A novel role for retromer in the control of epithelial cell polarity

The establishment and maintenance of epithelial cell polarity is essential throughout the development and adult life of all multicellular organisms. A key player in maintaining epithelial polarity is Crumbs (Crb), an evolutionarily conserved type-I transmembrane protein initially identified in Drosophila. Correct Crb levels and apical localization are imperative for its function. However, as is the case for many polarized proteins, the mechanisms of its trafficking and strict apical localization are poorly understood. To address these questions, we developed a liposome-based assay to identify trafficking coats and interaction partners of Crb in a native-like environment. Thereby, we demonstrated that Crb is a cargo for Retromer, a trafficking complex required for transport from endosomes to the trans-Golgi-network. The functional importance of this interaction was revealed by studies in Drosophila epithelia, which established Retromer as a novel regulator of epithelial cell polarity and verified the vast potential of this technique.

A novel approach to modelling and exploiting uncertainty in stochastic control systems

We consider an inversion-based neurocontroller for solving control problems of uncertain nonlinear systems. Classical approaches do not use uncertainty information in the neural network models. In this paper we show how we can exploit knowledge of this uncertainty to our advantage by developing a novel robust inverse control method. Simulations on a nonlinear uncertain second order system illustrate the approach.

The choice of the model in inventory control and the cost of sophistication

This thesis is concerned with the inventory control of items that can be considered independent of one another. The decisions when to order and in what quantity, are the controllable or independent variables in cost expressions which are minimised. The four systems considered are referred to as (Q, R), (nQ,R,T), (M,T) and (M,R,T). Wiith ((Q,R) a fixed quantity Q is ordered each time the order cover (i.e. stock in hand plus on order ) equals or falls below R, the re-order level. With the other three systems reviews are made only at intervals of T. With (nQ,R,T) an order for nQ is placed if on review the inventory cover is less than or equal to R, where n, which is an integer, is chosen at the time so that the new order cover just exceeds R. In (M, T) each order increases the order cover to M. Fnally in (M, R, T) when on review, order cover does not exceed R, enough is ordered to increase it to M. The (Q, R) system is examined at several levels of complexity, so that the theoretical savings in inventory costs obtained with more exact models could be compared with the increases in computational costs. Since the exact model was preferable for the (Q,R) system only exact models were derived for theoretical systems for the other three. Several methods of optimization were tried, but most were found inappropriate for the exact models because of non-convergence. However one method did work for each of the exact models. Demand is considered continuous, and with one exception, the distribution assumed is the normal distribution truncated so that demand is never less than zero. Shortages are assumed to result in backorders, not lost sales. However, the shortage cost is a function of three items, one of which, the backorder cost, may be either a linear, quadratic or an exponential function of the length of time of a backorder, with or without period of grace. Lead times are assumed constant or gamma distributed. Lastly, the actual supply quantity is allowed to be distributed. All the sets of equations were programmed for a KDF 9 computer and the computed performances of the four inventory control procedures are compared under each assurnption.

A quantitative analysis of optic nerve axons in elderly control subjects and patients with Alzheimer's disease

Objective: To study the density and cross-sectional area of axons in the optic nerve in elderly control subjects and in cases of Alzheimer's disease (AD) using an image analysis system. Methods: Sections of optic nerves from control and AD patients were stained with toluidine blue to reveal axon profiles. Results: The density of axons was reduced in both the center and peripheral portions of the optic nerve in AD compared with control patients. Analysis of axons with different cross-sectional areas suggested a specific loss of the smaller sized axons in AD, i.e., those with areas less that 1.99 μm2. An analysis of axons >11 μm2 in cross-sectional area suggested no specific loss of the larger axons in this group of patients. Conclusions: The data suggest that image analysis provides an accurate and reproducible method of quantifying axons in the optic nerve. In addition, the data suggest that axons are lost throughout the optic nerve with a specific loss of the smaller-sized axons. Loss of the smaller axons may explain the deficits in color vision observed in a significant proportion of patients with AD.

The development of a computer simulation model of the interaction between the supply and usage of major components in car assembly you use in stock control

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Fuzzy knowledge-based approach to treating uncertainty in inventory control

Inventory control in complex manufacturing environments encounters various sources of uncertainity and imprecision. This paper presents one fuzzy knowledge-based approach to solving the problem of order quantity determination, in the presence of uncertain demand, lead time and actual inventory level. Uncertain data are represented by fuzzy numbers, and vaguely defined relations between them are modeled by fuzzy if-then rules. The proposed representation and inference mechanism are verified using a large numbers of examples. The results of three representative cases are summarized. Finally a comparison between the developed fuzzy knowledge-based and traditional, probabilistic approaches is discussed.

A mixture density network approach to modelling and exploiting uncertainty in nonlinear control problems

In nonlinear and stochastic control problems, learning an efficient feed-forward controller is not amenable to conventional neurocontrol methods. For these approaches, estimating and then incorporating uncertainty in the controller and feed-forward models can produce more robust control results. Here, we introduce a novel inversion-based neurocontroller for solving control problems involving uncertain nonlinear systems which could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. Based on importance sampling from these distributions a novel robust inverse control approach is obtained. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The developed methodology circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider. A nonlinear multi-variable system with different delays between the input-output pairs is used to demonstrate the successful application of the developed control algorithm. The proposed method is suitable for redundant control systems and allows us to model strongly non-Gaussian distributions of control signal as well as processes with hysteresis. © 2004 Elsevier Ltd. All rights reserved.

