Epidemic forecasting based on mobility patterns: an approach and experimental evaluation on COVID-19 Data.

During an epidemic, decision-makers in public health need accurate predictions of the future case numbers, in order to control the spread of new cases and allow efficient resource planning for hospital needs and capacities. In particular, considering that infectious diseases are spread through human-human transmissions, the analysis of spatio-temporal mobility data can play a fundamental role to enable epidemic forecasting. This paper presents the design and implementation of a predictive approach, based on spatial analysis and regressive models, to discover spatio-temporal predictive epidemic patterns from mobility and infection data. The experimental evaluation, performed on mobility and COVID-19 data collected in the city of Chicago, is aimed to assess the effectiveness of the approach in a real-world scenario.

Smart Monitoring and Control in the Future Internet of Things.

The Internet of Things (IoT) and related technologies are promising in terms of realizing pervasive and smart applications, which, in turn, have the potential to improve the quality of life of people living in a connected world [...].

Olive mill wastewaters: quantitation of the phenolic content and profiling of elenolic acid derivatives using HPLC-DAD and HPLC/MS2 with an embedded polar group stationary phase.

Olive mill wastewaters (OMWs) are important by-products of olive oil production. The wide availability and the forbidding economic costs of OMWs disposal have generated interest in their possible exploitation as a sustainable source of polyphenols. The development and optimisation of improved analytical methods for the detailed characterisation of polyphenol molecular profiles after production and during storage conditions are thus required. A new analytical method based on reverse-phase HPLC separation of polyphenols in OMWs on an embedded-polar group (EPG) stationary phase is proposed as an alternative to conventional C18 columns. The procedure was used for the quantitation of 11 polyphenols, using diode-array detection (DAD), and achieving quantitation limits equal to or lower than 0.1 µg g-1. The same chromatographic set-up, coupled with high resolution tandem mass spectrometry (HPLC/ESI-Q-ToF), allowed us to identify hydroxytyrosyl esters of elenolic acid, whose relative abundance is proposed for monitoring the ageing of OMWs during storage.

On the Design of Smart Homes: A Framework for Activity Recognition in Home Environment.

A smart home is a home environment enriched with sensing, actuation, communication and computation capabilities which permits to adapt it to inhabitants preferences and requirements. Establishing a proper strategy of actuation on the home environment can require complex computational tasks on the sensed data. This is the case of activity recognition, which consists in retrieving high-level knowledge about what occurs in the home environment and about the behaviour of the inhabitants. The inherent complexity of this application domain asks for tools able to properly support the design and implementation phases. This paper proposes a framework for the design and implementation of smart home applications focused on activity recognition in home environments. The framework mainly relies on the Cloud-assisted Agent-based Smart home Environment (CASE) architecture offering basic abstraction entities which easily allow to design and implement Smart Home applications. CASE is a three layered architecture which exploits the distributed multi-agent paradigm and the cloud technology for offering analytics services. Details about how to implement activity recognition onto the CASE architecture are supplied focusing on the low-level technological issues as well as the algorithms and the methodologies useful for the activity recognition. The effectiveness of the framework is shown through a case study consisting of a daily activity recognition of a person in a home environment.

Decalcifying capability of irrigating solutions on root canal dentin mineral content.

BACKGROUND: Chelating agents are believed to aid root canal irrigation and to be able to remove the inorganic smear layer. AIMS: The purpose of the present study was to evaluate and to compare the decalcifying capability of different irrigating solutions (Tubuliclean, Largal Ultra, ethylenediaminetetraacetic acid 17%, Tetraclean, Tetraclean NA). MATERIALS AND METHODS: Sixty maxillary central incisors were used. Root canals were instrumented and irrigated. From each root, four comparable slices of cervical dentin were obtained. At three successive 5-min interval immersion times, the concentration of calcium extracted from root canal dentin was assessed with an inductively coupled plasma-atomic emission spectrometer. STATISTICAL ANALYSIS USED: Data were analyzed by means of Kruskal Wallis and Mann-Whitney tests. Significance was predetermined at P < 0.05. RESULTS AND CONCLUSIONS: For all irrigating solutions, the maximum amount of Ca(2+) extracted from root canal dentin samples was reached after 10 min contact time except for citric acid-based agents (Tetraclean and Tetraclean NA) which induced a higher and still increasing calcium release even after 10 min contact time. In order to obtain an efficient decalcifying action on dentin and to facilitate the biomechanical procedures, citric acid-based irrigants can be applied.