The Hierarchical Structure of the Firm: A Geometric Perspective

This paper incorporates hierarchical structure into the neoclassical theory of the firm. Firms are hierarchical in two respects: the organization of workers in production and the wage structure. The firm’s hierarchy is represented as the sector of a circle, where the radius represents the hierarchy’s height, the width of the sector represents the breadth of the hierarchy at a given height, and the angle of the sector represents span of control for any given supervisor. A perfectly competitive firm then chooses height and width, as well as capital inputs, in order to maximize profit. We analyze the short run and long run impact of changes in scale economies, input substitutability and input and output prices on the firm’s hierarchical structure. We find that the firm unambiguously becomes more hierarchical as the specialization of its workers increases or as its output price increases relative to input prices. The effect of changes in scale economies is contingent on the output price. The model also brings forth an analysis of wage inequality within the firm, which is found to be independent of technological considerations, and only depends on the firm’s wage schedule.

Guiding local regression using visualisation

Solving many scientific problems requires effective regression and/or classification models for large high-dimensional datasets. Experts from these problem domains (e.g. biologists, chemists, financial analysts) have insights into the domain which can be helpful in developing powerful models but they need a modelling framework that helps them to use these insights. Data visualisation is an effective technique for presenting data and requiring feedback from the experts. A single global regression model can rarely capture the full behavioural variability of a huge multi-dimensional dataset. Instead, local regression models, each focused on a separate area of input space, often work better since the behaviour of different areas may vary. Classical local models such as Mixture of Experts segment the input space automatically, which is not always effective and it also lacks involvement of the domain experts to guide a meaningful segmentation of the input space. In this paper we addresses this issue by allowing domain experts to interactively segment the input space using data visualisation. The segmentation output obtained is then further used to develop effective local regression models.

Typical performance of low-density parity-check codes over general symmetric channels

Typical performance of low-density parity-check (LDPC) codes over a general binary-input output-symmetric memoryless channel is investigated using methods of statistical mechanics. The binary-input additive-white-Gaussian-noise channel and the binary-input Laplace channel are considered as specific channel noise models.

A comparison of linear forecasting models and neural networks:an application to Euro inflation and Euro Divisia

Linear models reach their limitations in applications with nonlinearities in the data. In this paper new empirical evidence is provided on the relative Euro inflation forecasting performance of linear and non-linear models. The well established and widely used univariate ARIMA and multivariate VAR models are used as linear forecasting models whereas neural networks (NN) are used as non-linear forecasting models. It is endeavoured to keep the level of subjectivity in the NN building process to a minimum in an attempt to exploit the full potentials of the NN. It is also investigated whether the historically poor performance of the theoretically superior measure of the monetary services flow, Divisia, relative to the traditional Simple Sum measure could be attributed to a certain extent to the evaluation of these indices within a linear framework. Results obtained suggest that non-linear models provide better within-sample and out-of-sample forecasts and linear models are simply a subset of them. The Divisia index also outperforms the Simple Sum index when evaluated in a non-linear framework. © 2005 Taylor & Francis Group Ltd.

Foreign direct investment, transactions linkages, and the performance of the domestic sector

Using data from the UK Census of Production, including foreign ownership data, and information from UK industry input-output tables, this paper examines whether the intensity of transactions linkages between foreign and domestic firms affects productivity growth in domestic manufacturing industries. The implications of the findings for policies promoting linkages between multinational and domestic firms in the UK economy are outlined.

Three-factor models versus time series models:quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant.

Comparing different approach and avoidance models of learning and personality in the prediction of work, university, and leadership outcomes

Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N=137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.

Feasibility studies of an on-line identification technique

This thesis is concerned with the study of a non-sequential identification technique, so that it may be applied to the identification of process plant mathematical models from process measurements with the greatest degree of accuracy and reliability. In order to study the accuracy of the technique under differing conditions, simple mathematical models were set up on a parallel hybrid. computer and these models identified from input/output measurements by a small on-line digital computer. Initially, the simulated models were identified on-line. However, this method of operation was found not suitable for a thorough study of the technique due to equipment limitations. Further analysis was carried out in a large off-line computer using data generated by the small on-line computer. Hence identification was not strictly on-line. Results of the work have shovm that the identification technique may be successfully applied in practice. An optimum sampling period is suggested, together with noise level limitations for maximum accuracy. A description of a double-effect evaporator is included in this thesis. It is proposed that the next stage in the work will be the identification of a mathematical model of this evaporator using the teclmique described.

