Rejection Properties of Stochastic-Resonance-Based Detectors of Weak Harmonic Signals

In (V. Galdi et al., Phys. Rev. E57, 6470, 1998) a thorough characterization in terms of receiver operating characteristics (ROCs) of stochastic-resonance (SR) detectors of weak harmonic signals of known frequency in additive gaussian noise was given. It was shown that strobed sign-counting based strategies can be used to achieve a nice trade-off between performance and cost, by comparison with non-coherent correlators. Here we discuss the more realistic case where besides the sought signal (whose frequency is assumed known) further unwanted spectrally nearby signals with comparable amplitude are present. Rejection properties are discussed in terms of suitably defined false-alarm and false-dismissal probabilities for various values of interfering signal(s) strength and spectral separation.Comment: 4 pages, 5 figures. Misprints corrected. PACS numbers added. RevTeX

European Museums in the 21st Century: Setting the Framework (3 Voll.)

This book grew out of the earliest work of the MeLa Research Field 6, “Envisioning 21st Century Museums,” aimed at exploring current trends in European contemporary museums. Analysing their ongoing evolution triggered by this “age of migrations” and with specific attention to their architecture and exhibition design, the volume collects the preliminary observations ensuing from this survey, complemented by the some paradigmatic examples, and further enriched by interviews and contributions from scholars, curators and museum practitioners. With contributions by Florence Baläen, Michela Bassanelli, Luca Basso Peressut, Joachim Baur, Lorraine Bluche, Marco Borsotti, Mariella Brenna, Anna Chiara Cimoli, Lars De Jaegher, Maria Camilla De Palma, Hugues De Varine, Maria De Waele, Nélia Dias, Simone Eick, Fabienne Galangau Quérat, Sarah Gamaire, Jan Gerchow, Marc-Olivier Gonset, Klas Grinell, Laurence Isnard, Marie-Paule Jungblut, Galitt Kenan, Francesca Lanz, José María Lanzarote Guiral, Vito Lattanzi, Jack Lohman, Carolina Martinelli, Frauke Miera, Elena Montanari, Chantal Mouffe, Judith Pargamin, Giovanni Pinna, Camilla Pagani, Clelia Pozzi, Paolo Rosa, Anna Seiderer

The impact of diabetes in implant oral rehabilitations: A bibliometric study and literature review

Introduction: Diabetes represents a potential risk factor for bone healing and dental implant treatment predictability. The aim of the present investigation was to perform a bibliometric evaluation of articles on the topic of the impact of diabetes on implant oral rehabilitations. Material and methods: A Boolean keywords search was performed on Scopus database and recorded the list of articles, authors and affiliations. The journal impact factor was calculated by the Journal Citation Report Clarivate electronic database. The total papers, number of citations and journal impact factors were calculated. Results: a total of 476 papers and 162 authors were assessed. The mean authors total citations were 2880.11± 4070.24 and the mean impact factor value was 1.942±1.15 Conclusions: uncontrolled diabetes impacts on dental implant rehabilitation with an increased risk of implant failure and periimplant disease in long-term rehabilitation

In search of knowledge: text mining dedicated to technical translation

Articolo pubblicato su CD e commercializzato direttamente dall'ASLIB (http://shop.emeraldinsight.com/product_info.htm/cPath/56_59/products_id/431). Programma del convegno su http://aslib.co.uk/conferences/tc_2011/programme.htm

Global recession and higher education in eastern Asia: China, Mongolia and Vietnam

This paper presents a perspective on the capacity of colleges and universities during past and present economic shocks. The main argument is that the environment of the global recession-an Asia far more economically integrated than during past economic shocks, with more unified aspirations to be globally competitive and socially responsible-no longer delay reforms in higher education. In fact, the global recession has become an opportune time for higher education in Asia, specifically developing countries in eastern (East and Southeast) Asia, to continue reforming governance and administration, access and equity, internal and external efficiency, and regional collaboration. Economic shocks have accelerated reforms in higher education, especially those for promoting innovation in their economies, though more is needed in improving governance and access for underserved populations. This paper examines the cases of China, Mongolia, and Vietnam as examples of how the global recession and regional integration are growing forces in shaping their higher education reform and development. The paper also identifies a series of measures for increasing the resilience of higher education systems in serving poor and vulnerable populations during economic recessions. Responses to the global economic recession by nations in eastern Asia are likely to improve the global shift in economy and human capital. © 2011 The Author(s).published_or_final_versionSpringer Open Choice, 21 Feb 201

A Nearly Minimum Redundant Correlator Interpolation Formula for Gravitational Wave Chirp Detection

An absolute lower bound on the number of templates needed to keep the fitting factor above a prescribed minimal value $\Gamma$ in correlator bank detection of (newtonian) gravitational wave chirps from unknown inspiraling compact binary sources is derived, resorting to the theory of quasi-bandlimited functions in the $L^\infty$ norm. An explicit nearly-minimum redundant cardinal-interpolation formula for the (reduced, noncoherent) correlator is introduced. Its computational burden and statistical properties are compared to those of the plain lattice of (reduced, noncoherent) correlators, for the same $\Gamma$. Extension to post-newtonian models is outlined

