Increasing food familiarity without the tears. A role for visual exposure?

Research has established the success of taste exposure paradigms as a means of increasing children’s acceptance, and liking, of previously unfamiliar or disliked foods. Yet, parents report that they tend to avoid the stress associated with repeatedly offering their children foods that are likely to be rejected. Given that successful taste exposure programmes often enhance children’s familiarity with a food’s appearance, as well as its taste, this article reviews the potential for exposure interventions that do not require repeated tastings to bring about positive attitude changes towards healthy foods. Recent evidence from studies that expose toddlers to picture books about fruit and vegetables suggest that familiarity with the origins and appearance of unfamiliar foods might increase children’s willingness to accept these into their diets.

General care of the older cancer patient.

With increasing age, there are greater numbers of older people who will be diagnosed with cancer. It must be remembered that such individuals have increased frailty and have a number of geriatric syndromes and conditions particularly pertinent to older age, including incontinence, poor cognition and impaired nutrition. It is often difficult to define the effects of cancer and its treatment or complications, and separate these from the effects of normal ageing and geriatric syndromes. The documentation of poor nutrition and its management must combine knowledge from both geriatric medicine and oncology. Nutrition serves to identify key healthcare professionals who are all essential in any patient at risk or suffering from malnutrition. Incontinence must be actively sought, its cause identified and efforts made to either 'cure' it or, in certain circumstances, 'manage' it. Older patients with cancer are cared for predominantly by older relations and informal care mechanisms and special consideration of their physical and practical needs are paramount. In this area, nurses, doctors, therapists and social workers should work to identify formal and informal mechanisms to support particularly the older carer.

Towards a life-event oriented G2C e-service provision: the NoBLE Framework

One of the primary features of modern government-to-citizen (G2C) service provision is the ability to offer a citizen-centric view of the e-government portal. Life-event approach is one of the most widely adopted paradigms supporting the idea of solving a complex event in a citizen’s life through a single service provision. Several studies have used this approach to design e-government portals. However, they were limited in terms of use and scalability. There were no mechanisms that show how to specify a life-event for structuring public e-services, or how to systematically match life-events with these services taking into consideration the citizen needs. We introduce the NOrm-Based Life-Event (NoBLE) framework for G2C e-service provision with a set of mechanisms as a guide for designing active life-event oriented e-government portals.

The status and challenge of global fire modelling

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, either using well-founded empirical relationships or process-based models with good predictive skill. A large variety of models exist today and it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project - FireMIP, an international project to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we summarise the current state-of-the-art in fire regime modelling and model evaluation, and outline what essons may be learned from FireMIP.

PETS2009: dataset and challenge

This paper describes the crowd image analysis challenge that forms part of the PETS 2009 workshop. The aim of this challenge is to use new or existing systems for i) crowd count and density estimation, ii) tracking of individual(s) within a crowd, and iii) detection of separate flows and specific crowd events, in a real-world environment. The dataset scenarios were filmed from multiple cameras and involve multiple actors.

PETS 2015: datasets and challenge

This paper presents the two datasets (ARENA and P5) and the challenge that form a part of the PETS 2015 workshop. The datasets consist of scenarios recorded by us- ing multiple visual and thermal sensors. The scenarios in ARENA dataset involve different staged activities around a parked vehicle in a parking lot in UK and those in P5 dataset involve different staged activities around the perimeter of a nuclear power plant in Sweden. The scenarios of each dataset are grouped into ‘Normal’, ‘Warning’ and ‘Alarm’ categories. The Challenge specifically includes tasks that account for different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘atomic’ event detection) and High-Level Video Analysis (‘complex’ event detection). The evaluation methodology used for the Challenge includes well-established measures.

PETS 2014: dataset and challenge

This paper describes the dataset and vision challenges that form part of the PETS 2014 workshop. The datasets are multisensor sequences containing different activities around a parked vehicle in a parking lot. The dataset scenarios were filmed from multiple cameras mounted on the vehicle itself and involve multiple actors. In PETS2014 workshop, 22 acted scenarios are provided of abnormal behaviour around the parked vehicle. The aim in PETS 2014 is to provide a standard benchmark that indicates how detection, tracking, abnormality and behaviour analysis systems perform against a common database. The dataset specifically addresses several vision challenges corresponding to different steps in a video understanding system: Low-Level Video Analysis (object detection and tracking), Mid-Level Video Analysis (‘simple’ event detection: the behaviour recognition of a single actor) and High-Level Video Analysis (‘complex’ event detection: the behaviour and interaction recognition of several actors).