Length, lexicality, and articulatory suppression in immediate recall:evidence against the articulatory loop

Influential models of short-term memory have attributed the fact that short words are recalled better than longer words in serial recall (the length effect) to articulatory rehearsal. Crucial for this link is the finding that the length effect disappears under articulatory suppression. We show, instead, that, under suppression, the length effect is abolished or reversed for real words but remains robust for nonwords. The latter finding is demonstrated in a variety of conditions: with lists of three and four nonwords, with nonwords drawn from closed and open sets, with spoken and written presentation, and with written and spoken output. Our interpretation is that the standard length effect derives from the number of phonological units to be retained. The length effect is abolished or reversed under suppression because this condition encourages reliance on lexical-semantic representations. Using these representations, longer words can more easily be reconstructed from degraded phonology than shorter words. © 2005 Elsevier Inc. All rights reserved.

Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems

The kinematic mapping of a rigid open-link manipulator is a homomorphism between Lie groups. The homomorphisrn has solution groups that act on an inverse kinematic solution element. A canonical representation of solution group operators that act on a solution element of three and seven degree-of-freedom (do!) dextrous manipulators is determined by geometric analysis. Seven canonical solution groups are determined for the seven do! Robotics Research K-1207 and Hollerbach arms. The solution element of a dextrous manipulator is a collection of trivial fibre bundles with solution fibres homotopic to the Torus. If fibre solutions are parameterised by a scalar, a direct inverse funct.ion that maps the scalar and Cartesian base space coordinates to solution element fibre coordinates may be defined. A direct inverse pararneterisation of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators generates cyclical solutions. The solution representation is proposed as a model of inverse kinematic transformations in primate nervous systems. Simultaneous calibration of a composition of stereo-camera and manipulator kinematic models is under-determined by equi-output parameter groups in the composition of stereo-camera and Denavit Hartenberg (DH) rnodels. An error measure for simultaneous calibration of a composition of models is derived and parameter subsets with no equi-output groups are determined by numerical experiments to simultaneously calibrate the composition of homogeneous or pan-tilt stereo-camera with DH models. For acceleration of exact Newton second-order re-calibration of DH parameters after a sequential calibration of stereo-camera and DH parameters, an optimal numerical evaluation of DH matrix first order and second order error derivatives with respect to a re-calibration error function is derived, implemented and tested. A distributed object environment for point and click image-based tele-command of manipulators and stereo-cameras is specified and implemented that supports rapid prototyping of numerical experiments in distributed system control. The environment is validated by a hierarchical k-fold cross validated calibration to Cartesian space of a radial basis function regression correction of an affine stereo model. Basic design and performance requirements are defined for scalable virtual micro-kernels that broker inter-Java-virtual-machine remote method invocations between components of secure manageable fault-tolerant open distributed agile Total Quality Managed ISO 9000+ conformant Just in Time manufacturing systems.

Expert systems for fault tree synthesis

Hazard and operability (HAZOP) studies on chemical process plants are very time consuming, and often tedious, tasks. The requirement for HAZOP studies is that a team of experts systematically analyse every conceivable process deviation, identifying possible causes and any hazards that may result. The systematic nature of the task, and the fact that some team members may be unoccupied for much of the time, can lead to tedium, which in turn may lead to serious errors or omissions. An aid to HAZOP are fault trees, which present the system failure logic graphically such that the study team can readily assimilate their findings. Fault trees are also useful to the identification of design weaknesses, and may additionally be used to estimate the likelihood of hazardous events occurring. The one drawback of fault trees is that they are difficult to generate by hand. This is because of the sheer size and complexity of modern process plants. The work in this thesis proposed a computer-based method to aid the development of fault trees for chemical process plants. The aim is to produce concise, structured fault trees that are easy for analysts to understand. Standard plant input-output equation models for major process units are modified such that they include ancillary units and pipework. This results in a reduction in the nodes required to represent a plant. Control loops and protective systems are modelled as operators which act on process variables. This modelling maintains the functionality of loops, making fault tree generation easier and improving the structure of the fault trees produced. A method, called event ordering, is proposed which allows the magnitude of deviations of controlled or measured variables to be defined in terms of the control loops and protective systems with which they are associated.

