Alkaline phosphatase activity in pasteurized milk: a quantitative comparison of Fluorophos and colourimetric procedures

Fluorophos and colourimetric procedures for alkaline phosphatase (ALP) testing were compared using milk with raw milk additions, purified bovine ALP additions and heat treatments. Repeatability was between 0.9% and 10.1% for Fluorophos, 3.5% and 46.1% for the Aschaffenburg and Mullen (A&M) procedure and 4.4% and 8.8% for the Scharer rapid test. Linearity (R-2) using raw milk addition was 0.96 between Fluorophos and the Scharer procedure. Between the Fluorophos and the A&M procedures, R-2 values were 0.98, 0.99 and 0.98 for raw milk additions, bovine ALP additions and heat treatments respectively. Fluorophos showed greater sensitivity and was both faster and simpler to perform.

Distinguishing novelty and familiarity effects in infant preference procedures

This paper considers possible problems researchers might face when interpreting the results of studies that employ variants of the preference procedure. Infants show a tendency to shift their preference from familiar to novel stimuli with increasing exposure to the familiar stimulus, a behaviour that is exploited by the habituation paradigm. This change in attentional preference with exposure leads us to suggest that researchers interested in infants' pre-experimental or spontaneous preferences should beware of the potentially confounding effects of exposing infants to familiarization trials prior to employing the preference procedure. The notion that infant attentional preference is dynamic also calls into question the use of the direction of post-familiarization preference per se when interpreting the knowledge or strategies available to infants. We look into the results of a cross-modal word learning study to show how the interpretation of results may be difficult when infants exhibit a significant preference in an unexpected direction. As a possible solution to this problem we propose that significant preferences in both directions should be sought at multiple intervals over time. Copyright (C) 2004 John Wiley Sons, Ltd.

Using continuous ground-based radar and lidar measurements for evaluating the representation of clouds in four operational models

The ability of four operational weather forecast models [ECMWF, Action de Recherche Petite Echelle Grande Echelle model (ARPEGE), Regional Atmospheric Climate Model (RACMO), and Met Office] to generate a cloud at the right location and time (the cloud frequency of occurrence) is assessed in the present paper using a two-year time series of observations collected by profiling ground-based active remote sensors (cloud radar and lidar) located at three different sites in western Europe (Cabauw. Netherlands; Chilbolton, United Kingdom; and Palaiseau, France). Particular attention is given to potential biases that may arise from instrumentation differences (especially sensitivity) from one site to another and intermittent sampling. In a second step the statistical properties of the cloud variables involved in most advanced cloud schemes of numerical weather forecast models (ice water content and cloud fraction) are characterized and compared with their counterparts in the models. The two years of observations are first considered as a whole in order to evaluate the accuracy of the statistical representation of the cloud variables in each model. It is shown that all models tend to produce too many high-level clouds, with too-high cloud fraction and ice water content. The midlevel and low-level cloud occurrence is also generally overestimated, with too-low cloud fraction but a correct ice water content. The dataset is then divided into seasons to evaluate the potential of the models to generate different cloud situations in response to different large-scale forcings. Strong variations in cloud occurrence are found in the observations from one season to the same season the following year as well as in the seasonal cycle. Overall, the model biases observed using the whole dataset are still found at seasonal scale, but the models generally manage to well reproduce the observed seasonal variations in cloud occurrence. Overall, models do not generate the same cloud fraction distributions and these distributions do not agree with the observations. Another general conclusion is that the use of continuous ground-based radar and lidar observations is definitely a powerful tool for evaluating model cloud schemes and for a responsive assessment of the benefit achieved by changing or tuning a model cloud

Design and development of a haptic dental training system - hapTEL

This paper presents a novel design of a virtual dental training system (hapTEL) using haptic technology. The system allows dental students to learn and practice procedures such as dental drilling, caries removal and cavity preparation for tooth restoration. This paper focuses on the hardware design, development and evaluation aspects in relation to the dental training and educational requirements. Detailed discussions on how the system offers dental students a natural operational position are documented. An innovative design of measuring and connecting the dental tools to the haptic device is also shown. Evaluation of the impact on teaching and learning is discussed.

An agent based approach to distributed task modeling for co-operative task support

This paper describes the design and implementation of an agent based network for the support of collaborative switching tasks within the control room environment of the National Grid Company plc. This work includes aspects from several research disciplines, including operational analysis, human computer interaction, finite state modelling techniques, intelligent agents and computer supported co-operative work. Aspects of these procedures have been used in the analysis of collaborative tasks to produce distributed local models for all involved users. These models have been used as the basis for the production of local finite state automata. These automata have then been embedded within an agent network together with behavioural information extracted from the task and user analysis phase. The resulting support system is capable of task and communication management within the transmission despatch environment.