One of the aims of the EPIC study is to produce accurate descriptions of the dietary habits of the participants recruited in the 27 EPIC centers of 10 European countries. To do this, different dietary assessment instruments were developed and applied to capture the wide range of diets characterizing the different European populations. Three different food frequency questionnaires were developed for Italy: one for the centers of Varese, Turin and Florence, one for Ragusa and one for Naples. These inquired about eating habits over the previous year and were completed by 46,839 Italian EPIC participants. Specially developed software analyzed the responses and linked them to food composition tables in order to provide a nutritional breakdown of individual and collective diets. A further aim of EPIC was to develop a method of rendering data from different dietary questionnaires comparable. To do this, dietary data were collected from a sample of about 8% of the Italian EPIC cohort, using a standardized computer-driven 24-hour dietary recall interview, and then compared with the dietary data collected by the questionnaires. This paper provides an extensive description of the technical features and performance of the food frequency questionnaires and the 24-hour recall interview, including a comparison of estimates of the intake of different food groups provided by the two instruments. From this comparison, the repeatability and reliability of consumption estimates was assessed, resulting in indications for improving data comparability. The paper also presents food frequency questionnaire estimates of the daily intake of foods and nutrients by center, sex and age group, as well as information on dietary habits such as place and time of intake, and food preparation and preservation methods as provided by the 24-hour recall interview. The picture that emerged is that Italian eating habits are undergoing marked changes, with a tendency to less healthy eating. Documentation of these changes in relation to age, sex and region provides an essential starting point for investigating the influence of diet on the development of cancer and other chronic diseases.

EPIC-Italy is the Italian section of a larger project known as EPIC (European Prospective Investigation into Cancer and Nutrition), a prospective study on diet and cancer carried out in 10 European countries. In the period 1993-1998, EPIC-Italy completed the recruitment of 47,749 volunteers (15,171 men, 32,578 women, aged 35-65 years) in 4 different areas covered by cancer registries: Varese (12,083 volunteers) and Turin (10,604) in the Northern part of the country; Florence (13,597) and Ragusa (6,403) in Central and Southern Italy, respectively. An associate center in Naples enrolled 5,062 women. Detailed information for each individual volunteer about diet and life-style habits, anthropometric measurements and a blood sample was collected, after signing an informed consent form. A food frequency questionnaire specifically developed for the Italian dietary pattern was tested in a pilot phase. A computerized data base with the dietary and life-style information of each participant was completed. Blood samples were processed in the same day of collection, aliquoted (RBC, WBC, serum and plasma) and stored in liquid nitrogen containers. Follow-up procedures were validated and implemented for the identification of newly diagnosed cancer cases. Cancer incidence was related to dietary habits and biochemical markers of food consumption and individual susceptibility in order to test the role of diet-related exposure in the etiology of cancer and its interaction with other environmental or genetic determinants. The comparability of information in a prospective study design is much higher than in other studies. The availability of such a large biological bank linked to individual data on dietary and life-style exposures also provides the unique opportunity of evaluating the role of selected genotypes involved in the metabolism of chemical compounds and DNA repair, potentially related to the risk of cancer, in residents of geographic areas of Italy characterized by specific cancer risk and different dietary patterns. Baseline characteristics of participants are briefly described.

Robots of today are eager to leave constrained industrial environments and embrace unexplored and unstructured areas, for extensive applications in the real world as service and social robots. Hence, in addition to these new physical frontiers, they must face human ones, too. This implies the need to consider a human-robot interaction from the beginning of the design; the possibility for a robot to recognize users' emotions and, in a certain way, to properly react and "behave". This could play a fundamental role in their integration in society. However, this capability is still far from being achieved. Over the past decade, several attempts to implement automata for different applications, outside of the industry, have been pursued. But very few applications have tried to consider the emotional state of users in the behavioural model of the robot, since it raises questions such as: how should human emotions be modelled for a correct representation of their state of mind? Which sensing modalities and which classification methods could be the most feasible to obtain this desired knowledge? Furthermore, which applications are the most suitable for the robot to have such sensitivity? In this context, this paper aims to provide a general overview of recent attempts to enable robots to recognize human emotions and interact properly.

A brief educational intervention by GPs can induce multiple diet changes that may lower BMI and potentially reduce chronic disease risk in generally healthy adults.

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems.