The impact of low energy proton damage on the operational characteristics of EPIC-MOS CCDs

The University of Tübingen 3.5 MeV Van de Graaf accelerator facility was used to investigate the effect of low energy protons on the performance of the European Photon Imaging Camera (EPIC), metal–oxide semiconductor (MOS), charge coupled devices (CCDs). Two CCDs were irradiated in different parts of their detecting areas using different proton spectra and dose rates. Iron-55 was the calibration source in all cases and was used to measure any increases in charge transfer inefficiency (CTI) and spectral resolution of the CCDs. Additional changes in the CCD bright pixel table and changes in the low X-ray energy response of the device were examined. The Monte Carlo code Stopping Range of Ions in Matter (SRIM) was used to model the effect of a 10 MeV equivalent fluence of protons interacting with the CCD. Since the non-ionising energy loss (NIEL) function could not be applied effectively at such low proton energies. From the 10 MeV values, the expected CTI degradation could be calculated and then compared to the measured CTI changes

Modeling brain connectivity dynamics in functional Magnetic Resonance Imaging via Particle Filtering

Interest in the studying of functional connections in the brain has grown considerably in the last decades, as many studies have pointed out that alterations in the interaction among brain areas can play a role as markers of neurological diseases. Most studies in this field treat the brain network as a system of connections stationary in time, but dynamic features of brain connectivity can provide useful information, both on physiology and pathological conditions of the brain. In this paper, we propose the application of a computational methodology, named Particle Filter (PF), to study non-stationarities in brain connectivity in functional Magnetic Resonance Imaging (fMRI). The PF algorithm estimates time-varying hidden parameters of a first-order linear time-varying Vector Autoregressive model (VAR) through a Sequential Monte Carlo strategy. On simulated time series, the PF approach effectively detected and enabled to follow time-varying hidden parameters and it captured causal relationships among signals. The method was also applied to real fMRI data, acquired in presence of periodic tactile or visual stimulations, in different sessions. On these data, the PF estimates were consistent with current knowledge on brain functioning. Most importantly, the approach enabled to detect statistically significant modulations in the cause-effect relationship between brain areas, which correlated with the underlying visual stimulation pattern presented during the acquisition

Respostas a tecnologias de trigo nos anos de 1981 e 1982.

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Multiphase modelling of tumour growth and extracellular matrix interaction: mathematical tools and applications

Resorting to a multiphase modelling framework, tumours are described here as a mixture of tumour and host cells within a porous structure constituted by a remodelling extracellular matrix (ECM), which is wet by a physiological extracellular fluid. The model presented in this article focuses mainly on the description of mechanical interactions of the growing tumour with the host tissue, their influence on tumour growth, and the attachment/detachment mechanisms between cells and ECM. Starting from some recent experimental evidences, we propose to describe the interaction forces involving the extracellular matrix via some concepts coming from viscoplasticity. We then apply the model to the description of the growth of tumour cords and the formation of fibrosis

SiPM and front-end electronics development for Cherenkov light detection

The Italian Institute of Nuclear Physics (INFN) is involved in the development of a demonstrator for a SiPM-based camera for the Cherenkov Telescope Array (CTA) experiment, with a pixel size of 6$\times$6 mm$^2$. The camera houses about two thousands electronics channels and is both light and compact. In this framework, a R&D program for the development of SiPMs suitable for Cherenkov light detection (so called NUV SiPMs) is ongoing. Different photosensors have been produced at Fondazione Bruno Kessler (FBK), with different micro-cell dimensions and fill factors, in different geometrical arrangements. At the same time, INFN is developing front-end electronics based on the waveform sampling technique optimized for the new NUV SiPM. Measurements on 1$\times$1 mm$^2$, 3$\times$3 mm$^2$, and 6$\times$6 mm$^2$ NUV SiPMs coupled to the front-end electronics are presentedComment: In Proceedings of the 34th International Cosmic Ray Conference (ICRC2015), The Hague, The Netherlands. All CTA contributions at arXiv:1508.0589

Percolation, Morphogenesis, and Burgers Dynamics in Blood Vessels Formation

Experiments of in vitro formation of blood vessels show that cells randomly spread on a gel matrix autonomously organize to form a connected vascular network. We propose a simple model which reproduces many features of the biological system. We show that both the model and the real system exhibit a fractal behavior at small scales, due to the process of migration and dynamical aggregation, followed at large scale by a random percolation behavior due to the coalescence of aggregates. The results are in good agreement with the analysis performed on the experimental data.Comment: 4 pages, 11 eps figure