Neural networks for fatigue crack propagation predictions in real-time under uncertainty

Crack propagation analyses are fundamental for all mechanical structures for which safety must be guaranteed, e. g. as for the aviation and aerospace fields. The estimation of life for structures in presence of defects is a process inevitably affected by numerous and unavoidable uncertainty and variability sources, whose effects need to be quantified to avoid unexpected failures or excessive conservativism. In this work, residual fatigue life prediction models have been created through neural networks for the purpose of performing probabilistic life predictions of damaged structures in real-time and under stochastically varying input parameters. In detail, five different neural network architectures have been compared in terms of accuracy, computational runtimes and minimum number of samples needed for training, so to determine the ideal architecture with the strongest generalization power. The networks have been trained, validated and tested by using the fatigue life predictions computed by means of simulations developed with FEM and Monte Carlo methods. A real-world case study has been presented to show how the proposed approach can deliver accurate life predictions even when input data are uncertain and highly variable. Results demonstrated that the “H1-L1” neural network has been the best model, achieving an accuracy (Mean Square Error) of 4.8e-7 on the test dataset, and the best and the most stable results when decreasing the amount of data. Additionally, since requiring only very few parameters, its potential applicability for Structural Health Monitoring purposes in small cost-effective GPU devices resulted to be attractive

On the use of neural networks and statistical tools for nonlinear modeling and on-field diagnosis of solid oxide fuel cell stacks

Abstract The paper reports on the activities performed within the European funded project GENIUS to develop black-box models for modeling and diagnosis of solid oxide fuel cell (SOFC) stacks. Two modeling techniques were investigated, i.e. Neural Networks (NNs) and Statistical Tools (STs). The deployment of NNs was twofold: Recurrent Neural Networks (RNNs) and an NN classifier were developed to simulate transient operation of SOFCs and identify some specific faults that may occur in such devices, respectively. On the other hand, STs are based on a stepwise multiple regression. Data for model development were obtained from experiments specifically designed to reach maximal information content. The final aim was to obtain highly general models of SOFC stacks' operation in both transient and steady state. All the developed black-box models exhibited high accuracy and reliability on both training and test data-sets. Moreover, the black-box models were also proven effective in performing real-time monitoring and degradation analysis for different SOFC stack technologies

Are nutrition and physical activity associated with gut microbiota? A pilot study on a sample of healthy young adults

BACKGROUND: The literature shows that gut microbiota composition is related with health, and a lot of individual and outer factors may determine its variability. In particular, nutrition and exercise seem to influence the presence in the gut of the two major bacterial phyla of Firmicutes and Bacteroidetes. STUDY DESIGN: An ongoing cross-sectional investigation is aimed to explore these associations in humans. METHODS: Healthy Caucasian young adults were asked to provide a fecal sample in order to analyze their gut microbiome considering their Body Mass Index (BMI), adherence to Mediterranean diet and Physical Activity (PA) level. RESULTS: A total of 59 participants (49.1% males, mean age 23.1 ± 3.14 years) were enrolled so far. Firmicutes (61.6±14.6) and Bacteroidetes (30.7 ± 13.3) showed the highest relative abundance in fecal samples. The Pearson's analysis showed a significant negative correlation between PA and Firmicutes (r =-0.270, p = 0.03). Linear regression confirmed a significant decrease of this phylum with the increase of PA (R2 = 0.07, p = 0.03). CONCLUSIONS: These preliminary results suggest the association between physical activity and gut microbiota composition in healthy humans

Impact of COVID-19 pandemic lockdown on narcolepsy type 1 management

Study Objectives: Narcolepsy type 1 (NT1) is a chronic rare hypersomnia of central origin requiring a combination of behavioral and pharmacological treatments. During the coronavirus disease 2019 (COVID-19) pandemic, in Italy the population was forced into a lockdown. With this study, we aimed to describe the lockdown impact on NT1 symptom management, according to different patients' working schedule. Methods: In the period between 10 April and 15 May 2020, we performed routine follow-up visits by telephone (as recommended during the COVID-19 emergency) to 50 patients >18 years old (40% males) under stable long-term treatment. We divided patients into three groups: unchanged working schedule, forced working/studying at home, and those who lost their job (“lost occupation”). Current sleep–wake habit and symptom severity were compared with prelockdown assessment (six months before) in the three patient groups. Results: At assessment, 20, 22, and eight patients belonged to the unchanged, working/studying at home, and lost occupation groups, respectively. While in the lost occupation group, there were no significant differences compared with prepandemic assessment, the patients with unchanged schedules reported more nocturnal awakenings, and NT1 patients working/studying at home showed an extension of nocturnal sleep time, more frequent daytime napping, improvement of daytime sleepiness, and a significant increase in their body mass index. Sleep-related paralysis/hallucinations, automatic behaviors, cataplexy, and disturbed nocturnal sleep did not differ. Conclusions: Narcolepsy type 1 patients working/studying at home intensified behavioral interventions (increased nocturnal sleep time and daytime napping) and ameliorated daytime sleepiness despite presenting with a slight, but significant, increase of weight