolution. The survey will detect of order 100,000 galaxies at 5\sigma in some of the best studied fields in the sky. Additionally, HerMES is closely coordinated with the PACS Evolutionary Probe survey. Making maximum use of the full spectrum of ancillary data, from radio to X-ray wavelengths, it is designed to: facilitate redshift determination; rapidly identify unusual objects; and understand the relationships between thermal emission from dust and other processes. Scientific questions HerMES will be used to answer include: the total infrared emission of galaxies; the evolution of the luminosity function; the clustering properties of dusty galaxies; and the properties of populations of galaxies which lie below the confusion limit through lensing and statistical techniques. This paper defines the survey observations and data products, outlines the primary scientific goals of the HerMES team, and reviews some of the early results.Comment: 23 pages, 17 figures, 9 Tables, MNRAS accepte

Small but crucial : the novel small heat shock protein Hsp21 mediates stress adaptation and virulence in Candida albicans

Peer reviewedPublisher PD

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Calibration of the Logarithmic-Periodic Dipole Antenna (LPDA) Radio Stations at the Pierre Auger Observatory using an Octocopter

An in-situ calibration of a logarithmic periodic dipole antenna with a frequency coverage of 30 MHz to 80 MHz is performed. Such antennas are part of a radio station system used for detection of cosmic ray induced air showers at the Engineering Radio Array of the Pierre Auger Observatory, the so-called Auger Engineering Radio Array (AERA). The directional and frequency characteristics of the broadband antenna are investigated using a remotely piloted aircraft (RPA) carrying a small transmitting antenna. The antenna sensitivity is described by the vector effective length relating the measured voltage with the electric-field components perpendicular to the incoming signal direction. The horizontal and meridional components are determined with an overall uncertainty of 7.4^{+0.9}_{-0.3} % and 10.3^{+2.8}_{-1.7} % respectively. The measurement is used to correct a simulated response of the frequency and directional response of the antenna. In addition, the influence of the ground conductivity and permittivity on the antenna response is simulated. Both have a negligible influence given the ground conditions measured at the detector site. The overall uncertainties of the vector effective length components result in an uncertainty of 8.8^{+2.1}_{-1.3} % in the square root of the energy fluence for incoming signal directions with zenith angles smaller than 60{\deg}.Comment: Published version. Updated online abstract only. Manuscript is unchanged with respect to v2. 39 pages, 15 figures, 2 table