Stomach temperature records reveal nursing behaviour and transition to solid food consumption in an unweaned mammal, the harbour seal pup (Phoca vitulina)

Knowledge of milk transfer from mother to offspring and early solid food ingestions in mammals allows for a greater understanding of the factors affecting transition to nutritional independence and pre-weaning growth and survival. Yet studies monitoring suckling behaviour have often relied on visual observations, which might not accurately represent milk intake. We assessed the use of stomach temperature telemetry to monitor suckling and foraging behaviour in free-ranging harbour seal (Phoca vitulina) pups during lactation. Stomach temperature declines were analysed using principal component and cluster analyses, as well as trials using simulated stomachs resulting in a precise classification of stomach temperature drops into milk, seawater and solid food ingestions. Seawater and solid food ingestions represented on average 15.361.6% [0-40.0%] and 0.760.2% [0-13.0%], respectively, of individual ingestions. Overall, 63.7% of milk ingestions occurred while the pups were in the water, of which 13.9% were preceded by seawater ingestion. The average time between subsequent ingestions was significantly less for seawater than for milk ingestions. These results suggest that seawater ingestion might represent collateral ingestion during aquatic suckling attempts. Alternatively, as solid food ingestions (n = 19) were observed among 7 pups, seawater ingestion could result from missed prey capture attempts. This study shows that some harbour seals start ingesting prey while still being nursed, indicating that weaning occurs more gradually than previously thought in this species. Stomach temperature telemetry represents a promising method to study suckling behaviour in wild mammals and transition to nutritional independence in various endotherm species.

Longitudinal predictors of frequent vegetable and fruit consumption among socio-economically disadvantaged Australian adolescents

Adequate vegetable and fruit consumption is necessary for preventing nutrition-related diseases. Socio-economically disadvantaged adolescents tend to consume relatively few vegetables and fruits. However, despite nutritional challenges associated with socio-economic disadvantage, a minority of adolescents manage to eat vegetables and fruit in quantities that are more in line with dietary recommendations. This investigation aimed to identify predictors of more frequent intakes of fruits and vegetables among adolescents over a 2-year follow-up period. Data were drawn from 521 socio-economically disadvantaged (maternal education ≤Year 10 of secondary school) Australian adolescents aged 12–15 years. Participants were recruited from 37 secondary schools and were asked to complete online surveys in 2004/2005 (baseline) and 2006/2007 (follow-up). Surveys comprised a 38-item FFQ and questions based on Social Ecological models examining intrapersonal, social and environmental influences on diet. At baseline and follow-up, respectively, 29% and 24% of adolescents frequently consumed vegetables (≥2 times/day); 33% and 36% frequently consumed fruit (≥1 time/day). In multivariable logistic regressions, baseline consumption strongly predicted consumption at follow-up. Frequently being served vegetables at dinner predicted frequent vegetable consumption. Female sex, rarely purchasing food or drink from school vending machines, and usually being expected to eat all foods served predicted frequent fruit consumption. Findings suggest nutrition promotion initiatives aimed at improving eating behaviours among this at-risk population and should focus on younger adolescents, particularly boys; improving adolescent eating behaviours at school; and encouraging families to increase home availability of healthy foods and to implement meal time rules.

A data mining framework for electricity consumption analysis from meter data

This paper presents a novel data mining framework for the exploration and extraction of actionable knowledge from data generated by electricity meters. Although a rich source of information for energy consumption analysis, electricity meters produce a voluminous, fast-paced, transient stream of data that conventional approaches are unable to address entirely. In order to overcome these issues, it is important for a data mining framework to incorporate functionality for interim summarization and incremental analysis using intelligent techniques. The proposed Incremental Summarization and Pattern Characterization (ISPC) framework demonstrates this capability. Stream data is structured in a data warehouse based on key dimensions enabling rapid interim summarization. Independently, the IPCL algorithm incrementally characterizes patterns in stream data and correlates these across time. Eventually, characterized patterns are consolidated with interim summarization to facilitate an overall analysis and prediction of energy consumption trends. Results of experiments conducted using the actual data from electricity meters confirm applicability of the ISPC framework.

A control methodology for DFIG type wind turbines connected to distribution networks

This paper proposes a decentralised controller design for doubly-fed induction generators (DFIGs) to enhance dynamic performance of distribution networks. The change in the output power due to the variable nature of wind is considered as an uncertain term in the design algorithm. In addition, the interconnection effect of the other subsystems are considered in the design process. The H norm of the uncertain system is found out and simultaneous output-feedback linear controllers are designed based controller is verified on a 16 bus distribution test system for severe disturbances. Simulation results indicate that the designed controller is robust against uncertainties in operating conditions

Stability analysis of grid-connected photovoltaic systems using a linear zero dynamic controller

This paper proposed a new linear zero dynamic controller (LZDC) for