Polynuclear Complexes: Two Amino-Phenol Macrocycles Spaced by Several Linear Polyamines; Synthesis, Binding Properties, and Crystal Structure

The synthesis and characterization of the new polytopic ligands 1,14-bis(3,6,9-triaza-15-hydroxybicyclo[9.3.1]pentadeca-11,13,115-trien-6-yl)-3,6,9,12-tetraazatetradecane L1, 1,15-bis(3,6,9-triaza-15-hydroxybicyclo[9.3.1]pentadeca-11,13,115-trien-6-yl)-3,6,10,13-tetraazapentadecane L2, and 1,16-bis(3,6,9-triaza-15-hydroxybicyclo[9.3.1]pentadeca-11,13,115-trien-6-yl)-3,7,10,14-tetraazahexadecane L3, containing two equal amino-phenol macrocycles spaced by several linear tetraamines, are reported. The basicity and coordination behavior toward the Cu(II) ion were potentiometrically determined in aqueous solution at 298.1 K. All the ligands show similar acid-base properties behaving as octaprotic bases in the examined pH range (pH = 2-12). The acid protons of L1-L3 cannot be removed under the experimental conditions used; thus, the main deprotonated species obtainable in aqueous solution are the neutral ligands, having amphionic character as demonstrated by UV-vis experiments. These species are able to form mono-, di-, and trinuclear Cu(II) complexes having stoichiometry [CuL]2+, [Cu2L]4+, and [Cu3L]6+, respectively, that can lose one or two protons giving rise to [CuH-1L]+, [Cu2H-2L]2+, and [Cu3H-2L]4+. Depending on the used ligand to metal molar ratio, the mono-, di-, or trinuclear species prevail over the others in solution. Both di- and trinuclear complexes are able to add secondary ligands (such as OH-), and in some cases two Cu(II) can cooperate to stabilize themby coordinating the guest in a bridged conformation. The structure of the [Cu2L3]4+ cation was resolved by X-ray analysis of the {[Cu2L3](ClO4)4 3 3H2O}2 3 H2O crystalline complex. It shows that each Cu(II) is penta-coordinated by one phenolate oxygen, two amine functions, belonging to one macrocyclic unit, and two amine functions of the spacer; in this species the distance between the two Cu(II) is about 5.3 Å

Inactive Residents Living in Nursing Homes and Associated Predictors: Findings From a Regional-Based, Italian Retrospective Study.

Objectives: It has been amply reported that nursing home (NH) residents are largely inactive, a condition that may further increase functional decline, behavioral disorders, and risk of death. To date, studies have mainly focused on individual characteristics that may decrease residents' involvement in activities. Therefore, the aim of this study is to describe the prevalence of inactive NH residents in an Italian context, identifying predictors of inactivity at the individual and NH levels. Design: Retrospective regional-based study performed in 2014. Setting: All NHs (n = 105) located in the Friuli Venezia Giulia Region, northeastern region of Italy. Participants: A total of 8875 residents with at least 1 nursing assessment and living in an NH for at least 1 year. Measurements: The dependent variable was inactivity in the last week, defined as the resident not being involved in any socially or individually based, or meaningful recreational (eg, gardening) activities. The independent variables were set at individual and NH levels. Aiming at identifying predictors of inactivity, a hierarchical generalized linear (mixed-effects) model incorporating both fixed-effect parameters and random effects, was performed. Results: A total of 4042 (45.6%) residents were inactive during the week before the evaluation. At the resident level, those with severe cognitive impairment [odds (OR) 4.462, 95% confidence interval (CI) 3.880-5.132], unsociable behavior (OR 2.961, 95% CI 2.522-3.473), night restlessness (OR 1.605, 95% CI 1.395-1.853), lack of cooperation in daily care (OR 1.408, 95% CI 1.199-1.643), pressure sores (OR 1.314, 95% CI 1.065-1.622), depressive disorders (OR 1.242, 95% CI 1.089-1.416), and clinical instability (OR 1.110, 95% CI 1.037-1.188) reported an increased risk of being inactive. At the NH level, for each additional hour of care offered by professional educators, there was 1% less likelihood of inactive residents (OR .964, 95% .933-.996). Conclusions: Approximately one-half of the residents in this study living in Italian NHs are inactive. Inactivity is significantly associated with the presence of severe cognitive impairment, behavioral disorders (eg, unsociability, night restlessness, and lack of cooperation in daily care), pressure sores, depressive symptoms, and clinical instability. Moreover, receiving care from professional educators whose aim in their training program and professional mission is to improve individual and social engagement, decreased the likelihood of resident inactivity. \ua9 2016 AMDA - The Society for Post-Acute and Long-Term Care Medicine