Reproducibility of a short semi-quantitative food group questionnaire and its performance in estimating nutrient intake compared with a 7-day diet diary in the Million Women Study

Objectives: To assess the short- and long-term reproducibility of a short food group questionnaire, and to compare its performance for estimating nutrient intakes in comparison with a 7-day diet diary. Design: Participants for the reproducibility study completed the food group questionnaire at two time points, up to 2 years apart. Participants for the performance study completed both the food group questionnaire and a 7-day diet diary a few months apart. Reproducibility was assessed by kappa statistics and percentage change between the two questionnaires; performance was assessed by kappa statistics, rank correlations and percentages of participants classified into the same and opposite thirds of intake. Setting: A random sample of participants in the Million Women Study, a population-based prospective study in the UK. Subjects: In total, 12 221 women aged 50-64 years. Results: in the reproducibility study, 75% of the food group items showed at least moderate agreement for all four time-point comparisons. Items showing fair agreement or worse tended to be those where few respondents reported eating them more than once a week, those consumed in small amounts and those relating to types of fat consumed. Compared with the diet diary, the food group questionnaire showed consistently reasonable performance for the nutrients carbohydrate, saturated fat, cholesterol, total sugars, alcohol, fibre, calcium, riboflavin, folate and vitamin C. Conclusions: The short food group questionnaire used in this study has been shown to be reproducible over time and to perform reasonably well for the assessment of a number of dietary nutrients.

The influence of the supply chain agents on the new product development's performance: an analysis based on the multi-group moderation

Este estudo buscou verificar a influencia dos agentes da cadeia de suprimentos no desempenho do desenvolvimento de novos produtos quando os agentes são analisados em conjunto. A motivação desta pesquisa veio de estudos que alertaram para a consideração da integração da cadeia de suprimentos como um constructo multidimensional, englobando o envolvimento da manufatura, fornecedores e clientes no desenvolvimento de novos produtos; e devido à falta de informação sobre as influencias individuais destes agentes no desenvolvimento de novos produtos. Sob essas considerações, buscou-se construir um modelo analítico baseado na Teoria do Capital Social e Capacidade Absortiva, construir hipóteses a partir da revisão da literatura e conectar constructos como cooperação, envolvimento do fornecedor no desenvolvimento de novos produtos (DNP), envolvimento do cliente no DNP, envolvimento da manufatura no DNP, antecipação de novas tecnologias, melhoria contínua, desempenho operacional do DNP, desempenho de mercado do NPD e desempenho de negócio do DNP. Para testar as hipóteses foram consideradas três variáveis moderadoras, tais como turbulência ambiental (baixa, média e alta), indústria (eletrônicos, maquinários e equipamentos de transporte) e localização (América, Europa e Ásia). Para testar o modelo foram usados dados do projeto High Performance Manufacturing que contém 339 empresas das indústrias de eletrônicos, maquinários e equipamentos de transporte, localizadas em onze países. As hipóteses foram testadas por meio da Análise Fatorial Confirmatória (AFC) incluindo a moderação muti-grupo para as três variáveis moderadoras mencionadas anteriormente. Os principais resultados apontaram que as hipóteses relacionadas com cooperação foram confirmadas em ambientes de média turbulência, enquanto as hipóteses relacionadas ao desempenho no DNP foram confirmadas em ambientes de baixa turbulência ambiental e em países asiáticos. Adicionalmente, sob as mesmas condições, fornecedores, clientes e manufatura influenciam diferentemente no desempenho de novos produtos. Assim, o envolvimento de fornecedores influencia diretamente no desempenho operacional e indiretamente no desempenho de mercado e de negócio em baixos níveis de turbulência ambiental, na indústria de equipamentos de transporte em países da Americanos e Europeus. De igual forma, o envolvimento do cliente influenciou diretamente no desempenho operacional e indiretamente no desempenho de mercado e do negócio em médio nível de turbulência ambiental, na indústria de maquinários e em países Asiáticos. Fornecedores e clientes não influenciam diretamente no desempenho de mercado e do negócio e não influenciam indiretamente no desempenho operacional. O envolvimento da manufatura não influenciou nenhum tipo de desempenho do desenvolvimento de novos produtos em todos os cenários testados.

