A Multi-Task Learning Approach for Meal Assessment

Key role in the prevention of diet-related chronic diseases plays the balanced nutrition together with a proper diet. The conventional dietary assessment methods are time-consuming, expensive and prone to errors. New technology-based methods that provide reliable and convenient dietary assessment, have emerged during the last decade. The advances in the field of computer vision permitted the use of meal image to assess the nutrient content usually through three steps: food segmentation, recognition and volume estimation. In this paper, we propose a use one RGB meal image as input to a multi-task learning based Convolutional Neural Network (CNN). The proposed approach achieved outstanding performance, while a comparison with state-of-the-art methods indicated that the proposed approach exhibits clear advantage in accuracy, along with a massive reduction of processing time

Excellence in English: what we can learn from 12 outstanding schools

"One of the most pressing issues in English facing a large number of schools today is how to improve from being good to outstanding. The aim of this report is to improve practice in English across all schools and particularly to help them become outstanding. The report provides 12 case studies of schools which are successful in helping their pupils to make outstanding progress in English." - Cover

Bridge College: inspection of FEFC-funded provision in non-sector establishments for students with learning difficulties and/or disabilities (Report from the Inspectorate, 1999-00)

Independent Establishment 17/00, Inspection of FEFC-Funded Provision in non-sector establishments for students with learning difficulties and/or disabilities. Bridge College, Offerton, Stockport, Inspected June 200

Artifact Rejection Methodology Enables Continuous, Noninvasive Measurement of Gastric Myoelectric Activity in Ambulatory Subjects.

The increasing prevalence of functional and motility gastrointestinal (GI) disorders is at odds with bottlenecks in their diagnosis, treatment, and follow-up. Lack of noninvasive approaches means that only specialized centers can perform objective assessment procedures. Abnormal GI muscular activity, which is coordinated by electrical slow-waves, may play a key role in symptoms. As such, the electrogastrogram (EGG), a noninvasive means to continuously monitor gastric electrical activity, can be used to inform diagnoses over broader populations. However, it is seldom used due to technical issues: inconsistent results from single-channel measurements and signal artifacts that make interpretation difficult and limit prolonged monitoring. Here, we overcome these limitations with a wearable multi-channel system and artifact removal signal processing methods. Our approach yields an increase of 0.56 in the mean correlation coefficient between EGG and the clinical "gold standard", gastric manometry, across 11 subjects (p < 0.001). We also demonstrate this system's usage for ambulatory monitoring, which reveals myoelectric dynamics in response to meals akin to gastric emptying patterns and circadian-related oscillations. Our approach is noninvasive, easy to administer, and has promise to widen the scope of populations with GI disorders for which clinicians can screen patients, diagnose disorders, and refine treatments objectively

Validation of a recommender system for prompting omitted foods in online dietary assessment surveys

Recall assistance methods are among the key aspects that improve the accuracy of online dietary assessment surveys. These methods still mainly rely on experience of trained interviewers with nutritional background, but data driven approaches could improve cost-efficiency and scalability of automated dietary assessment. We evaluated the effectiveness of a recommender algorithm developed for an online dietary assessment system called Intake24, that automates the multiple-pass 24-hour recall method. The recommender builds a model of eating behavior from recalls collected in past surveys. Based on foods they have already selected, the model is used to remind respondents of associated foods that they may have omitted to report. The performance of prompts generated by the model was compared to that of prompts hand-coded by nutritionists in two dietary studies. The results of our studies demonstrate that the recommender system is able to capture a higher number of foods omitted by respondents of online dietary surveys than prompts hand-coded by nutritionists. However, the considerably lower precision of generated prompts indicates an opportunity for further improvement of the system

innovative Public Organic food Procurement for Youth (iPOPY). Lessons learned from implementing organic into European school meals – policy implications.

The introduction of organic food offers new dimensions to school meals, and schools offer new dimensions to organic food – when tackled properly. In this paper we present findings from the iPOPY research project that is funded by the ERA-Net, CORE-Organic-I funding body network. It is based on studies of school food policies in Denmark, Finland, Italy and Norway. The embedded food traditions and cultures have had different attention in these countries, why also food related consumption, institutions and markets are quite heterogeneous and dynamic. Whereas school food services are relatively widely embedded in the school systems in Finland and Italy, the Danish and Norwegian school food is predominantly defined by the packed lunch brought from home when it comes to organic food the pattern is different. To analyse the strategies used in these countries we have selected a number of cases where in-depth studies have been conducted. The concept of embedding has been used in these studies and it has been informed by policy and actor network theories. The results of this analysis show a complexity in implementing organic food in existing school food aims, in embedding school food policies and in comprising also aims and policies for organic food purchasing in these. The variety amongst the analysed countries in strategies and success is identified, covering both structural and stakeholder related findings. A major finding is pointing at the challenge of “multi-embedding” processes when including organic food in school meal procurement

How to measure mood in nutrition research

© 2014 The Authors. Mood is widely assessed in nutrition research, usually with rating scales. A core assumption is that positive mood reinforces ingestion, so it is important to measure mood well. Four relevant theoretical issues are reviewed: (i) the distinction between protracted and transient mood; (ii) the distinction between mood and emotion; (iii) the phenomenology of mood as an unstable tint to consciousness rather than a distinct state of consciousness; (iv) moods can be caused by social and cognitive processes as well as physiological ones. Consequently, mood is difficult to measure and mood rating is easily influenced by non-nutritive aspects of feeding, the psychological, social and physical environment where feeding occurs, and the nature of the rating system employed. Some of the difficulties are illustrated by reviewing experiments looking at the impact of food on mood. The mood-rating systems in common use in nutrition research are then reviewed, the requirements of a better mood-rating system are described, and guidelines are provided for a considered choice of mood-rating system including that assessment should: have two main dimensions; be brief; balance simplicity and comprehensiveness; be easy to use repeatedly. Also mood should be assessed only under conditions where cognitive biases have been considered and controlled