Statistical analysis of the trigger algorithm for the NEMO project

We discuss the performances of a trigger implemented for the planned neutrino telescope NEMO. This trigger seems capable to discriminate between the signal and the strong background introduced by atmospheric muons and by the beta decay of the K-40 nuclei present in the water. The performances of the trigger, as evaluated on simulated data are analyzed in detail.Comment: Published in the Proceedings of the "I Workshop of Astronomy and Astrophysics for Students", Eds. N.R. Napolitano & M. Paolillo, Naples, 19-20 April 2006 (astro-ph/0701577

Star Formation Rates for photometric samples of galaxies using machine learning methods

Star Formation Rates or SFRs are crucial to constrain theories of galaxy formation and evolution. SFRs are usually estimated via spectroscopic observations requiring large amounts of telescope time. We explore an alternative approach based on the photometric estimation of global SFRs for large samples of galaxies, by using methods such as automatic parameter space optimisation, and supervised Machine Learning models. We demonstrate that, with such approach, accurate multi-band photometry allows to estimate reliable SFRs. We also investigate how the use of photometric rather than spectroscopic redshifts, affects the accuracy of derived global SFRs. Finally, we provide a publicly available catalogue of SFRs for more than 27 million galaxies extracted from the Sloan Digital Sky survey Data Release 7. The catalogue is available through the Vizier facility at the following link ftp://cdsarc.u-strasbg.fr/pub/cats/J/MNRAS/486/1377

Single pulse avalanche robustness and repetitive stress ageing of SiC power MOSFETs

This paper presents an extensive electro-thermal characterisation of latest generation silicon carbide (SiC) Power MOSFETs under unclamped inductive switching (UIS) conditions. Tests are carried out to thoroughly understand the single pulse avalanche ruggedness limits of commercial SiC MOSFETs and assess their aging under repetitive stress conditions. Both a functional and a structural characterisation of the transistors is presented, with the aim of informing future device technology development for robust and reliable power system development

Identifying Medication Management Smartphone App Features Suitable for Young Adults With Developmental Disabilities: Delphi Consensus Study

Background: Smartphone apps can be a tool to facilitate independent medication management among persons with developmental disabilities. At present, multiple medication management apps exist in the market, but only 1 has been specifically designed for persons with developmental disabilities. Before initiating further app development targeting this population, input from stakeholders including persons with developmental disabilities, caregivers, and professionals regarding the most preferred features should be obtained. Objective: The aim of this study was to identify medication management app features that are suitable to promote independence in the medication management process by young adults with developmental disabilities using a Delphi consensus method. Methods: A compilation of medication management app features was performed by searching the iTunes App Store, United States, in February 2016, using the following terms: adherence, medication, medication management, medication list, and medication reminder. After identifying features within the retrieved apps, a final list of 42 features grouped into 4 modules (medication list, medication reminder, medication administration record, and additional features) was included in a questionnaire for expert consensus rating. A total of 52 experts in developmental disabilities, including persons with developmental disabilities, caregivers, and professionals, were invited to participate in a 3-round Delphi technique. The purpose was to obtain consensus on features that are preferred and suitable to promote independence in the medication management process among persons with developmental disabilities. Consensus for the first, second, and third rounds was defined as ≥90%, ≥80%, and ≥75% agreement, respectively. Results: A total of 75 responses were received over the 3 Delphi rounds—30 in the first round, 24 in the second round, and 21 in the third round. At the end of the third round, cumulative consensus was achieved for 60% (12/20) items in the medication list module, 100% (3/3) in the medication reminder module, 67% (2/3) in the medication administration record module, and 63% (10/16) in the additional features module. In addition to the medication list, medication reminder, and medication administration record features, experts selected the following top 3 most important additional features: automatic refills through pharmacies; ability to share medication information from the app with providers; and ability to share medication information from the app with family, friends, and caregivers. The top 3 least important features included a link to an official drug information source, privacy settings and password protection, and prescription refill reminders. Conclusions: Although several mobile apps for medication management exist, few are specifically designed to support persons with developmental disabilities in the complex medication management process. Of the 42 different features assessed, 64% (27/42) achieved consensus for inclusion in a future medication management app. This study provides information on the features of a medication management app that are most important to persons with developmental disabilities, caregivers, and professionals

Towards a Powerful Hardware‐in‐the‐Loop System for Virtual Calibration of an Off‐Road Diesel Engine

A common challenge among internal combustion engine (ICE) manufacturers is shorten-ing the development time while facing requirements and specifications that are becoming more complex and border in scope. Virtual simulation and calibration are effective instruments in the face of these demands. This article presents the development of zero‐dimensional (0D)—real‐time engine and exhaust after‐treatment system (EAS) models and their deployment on a Virtual test bench (VTB). The models are created using a series of measurements acquired in a real test bench, carefully performed in view of ensuring the highest reliability of the models themselves. A zero‐dimensional approach was chosen to guarantee that models could be run in real‐time and interfaced to the real engine Electronic Control Unit (ECU). Being physically based models, they react to changes in the ECU calibration parameters. Once the models are validated, they are then integrated into a Sim-ulink® based architecture with all the Inputs/Outputs connections to the ECU. This Simulink® model is then deployed on a Hardware in the Loop (HiL) machine for ECU testing and calibration. The results for engine and EAS performance and emissions align with both steady‐state and transient measurements. Finally, two different applications of the HiL system are presented to explain the opportunities and advantages of this tool integrated within the standard engine development. Ex-amples cited refer to altitude calibration activities and soot loading investigation on vehicle duty cycles. The cases described in this work are part of the actual development of one of the latest engines developed by Kohler Engines: the KDI 1903 TCR Stage V. The application of this methodology reveals a great potential for engine development and may become an essential tool for calibration engineers