Genetic group x ambient temperature interaction effects on physiological responses and growth performance of rabbits

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The Performance of Elliptic Curve Based Group Diffie-Hellman Protocols for Secure Group Communication over Ad Hoc Networks

The security of the two party Diffie-Hellman key exchange protocol is currently based on the discrete logarithm problem (DLP). However, it can also be built upon the elliptic curve discrete logarithm problem (ECDLP). Most proposed secure group communication schemes employ the DLP-based Diffie-Hellman protocol. This paper proposes the ECDLP-based Diffie-Hellman protocols for secure group communication and evaluates their performance on wireless ad hoc networks. The proposed schemes are compared at the same security level with DLP-based group protocols under different channel conditions. Our experiments and analysis show that the Tree-based Group Elliptic Curve Diffie-Hellman (TGECDH) protocol is the best in overall performance for secure group communication among the four schemes discussed in the paper. Low communication overhead, relatively low computation load and short packets are the main reasons for the good performance of the TGECDH protocol.

Group abilities, individual group-efficacy beliefs and performance motivation: A mediation analysis

Introduction Research has shown that individuals infer their group-efficacy beliefs from the groups’ abilities to perform in specific tasks. Group abilities also seem to affect team members’ performance motivation adding a psychological advantage to teams already high on task relevant abilities. In a recent study we found the effect of group abilities on individual performance motivation to be partially mediated by the team members’ individual group-efficacy beliefs which is an example of how attributes on a group-level can be affecting individual-level parameters. Objectives The study aimed at testing the possibility to reduce the direct and mediated effects of low group abilities on performance motivation by augmenting the visibility of individual contributions to group performances via the inclusion of a separate ranking on individual performances. Method Forty-seven students (M=22.83 years, SD=2.83, 34% women) of the University of Bern participated in the study. At three collection points (t1-3) subjects were provided information about fictive team members with whom they had to imagine performing a group triathlon. Three values (low, medium, high) of the other team members’ abilities to perform in their parts of the triathlon (swimming and biking) were combined in a 3x3 full factorial design yielding nine groups with different ability profiles. At t1 subjects were asked to rate their confidence that the teams would perform well in the triathlon task, at t2 and t3 subjects were asked how motivated they were to perform at their best in the respective groups. At t3 the presence of an individual performance ranking was mentioned in the cover story. Mixed linear models (SPSS) and structural equation models for complex survey data (Mplus) were specified to estimate the effects of the individual performance rankings on the relationship between group-efficacy beliefs and performance motivation. Results A significant interaction effect for individual group-efficacy beliefs and the triathlon condition on performance motivation was found; the effect of group-efficacy beliefs on performance motivation being smaller with individual performance rankings available. The partial mediation of group attributes on performance motivation by group-efficacy beliefs disappeared with the announcement of individual performance rankings. Conclusion In teams low in task relevant abilities the disadvantageous effect of group-efficacy beliefs on performance motivation might be reduced by providing means of evaluating individual performances apart from a group’s overall performance. While it is believed that a common group goal is a core criterion for a well performing sport group future studies should also aim at the possible benefit of individualized goal setting in groups.

Group abilities, individual group-efficacy beliefs and performance motivation: A mediation analysis

Introduction Research has shown that individuals infer their group-efficacy beliefs from the groups’ abilities to perform in specific tasks. Group abilities also seem to affect team members’ performance motivation adding a psychological advantage to teams already high on task relevant abilities. In a recent study we found the effect of group abilities on individual performance motivation to be partially mediated by the team members’ individual group-efficacy beliefs which is an example of how attributes on a group-level can be affecting individual-level parameters. Objectives The study aimed at testing the possibility to reduce the direct and mediated effects of low group abilities on performance motivation by augmenting the visibility of individual contributions to group performances via the inclusion of a separate ranking on individual performances. Method Forty-seven students (M=22.83 years, SD=2.83, 34% women) of the University of Bern participated in the study. At three collection points (t1-3) subjects were provided information about fictive team members with whom they had to imagine performing a group triathlon. Three values (low, medium, high) of the other team members’ abilities to perform in their parts of the triathlon (swimming and biking) were combined in a 3x3 full factorial design yielding nine groups with different ability profiles. At t1 subjects were asked to rate their confidence that the teams would perform well in the triathlon task, at t2 and t3 subjects were asked how motivated they were to perform at their best in the respective groups. At t3 the presence of an individual performance ranking was mentioned in the cover story. Mixed linear models (SPSS) and structural equation models for complex survey data (Mplus) were specified to estimate the effects of the individual performance rankings on the relationship between group-efficacy beliefs and performance motivation. Results A significant interaction effect for individual group-efficacy beliefs and the triathlon condition on performance motivation was found; the effect of group-efficacy beliefs on performance motivation being smaller with individual performance rankings available. The partial mediation of group attributes on performance motivation by group-efficacy beliefs disappeared with the announcement of individual performance rankings. Conclusion In teams low in task relevant abilities the disadvantageous effect of group-efficacy beliefs on performance motivation might be reduced by providing means of evaluating individual performances apart from a group’s overall performance. While it is believed that a common group goal is a core criterion for a well performing sport group future studies should also aim at the possible benefit of individualized goal setting in groups.

