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 Tnt1 family member Retrosol copy number and structure disclose retrotransposon diversification in different Solanum species

Eukaryotic genome expansion/retraction caused by LTR-retrotransposon activity is dependent on the expression of full length copies to trigger efficient transposition and recombination-driven events. The Tnt1 family of retrotransposons has served as a model to evaluate the diversity among closely related elements within Solanaceae species and found that members of the family vary mainly in their U3 region of the long terminal repeats (LTRs). Recovery of a full length genomic copy of Retrosol was performed through a PCR-based approach from wild potato, Solanum oplocense. Further characterization focusing on both LTR sequences of the amplified copy allowed estimating an approximate insertion time at 2 million years ago thus supporting the occurrence of transposition cycles after genus divergence. Copy number of Tnt1-like elements in Solanum species were determined through genomic quantitative PCR whereby results sustain that Retrosol in Solanum species is a low copy number retrotransposon (1-4 copies) while Retrolyc1 has an intermediate copy number (38 copies) in S. peruvianum. Comparative analysis of retrotransposon content revealed no correlation between genome size or ploidy level and Retrosol copy number. The tetraploid cultivated potato with a cellular genome size of 1,715 Mbp harbours similar copy number per monoploid genome than other diploid Solanum species (613-884 Mbp). Conversely, S. peruvianum genome (1,125 Mbp) has a higher copy number. These results point towards a lineage specific dynamic flux regarding the history of amplification/activity of Tnt1-like elements in the genome of Solanum species.

The nested assembly of individual-resource networks

P>1. Much of the current understanding of ecological systems is based on theory that does not explicitly take into account individual variation within natural populations. However, individuals may show substantial variation in resource use. This variation in turn may be translated into topological properties of networks that depict interactions among individuals and the food resources they consume (individual-resource networks). 2. Different models derived from optimal diet theory (ODT) predict highly distinct patterns of trophic interactions at the individual level that should translate into distinct network topologies. As a consequence, individual-resource networks can be useful tools in revealing the incidence of different patterns of resource use by individuals and suggesting their mechanistic basis. 3. In the present study, using data from several dietary studies, we assembled individual-resource networks of 10 vertebrate species, previously reported to show interindividual diet variation, and used a network-based approach to investigate their structure. 4. We found significant nestedness, but no modularity, in all empirical networks, indicating that (i) these populations are composed of both opportunistic and selective individuals and (ii) the diets of the latter are ordered as predictable subsets of the diets of the more opportunistic individuals. 5. Nested patterns are a common feature of species networks, and our results extend its generality to trophic interactions at the individual level. This pattern is consistent with a recently proposed ODT model, in which individuals show similar rank preferences but differ in their acceptance rate for alternative resources. Our findings therefore suggest a common mechanism underlying interindividual variation in resource use in disparate taxa.

Infant mortality model for lifetime data

In this paper we introduce a parametric model for handling lifetime data where an early lifetime can be related to the infant-mortality failure or to the wear processes but we do not know which risk is responsible for the failure. The maximum likelihood approach and the sampling-based approach are used to get the inferences of interest. Some special cases of the proposed model are studied via Monte Carlo methods for size and power of hypothesis tests. To illustrate the proposed methodology, we introduce an example consisting of a real data set.

Image indexing and retrieval using an ART-2A neural network architecture

Traditional content-based image retrieval (CBIR) systems use low-level features such as colors, shapes, and textures of images. Although, users make queries based on semantics, which are not easily related to such low-level characteristics. Recent works on CBIR confirm that researchers have been trying to map visual low-level characteristics and high-level semantics. The relation between low-level characteristics and image textual information has motivated this article which proposes a model for automatic classification and categorization of words associated to images. This proposal considers a self-organizing neural network architecture, which classifies textual information without previous learning. Experimental results compare the performance results of the text-based approach to an image retrieval system based on low-level features. (c) 2008 Wiley Periodicals, Inc.

Global minimization using an Augmented Lagrangian method with variable lower-level constraints

A novel global optimization method based on an Augmented Lagrangian framework is introduced for continuous constrained nonlinear optimization problems. At each outer iteration k the method requires the epsilon(k)-global minimization of the Augmented Lagrangian with simple constraints, where epsilon(k) -> epsilon. Global convergence to an epsilon-global minimizer of the original problem is proved. The subproblems are solved using the alpha BB method. Numerical experiments are presented.

Performance evaluation of routing protocols for MANETs with known connectivity patterns using evolving graphs

The assessment of routing protocols for mobile wireless networks is a difficult task, because of the networks` dynamic behavior and the absence of benchmarks. However, some of these networks, such as intermittent wireless sensors networks, periodic or cyclic networks, and some delay tolerant networks (DTNs), have more predictable dynamics, as the temporal variations in the network topology can be considered as deterministic, which may make them easier to study. Recently, a graph theoretic model-the evolving graphs-was proposed to help capture the dynamic behavior of such networks, in view of the construction of least cost routing and other algorithms. The algorithms and insights obtained through this model are theoretically very efficient and intriguing. However, there is no study about the use of such theoretical results into practical situations. Therefore, the objective of our work is to analyze the applicability of the evolving graph theory in the construction of efficient routing protocols in realistic scenarios. In this paper, we use the NS2 network simulator to first implement an evolving graph based routing protocol, and then to use it as a benchmark when comparing the four major ad hoc routing protocols (AODV, DSR, OLSR and DSDV). Interestingly, our experiments show that evolving graphs have the potential to be an effective and powerful tool in the development and analysis of algorithms for dynamic networks, with predictable dynamics at least. In order to make this model widely applicable, however, some practical issues still have to be addressed and incorporated into the model, like adaptive algorithms. We also discuss such issues in this paper, as a result of our experience.