Role of hexose transport in control of glycolytic flux in Saccharomyces cerevisiae

The yeast Saccharomyces cerevisiae predominantly ferments glucose to ethanol at high external glucose concentrations, irrespective of the presence of oxygen. In contrast, at low external glucose concentrations and in the presence of oxygen, as in a glucose-limited chemostat, no ethanol is produced. The importance of the external glucose concentration suggests a central role for the affinity and maximal transport rates of yeast's glucose transporters in the control of ethanol production. Here we present a series of strains producing functional chimeras between the hexose transporters Hxt1 and Hxt7, each of which lias distinct glucose transport characteristics. The strains display a range of decreasing glycolytic rates resulting in a proportional decrease in ethanol production. Using these strains, we show for the first time that at high glucose levels, the glucose uptake capacity of wild-type S. cerevisiae does not control glycolytic flux during exponential batch growth. In contrast, our chimeric Hxt transporters control the rate of glycolysis to a high degree. Strains whose glucose uptake is mediated by these chimeric transporters will undoubtedly provide a powerful tool with which to examine in detail the mechanism underlying the switch between fermentation and respiration in S. cerevisiae and will provide new tools for the control of industrial fermentations.

Vergence control across saccades in dyslexic adults

Many aspects of vision have been investigated in developmental dyslexia. Some research suggests deficits in vergence control (e.g. Buzzelli, 1991, Optom. Vision Sci. 68, 842±846), although ability to control vergence across saccades has not yet been investigated. We have explored this question indirectly using Enright's (1996 Vision Res. 36, 307±312.) sequential stereopsis task. The task requires observers to set two adjacent targets (whose textures cannot be resolved simultaneously if either is fixated) to appear equi-distant. Enright has argued that sequential stereopsis stereoacuity thresholds offer an indication of vergence control across saccades. We report two experiments using a total of 17 dyslexic and 18 control adults. Performance was measured on a sequential stereopsis task and an ordinary `simultaneous' stereopsis task. No significant differences between groups were found. However, whereas practice of the sequential task lowered control group thresholds on the simultaneous task, for the dyslexic group it significantly raised thresholds, suggesting that visual fatigue is especially important in investigations of visual functions in dyslexia. Although the small samples used limit conclusions at this stage, the main sequential stereopsis results suggest that, if Enright is correct, dyslexic adults can show normal vergence control across saccades.

Enabling innovation:knowledge control, sharing and coordination boundaries in UK and German manufacturing

We investigate how boundaries in knowledge control, sharing and co-ordination influence UK and German manufacturing firms’ innovation intensity (an indicator of the volume of product change) and product life (an indicator of the pace of generational change). In general UK plants more commonly face knowledge control boundaries related to plant ownership or control, while German plants more commonly face boundaries related to knowledge sharing and knowledge co-ordination between functional groups. Our empirical results emphasise the importance of the strategic management of innovation. Knowledge control boundaries – related to external ownership, group membership and decision making autonomy – have a weak negative influence on plants’ innovation outcomes. Strategic decisions relating to multifunctional working and networking are found to be more important in overcoming knowledge sharing and co-ordination boundaries. Knowledge sharing boundaries, related to plant or company boundaries, prove most important where a plant has no in-house R&D capability. Knowledge co-ordination boundaries related to functional or multi-functional working have strong but differential effects on different innovation output measures: functional boundaries increase product life in both countries, and in Germany maintaining functional boundaries is also associated with increased innovation intensity.

The human factors aspects of alarms in human supervisory control tasks.

This research thesis is concerned with the human factors aspects of industrial alarm systems within human supervisory control tasks. Typically such systems are located in central control rooms, and the information may be presented via visual display units. The thesis develops a human, rather than engineering, centred approach to the assessment, measurement and analysis of the situation. A human factors methodology was employed to investigate the human requirements through: interviews, questionnaires, observation and controlled experiments. Based on the analysis of current industrial alarm systems in a variety of domains (power generation, manufacturing and coronary care), it is suggested that often designers do not pay due considerations to the human requirements. It is suggested that most alarm systems have severe shortcomings in human factors terms. The interviews, questionnaire and observations led to the proposal of 'alarm initiated activities' as a framework for the research to proceed. The framework comprises of six main stages: observe, accept, analyse, investigate, correct and monitor. This framework served as a basis for laboratory research into alarm media. Under consideration were speech-based alarm displays and visual alarm displays. Non-speech auditory displays were the subject of a literature review. The findings suggest that care needs to be taken when selecting the alarm media. Ideally it should be chosen to support the task requirements of the operator, rather than being arbitrarily assigned. It was also indicated that there may be some interference between the alarm initiated activities and the alarm media, i.e. information that supports one particular stage of alarm handling may interfere with another.