Investigations of the site and mechanisms of drug-induced reductions in the reabsorption of divalent cations by the kidney

Disturbances in electrolyte homeostasis are a frequent adverse side-effect of the administration of aminoglycoside antibiotics such as gentamicin, and the antineoplastic agent cis-platinum. The aims of this work were to further elucidate the site(s) and mechanism(s) by which these drugs may produce disturbances in the renal reabsorption of calcium and magnesium. These investigations were undertaken using a range of in vivo and in vitro techniques and models. Initially, a series of in vivo studies was conducted to delineate aspects of the acute and chronic effects of both drugs on renal electrolyte handling and to select and evaluate an appropriate animal model: subsequent investigations were focused on gentamicin. In a study of the acute and chronic effects of cis-platinum administration, there were pronounced acute changes in a variety of indices of nephrotoxic injury, including electrolyte excretion. Most effects resolved but there were chronic increases in the urinary excretion of calcium and magnesium. The renal response of three strains of rat (Fischer 344, Sprague-Dawley (SD), and Wistar) to a ranges of doses of gentamicin was also investigated. Drug administration produced substantially different responses between strains, in particular marked differences in calcium and magnesium excretion. The results suggested that the SD rat was an appropriately sensitive strain for use in further investigations. Acute infusion of gentamicin in the anaesthetised SD rat produced rapid, substantial increases in the fractional excretion of calcium and magnesium, while sodium and potassium output were unaffected, confirming previous results of similar experiments using F344 rats. Studies using lithium clearance measurements in the anaesthetised SD rat were undertaken to investigate the effects of gentamicin on proximal tubular calcium reabsorption. Lithium clearance was unaffected by acute gentamicin infusion, suggesting that the site of acute gentamicin-induced hypercalciuria may not be located in the proximal tubule. Inhibition of Ca2+ ATPase activity was investigated as a potential mechanism by which calcium reabsorption could be affected after aminoglycoside administration. In vitro, both Ca2+ ATPase and Na+/K+ ATPase activity could be similarly inhibited by the presence of aminoglycosides, in a dose-related manner. Whilst inhibition of Na+/K+ ATPase could be demonstrated biochemically after in vivo administration of gentamicin, there were no concurrent effects on Ca2+ ATPase activity, suggesting that inhibition of Ca2+ ATPase activity is unlikely to be a primary mechanism of aminoglycoside-induced reductions of calcium reabsorption. Histochemical studies could not discern inhibition of either Na+/K+ ATPase or Ca2+ ATPase activity after in vivo administration of gentamicin. Selection of renal cell lines for further investigative in vitro studies on the mechanisms of altered cation reabsorption was considered using MTT (3-(4,5,-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide) and Neutral Red cytotoxicity assays. The ability of LLC-PK1 and LLC-RK1 cell lines to correctly rank a series of nephrotoxic compounds with their known nephrotoxic potency in vivo was studied. Using these cell lines grown on semi-permeable inserts, alterations in the paracellular transport of 45Ca was investigated as a possible mechanism by which gentamicin could alter calcium reabsorption in vivo. Short term exposure (I h) of LLC-RK1 cells to gentamicin, via both cell surfaces, resulted in a reduction in paracellular permeability to both transepithelial 3H-mannitol and 45Ca fluxes. When LLC-RK1 cells were exposed via the apical surface only, similar dose-related reductions were seen to those observed when cells were exposed to the drug from both sides. Short-term basal exposure to gentamicin appeared to contribute less to the observed reductions in 3H-mannitol and 45Ca fluxes. Experiments investigating transepithelial movement of 45Ca and 3H-mannitol on LLC-PK1 cells after acute gentamicin exposure were inconclusive. Longer exposure (48 h) to gentamicin caused an increase in the permeability of the monolayer and a consequent increase in transepithelial 45Ca flux in the LLC-RK1 cell line; increases in permeability of LLC-PK1 cells to 45Ca and 3H-mannitol were not apparent under the same conditions. The site and mechanism at which gentamicin, in particular, alters calcium reabsorption cannot be definitively described from these studies. However, indirect evidence from lithium clearance studies suggests that the site of the lesion is unlikely to be located in the proximal tubule. The mechanism by which gentamicin exposure alters calcium reabsorption may be by reducing paracellular permeability to calcium rather than by altering active calcium transport processes.

Exploiting uncertainty in nonlinear stochastic control problem

This work introduces 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. Convergence of the output error for the proposed control method is verified by using a Lyapunov function. Several simulation examples are provided to demonstrate the efficiency of the developed control method. The manner in which such a method is extended to nonlinear multi-variable systems with different delays between the input-output pairs is considered and demonstrated through simulation examples.