Application of Narrative Pedagogy to Promote Excellence in the Clinical Setting

The clinical setting has become increasingly complex in recent years. Nurse educators have recognized the limitations of traditional pedagogies in the clinical setting. The need for innovative, student-centered learning is essential in order to transfer knowledge to practical situations and discover new ways of thinking about clinical situations. Narrative pedagogy which emphasizes how students learn and experience learning is an effective evidence-based approach to clinical education.

Talangfabriken : Om organisation av kunskap och kreativitet i skivindustrin

The purpose of this dissertation is to describe, explain and understand how record companies identify and develop new music and new talent. The analysis is carried out on three levels: individual, organizational and sector level. In a record company, this task formally goes to A&R (Artist and Repertoire). This dissertation takes its point of departure in how the capacity for discovering new talent can be understood in terms of knowledge, creativity and competence and how this capacity is affected in the meeting between the record company and the industry. The theoretical framework of the dissertation spans two sociological fields: the sociology of organizations and the sociology of knowledge. While it takes its organizational starting point in the Knowledge Company Approach, it employs a practice-based approach to discuss knowledge. I argue that within the Knowledge company approach there are two contrasting ways to understand knowledge; a distinction is made between knowledge- and creativity-intensive enterprises. The results show that the record industry’s polarized structure can be seen as a result of the Knowledge Company’s typical problems. The A&R’s work is described as including two phases, one intuitive and one analytical. The intuitive assessment is direct, unconscious and without reflection. This ability has been described as "intuition" and "gut feeling". The analytical phase adds analysis and reflection based on knowledge. The results from the interviews with A&R’s reveal the limit of formal and explicit knowledge not only in the choice of music but also in the marketing strategies. The overarching picture is one in which record companies move in a space characterized by tension between dichotomous forces – art and commercialism, creativity and knowledge, culture and economy, chaos and order, but where opposite poles are not mutually exclusive but complementary.

Undersökande arbetssätt i NO-undervisningen i grundskolans tidigare årskurser

This thesis deals with the use of inquiry-based approaches in primary school science. The aim is to investigate the goals and purposes that are constituted by the curriculum and by the teachers in interviews and through their teaching in the classroom. The results are used to develop conceptual tools that can be used by teachers’ in their work to support students’ learning of science when using an inquiry-based approach. The thesis is comprised of four papers. In paper one a comparative analysis is made of five Swedish national curricula for compulsory school regarding what students should learn about scientific inquiry. In paper two 20 teachers were interviewed about their own teaching using inquiry. Classroom interactions were filmed and analyzed in papers three and four, which examine how primary teachers use the various activities and purposes of the inquiry classroom to support learning progressions in science. The results of paper one show how the emphasis within and between the two goals of learning to carry out investigations and learning about the nature of science shifted and changed over time in the different curricula. Paper two describes the selective traditions and qualities that were emphasized in the teachers’ accounts of their own teaching. The results of papers three and four show how students need to be involved in the proximate and ultimate purposes of the teaching activities for progression to happen. The ultimate purposes are the scientific purposes for the lesson (as given by the teacher or by the curriculum), whereas the proximate purposes are the more student-centered purposes that through different activities should allow the students to relate their own experiences and language to the ultimate purpose. The results show the importance of proximate purposes working as ends-in-viewin the sense of John Dewey, meaning that the students see the goal of the activity and that they are able to relate to their experiences and familiar language.

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

Granularity and disaggregation in compositional modelling with applications to ecological systems

In the past decade, compositional modelling (CM) has established itself as the predominant knowledge-based approach to construct mathematical (simulation) models automatically. Although it is mainly applied to physical systems, there is a growing interest in applying CM to other domains, such as ecological and socio-economic systems. Inspired by this observation, this paper presents a method for extending the conventional CM techniques to suit systems that are fundamentally presented by interacting populations of individuals instead of physical components or processes. The work supports building model repositories for such systems, especially in addressing the most critical outstanding issues of granularity and disaggregation in ecological systems modelling.

Compositional Model Repositories via Dynamic Constraint Satisfaction with Order-of-Magnitude Preferences

The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude.

Does The Risk Of Groundwater Depletion Drive Tube-Well Technology Adoption: A Case Of Pakistan

We employ a moment-based approach to empirically analyse farmer’s decisions about adoption of tube-well technology under depleting groundwater resources using a farm level data from 200 farming households in the Punjab province, Pakistan. The results indicate that the higher the expected profit the greater the probability of adoption. Similarly, with increasing variance the probability of adopting tube-well increases significantly indicating that farmers choose to adopt tube-well technology in order to hedge against production risks. Statistical non-significant the third moment i.e., skewness indicates that farmer generally do not consider downside yield risk when decide to adopt tube-well technology whereas highly significant fourth moment (kurtosis) employ that probability of adoption decreases as a result of extreme events in profit distribution. In addition, we show that land tenureship and three other exogenous variables, i.e., extension services, access to different sources of information and off-farm income play a significant role in the adoption process.

Multi-Objective Pipe Smoothing Genetic Algorithm For Water Distribution Network Design

This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.