A possible reconceptualization of food engineering discipline

Food industry is critical to any nation’s health and well-being; it is also critical to the economic health of a nation, since it can typically constitute over a fifth of the nation’s manufacturing GDP. Food Engineering is a discipline that ought to be at the heart of the food industry. Unfortunately, this discipline is not playing its rightful role today: engineering has been relegated to play the role of a service provider to the food industry, instead of it being a strategic driver for the very growth of the industry. This paper hypothesises that food engineering discipline, today, seems to be continuing the way it was in the last century, and has not risen to the challenges that it really faces. This paper therefore categorises the challenges as those being posed by: 1. Business dynamics, 2. Market forces, 3. Manufacturing environment and 4. Environmental Considerations, and finds the current scope and subject-knowledge competencies of food engineering to be inadequate in meeting these challenges. The paper identifies: a) health, b) environment and c) security as the three key drivers of the discipline, and proposes a new definition of food engineering. This definition requires food engineering to have a broader science base which includes biophysical, biochemical and health sciences, in addition to engineering sciences. This definition, in turn, leads to the discipline acquiring a new set of subject-knowledge competencies that is fit-for-purpose for this day and age, and hopefully for the foreseeable future. The possibility of this approach leading to the development of a higher education program in food engineering is demonstrated by adopting a theme based curriculum development with five core themes, supplemented by appropriate enabling and knowledge integrating courses. At the heart of this theme based approach is an attempt to combine engineering of process and product in a purposeful way, termed here as Food Product Realisation Engineering. Finally, the paper also recommends future development of two possible niche specialisation programs in Nutrition and Functional Food Engineering and Gastronomic Engineering. It is hoped that this reconceptualization of the discipline will not only make it more purposeful for the food industry, but it will also make the subject more intellectually challenging and attract bright young minds to the discipline.

The Acute Care Undergraduate TEaching (ACUTE) initiative: consensus development of core competencies in acute care for undergraduates in the United Kingdom

Background: The care of the acutely ill patient in hospital is often sub-optimal. Poor recognition of critical illness combined with a lack of knowledge, failure to appreciate the clinical urgency of a situation, a lack of supervision, failure to seek advice and poor communication have been identified as contributory factors. At present the training of medical students in these important skills is fragmented. The aim of this study was to use consensus techniques to identify the core competencies in the care of acutely ill or arrested adult patients that medical students should possess at the point of graduation. Design: Healthcare professionals were invited to contribute suggestions for competencies to a website as part of a modified Delphi survey. The competency proposals were grouped into themes and rated by a nominal group comprised of physicians, nurses and students from the UK. The nominal group rated the importance of each competency using a 5-point Likert scale. Results: A total of 359 healthcare professionals contributed 2,629 competency suggestions during the Delphi survey. These were reduced to 88 representative themes covering: airway and oxygenation; breathing and ventilation; circulation; confusion and coma; drugs, therapeutics and protocols; clinical examination; monitoring and investigations; team-working, organisation and communication; patient and societal needs; trauma; equipment; pre-hospital care; infection and inflammation. The nominal group identified 71 essential and 16 optional competencies which students should possess at the point of graduation. Conclusions: We propose these competencies form a core set for undergraduate training in resuscitation and acute care.

An ontological approach to competency management

Competency management is a very important part of a well-functioning organisation. Unfortunately competency descriptions are not uniformly specified nor defined across borders: National, sectorial or organisational, leading to an opaque competency description market with a multitude of competency frameworks and competency benchmarks. An ontology is a formalised description of a domain, which enables automated reasoning engines to be built which by utilising the interrelations between entities can make “intelligent” choices in different situations within the domain. Introducing formalised competency ontologies automated tools, such as skill gap analysis, training suggestion generation, job search and recruitment, can be developed, which compare and contrast different competency descriptions on the semantic level. The major problem with defining a common formalised ontology for competencies is that there are so many viewpoints of competencies and competency frameworks. Work within the TRACE project has focused on finding common trends within different competency frameworks in order to allow an intermediate competency description to be made, which other frameworks can reference. This research has shown that competencies can be divided up into “knowledge”, “skills” and what we call “others”. An ontology has been created based on this with a simple structure of different “kinds” of “knowledges” and “skills” using semantic interrelations to define the basic semantic structure of the ontology. A prototype tool for analysing a skill gap analysis has been developed. Personal profiles can be produced using the tool and a skill gap analysis is performed on a desired competency profile by using an ontologically based inference engine, which is able to list closest fit and possible proficiency gaps

Can knowledge of the state of the stratosphere be used to improve statistical forecasts of the troposphere?