Sull’utilizzo dell’energia cinetica per produzione additiva: primi risultati di prove di fatica e confronto con lavorazioni SLM

Il cold spray (CS) è una tecnica di rivestimento a freddo in cui la deposizione delle polveri avviene grazie all’impatto ad alta velocità delle particelle contro un substrato e alla conseguente elevata deformazione plastica, con l’instaurarsi delle condizioni di instabilità adiabatica di taglio. Nel presente lavoro sono stati considerati provini in In718 prodotti con CS e con SLM, sottoposti a diversi trattamenti termici, a valle della lavorazione dei provini. La caratterizzazione dei provini ha compreso l’analisi microstrutturale, la misura degli sforzi residui e della la porosità, mentre le prove meccaniche hanno previsto prove di trazione statiche e di fatica assiale. I risultati mostrano caratteristiche e resistenza comparabili a quelle dei provini SLM, suggerendo che il CS, grazie alla minore temperatura del processo e al ridotto impegno energetico, possa divenire una tecnologia additiva alternativa o complementare rispetto alle più consolidate tecnologie laser

FARO: FAce Recognition against Occlusions and Expression Variations

FARO: FAce Recognition Against Occlusions and Expression Variations Maria De Marsico, Member, IEEE, Michele Nappi, and Daniel Riccio Abstract—Face recognition is widely considered as one of the most promising biometric techniques, allowing high recognition rates without being too intrusive. Many approaches have been presented to solve this special pattern recognition problem, also addressing the challenging cases of face changes, mainly occurring in expression, illumination, or pose. On the other hand, less work can be found in literature that deals with partial occlusions (i.e., sunglasses and scarves). This paper presents FAce Recognition against Occlusions and Expression Variations (FARO) as a new method based on partitioned iterated function systems (PIFSs), which is quite robust with respect to expression changes and partial occlusions. In general, algorithms based on PIFSs compute a map of self-similarities inside the whole input image, searching for correspondences among small square regions. However, traditional algorithms of this kind suffer from local distortions such as occlusions. To overcome such limitation, information extracted by PIFS is made local by working independently on each face component (eyes, nose, and mouth). Distortions introduced by likely occlusions or expression changes are further reduced by means of an ad hoc distance measure. In order to experimentally confirm the robustness of the proposed method to both lighting and expression variations, as well as to occlusions, FARO has been tested using AR-Faces database, one of the main benchmarks for the scientific community in this context. A further validation of FARO performances is provided by the experimental results produced on Face Recognition Grand Challenge database

Massive megarectum secondary to constipation in institutionalized patient

Chronic constipation is a common cause of morbidity in the elderly and institutionalized population. It can be associated with significant morbidity and socioeconomical burden. Chronic resistance constipation can rarely be associated with megarectum. Herein, we present the case of a patient with physical and mental disability that presented with refractory constipation associated with extreme stool burden and a massive megarectum. We discuss chronic constipation in the elderly population, its etiologies and diagnostic work-up including surgical options. The management of chronic constipation with megarectum should be on a case-by-case basis

CABALA: Collaborative Architectures based on Biometric Adaptable Layers and Activities

The lack of communication and of dynamic adaptation to working settings often hinder stable performances of subsystems of present multibiometric architectures. The calibration phase often uses a specific training set, so that (sub)systems are tuned with respect to well determined conditions. In this work we investigate the modular construction of systems according to CABALA (Collaborative Architectures based on Biometric Adaptable Layers and Activities) approach. Different levels of flexibility and collaboration are supported. The computation of system reliability (SRR), for each single response of each single subsystem, allows to address temporary decrease of accuracy due to adverse conditions (light, dirty sensors, etc.), by possibly refusing a poorly reliable response or by asking for a new recognition operation. Subsystems can collaborate at a twofold level, both in returning a jointly determined answer, and in co-evolving to tune to changing conditions. At the first level, single-biometric subsystems implement the N-Cross Testing Protocol: they work in parallel, but exchange information to reach the final response. At an higher level of interdependency, parameters of each subsystem can be dynamically optimized according to the behavior of their companions. To this aim, an additional Supervisor Module analyzes the single results and, in our present implementation, modifies the degree of reliability required from each subsystem to accept its future responses. The paper explores different combinations of these novel strategies. We demonstrate that as component collaboration increases, the same happens to both the overall system accuracy and to the ability to identify unstable subsystems. (C) 2011 Elsevier Ltd. All rights reserved