Incorporating Group Recommendations to Recommender Systems: Alternatives and Performance

La importancia de los sistemas de recomendación ha experimentado un crecimiento exponencial como consecuencia del auge de las redes sociales. En esta tesis doctoral presentaré una amplia visión sobre el estado del arte de los sistemas de recomendación. Incialmente, estos estaba basados en fitrado demográfico, basado en contendio o colaborativo. En la actualidad, estos sistemas incorporan alguna información social al proceso de recomendación. En el futuro utilizarán información implicita, local y personal proveniente del Internet de las cosas. Los sistemas de recomendación basados en filtrado colaborativo se pueden modificar con el fin de realizar recomendaciones a grupos de usuarios. Existen trabajos previos que han incluido estas modificaciones en diferentes etapas del algoritmo de filtrado colaborativo: búsqueda de los vecinos, predicción de las votaciones y elección de las recomendaciones. En esta tesis doctoral proporcionaré un nuevo método que realizar el proceso de unficación (pasar de varios usuarios a un grupo) en el primer paso del algoritmo de filtrado colaborativo: cálculo de la métrica de similaridad. Proporcionaré una formalización completa del método propuesto. Explicaré cómo obtener el conjunto de k vecinos del grupo de usuarios y mostraré cómo obtener recomendaciones usando dichos vecinos. Asimismo, incluiré un ejemplo detallando cada paso del método propuesto en un sistema de recomendación compuesto por 8 usuarios y 10 items. Las principales características del método propuesto son: (a) es más rápido (más eficiente) que las alternativas proporcionadas por otros autores, y (b) es al menos tan exacto y preciso como otras soluciones estudiadas. Para contrastar esta hipótesis realizaré varios experimentos que miden la precisión, la exactitud y el rendimiento del método. Los resultados obtenidos se compararán con los resultados de otras alternativas utilizadas en la recomendación de grupos. Los experimentos se realizarán con las bases de datos de MovieLens y Netflix. ABSTRACT The importance of recommender systems has grown exponentially with the advent of social networks. In this PhD thesis I will provide a wide vision about the state of the art of recommender systems. They were initially based on demographic, contentbased and collaborative filtering. Currently, these systems incorporate some social information to the recommendation process. In the future, they will use implicit, local and personal information from the Internet of Things. As we will see here, recommender systems based on collaborative filtering can be used to perform recommendations to group of users. Previous works have made this modification in different stages of the collaborative filtering algorithm: establishing the neighborhood, prediction phase and determination of recommended items. In this PhD thesis I will provide a new method that carry out the unification process (many users to one group) in the first stage of the collaborative filtering algorithm: similarity metric computation. I will provide a full formalization of the proposed method. I will explain how to obtain the k nearest neighbors of the group of users and I will show how to get recommendations using those users. I will also include a running example of a recommender system with 8 users and 10 items detailing all the steps of the method I will present. The main highlights of the proposed method are: (a) it will be faster (more efficient) that the alternatives provided by other authors, and (b) it will be at least as precise and accurate as other studied solutions. To check this hypothesis I will conduct several experiments measuring the accuracy, the precision and the performance of my method. I will compare these results with the results generated by other methods of group recommendation. The experiments will be carried out using MovieLens and Netflix datasets.