Recent analysis of the Arctic Oscillation (AO) in the stratosphere and troposphere has suggested that predictability of the state of the tropospheric AO may be obtained from the state of the stratospheric AO. However, much of this research has been of a purely qualitative nature. We present a more thorough statistical analysis of a long AO amplitude dataset which seeks to establish the magnitude of such a link. A relationship between the AO in the lower stratosphere and on the 1000 hPa surface on a 10-45 day time-scale is revealed. The relationship accounts for 5% of the variance of the 1000 hPa time series at its peak value and is significant at the 5% level. Over a similar time-scale the 1000 hPa time series accounts for 1% of itself and is not significant at the 5% level. Further investigation of the relationship reveals that it is only present during the winter season and in particular during February and March. It is also demonstrated that using stratospheric AO amplitude data as a predictor in a simple statistical model results in a gain of skill of 5% over a troposphere-only statistical model. This gain in skill is not repeated if an unrelated time series is included as a predictor in the model. Copyright © 2003 Royal Meteorological Society

Strategy clusters and sources of knowledge in French L2 listening comprehension

This article reports on an exploratory investigation into the listening strategies of lower-intermediate learners of French as an L2, including the sources of knowledge they employed in order to comprehend spoken French. Data from 14 learners were analysed to investigate whether employment of strategies in general and sources of knowledge in particular varied according to the underlying linguistic knowledge of the student. While low linguistic knowledge learners were less likely to deploy effectively certain strategies or strategy clusters, high linguistic knowledge levels were not always associated with effective strategy use. Similarly, while there was an association between linguistic knowledge and learners’ ability to draw on more than one source of knowledge in a facilitative manner, there was also evidence that learners tended to over-rely on linguistic knowledge where other sources, such as world knowledge, would have proved facilitative. We conclude by arguing for a fresh approach to listening pedagogy and research, including strategy instruction, bottom-up skill development and a consideration of the role of linguistic knowledge in strategy use.

What's in a name? Lexical knowledge drives infants' visual preferences in the absence of referential input

Seventeen-month-old infants were presented with pairs of images, in silence or with the non-directive auditory stimulus 'look!'. The images had been chosen so that one image depicted an item whose name was known to the infant, and the other image depicted an image whose name was not known to the infant. Infants looked longer at images for which they had names than at images for which they did not have names, despite the absence of any referential input. The experiment controlled for the familiarity of the objects depicted: in each trial, image pairs presented to infants had previously been judged by caregivers to be of roughly equal familiarity. From a theoretical perspective, the results indicate that objects with names are of intrinsic interest to the infant. The possible causal direction for this linkage is discussed and it is concluded that the results are consistent with Whorfian linguistic determinism, although other construals are possible. From a methodological perspective, the results have implications for the use of preferential looking as an index of early word comprehension.

Negative correlations between control performance and verbalizable knowledge: indicators for implicit learning in process control tasks?

Negative correlations between task performance in dynamic control tasks and verbalizable knowledge, as assessed by a post-task questionnaire, have been interpreted as dissociations that indicate two antagonistic modes of learning, one being “explicit”, the other “implicit”. This paper views the control tasks as finite-state automata and offers an alternative interpretation of these negative correlations. It is argued that “good controllers” observe fewer different state transitions and, consequently, can answer fewer post-task questions about system transitions than can “bad controllers”. Two experiments demonstrate the validity of the argument by showing the predicted negative relationship between control performance and the number of explored state transitions, and the predicted positive relationship between the number of explored state transitions and questionnaire scores. However, the experiments also elucidate important boundary conditions for the critical effects. We discuss the implications of these findings, and of other problems arising from the process control paradigm, for conclusions about implicit versus explicit learning processes.

Modeling the user knowledge by belief networks

This paper describes the user modeling component of EPIAIM, a consultation system for data analysis in epidemiology. The component is aimed at representing knowledge of concepts in the domain, so that their explanations can be adapted to user needs. The first part of the paper describes two studies aimed at analysing user requirements. The first one is a questionnaire study which examines the respondents' familiarity with concepts. The second one is an analysis of concept descriptions in textbooks and from expert epidemiologists, which examines how discourse strategies are tailored to the level of experience of the expected audience. The second part of the paper describes how the results of these studies have been used to design the user modeling component of EPIAIM. This module works in a two-step approach. In the first step, a few trigger questions allow the activation of a stereotype that includes a "body" and an "inference component". The body is the representation of the body of knowledge that a class of users is expected to know, along with the probability that the knowledge is known. In the inference component, the learning process of concepts is represented as a belief network. Hence, in the second step the belief network is used to refine the initial default information in the stereotype's body. This is done by asking a few questions on those concepts where it is uncertain whether or not they are known to the user, and propagating this new evidence to revise the whole situation. The system has been implemented on a workstation under UNIX. An example of functioning is presented, and advantages and limitations of the approach are discussed.

Implicit and explicit knowledge bases in artificial grammar learning

Two experiments examined the claim for distinct implicit and explicit learning modes in the artificial grammar-learning task (Reber, 1967, 1989). Subjects initially attempted to memorize strings of letters generated by a finite-state grammar and then classified new grammatical and nongrammatical strings. Experiment 1 showed that subjects' assessment of isolated parts of strings was sufficient to account for their classification performance but that the rules elicited in free report were not sufficient. Experiment 2 showed that performing a concurrent random number generation task under different priorities interfered with free report and classification performance equally. Furthermore, giving different groups of subjects incidental or intentional learning instructions did not affect classification or free report.