Truth in complex adaptive systems models should be based on truth by constructive verification

It is argued that the truth status of emergent properties of complex adaptive systems models should be based on an epistemology of proof by constructive verification and therefore on the ontological axioms of a non-realist logical system such as constructivism or intuitionism. ‘Emergent’ properties of complex adaptive systems (CAS) models create particular epistemological and ontological challenges. These challenges bear directly on current debates in the philosophy of mathematics and in theoretical computer science. CAS research, with its emphasis on computer simulation, is heavily reliant on models which explore the entailments of Formal Axiomatic Systems (FAS). The incompleteness results of Gödel, the incomputability results of Turing, and the Algorithmic Information Theory results of Chaitin, undermine a realist (platonic) truth model of emergent properties. These same findings support the hegemony of epistemology over ontology and point to alternative truth models such as intuitionism, constructivism and quasi-empiricism.

Numerical prediction of atmospheric blocking - A case study

One of the fundamental questions in dynamical meteorology, and one of the basic objectives of GARP, is to determine the predictability of the atmosphere. In the early planning stage and preparation for GARP a number of theoretical and numerical studies were undertaken, indicating that there existed an inherent unpredictability in the atmosphere which even with the most ideal observing system would limit useful weather forecasting to 2-3 weeks.

The effects of a soft drink tax in the UK

The majority of the UK population is either overweight or obese. Health economists, nutritionists and doctors are calling for the UK to follow the example of other European countries and introduce a tax on soft drinks as a result of the perception that high intakes contribute to diet-related disease. We use a demand model estimated with household-level data on beverage purchases in the UK to investigate the effects of a tax on soft drink consumption. The model is a Quadratic Almost Ideal Demand System, and censoring is handled by applying a double hurdle. Separate models are estimated for low, moderate and high consumers to allow for a differential impact on consumption between these groups. Applying different hypothetical tax rates, we conclude that understanding the nature of substitute/complement relationships is crucial in designing an effective policy as these relationships differ between consumers depending on their consumption level. The overall impact of a soft drink tax on calorie consumption is likely to be small.

Playing Kant at the Court of King Arthur

This article contrasts the sense in which those whom Bernard Williams called ‘political realists’ and John Rawls are committed to the idea that political philosophy has to be distinctively political. Distinguishing the realist critique of political moralism from debates over ideal and non-ideal theory, it is argued that Rawls is more realist than many realists realise, and that realists can learn more about how to make a distinctively political vision of how our life together should be organised from his theorising, although it also points to a worrying tendency among Rawlsians to reach for inappropriately moralised arguments. G. A. Cohen’s advocacy of socialism and the second season of HBO’s The Wire are used as examples to illustrate these points.

Exploring the applications of a pulsating jet hydrodynamic modulated voltammetric (HMV) system - electrochemistry of nanostructured Pt electrodes and trace analysis

The electrochemistry of nanostructured electrodes is investigated using hydrodynamic modulated voltammetry (HMV). Here a liquid crystal templating process is used to produce a platinum modified electrode with a relatively high surface area (Roughness factor, Rf = 42.4). The electroreduction of molecular oxygen at a nanostructured platinum surface is used to demonstrate the ability of HMV to discriminate between Faradaic and non-Faradaic electrode reactions. The HMV approach shows that the reduction of molecular oxygen shows considerable hysteresis correlating with the formation and stripping of oxide species at the platinum surface. Without the HMV analysis it is difficult to discern the same detail under the conditions employed. In addition the detection limit of the apparatus is explored and shown, under ideal conditions, to be of the order of 45 nmol dm(-3) employing [Fe(CN)(6)](4-) as a test species. (C) 2009 Elsevier B.V. All rights reserved.

Model selection approaches for non-linear system identification: a review

The identification of non-linear systems using only observed finite datasets has become a mature research area over the last two decades. A class of linear-in-the-parameter models with universal approximation capabilities have been intensively studied and widely used due to the availability of many linear-learning algorithms and their inherent convergence conditions. This article presents a systematic overview of basic research on model selection approaches for linear-in-the-parameter models. One of the fundamental problems in non-linear system identification is to find the minimal model with the best model generalisation performance from observational data only. The important concepts in achieving good model generalisation used in various non-linear system-identification algorithms are first reviewed, including Bayesian parameter regularisation and models selective criteria based on the cross validation and experimental design. A significant advance in machine learning has been the development of the support vector machine as a means for identifying kernel models based on the structural risk minimisation principle. The developments on the convex optimisation-based model construction algorithms including the support vector regression algorithms are outlined. Input selection algorithms and on-line system identification algorithms are also included in this review. Finally, some industrial applications of non-linear models are discussed.

Suppression of directional interference for STBC MIMO system based on beam-forming

In civil applications, many researches on MIMO technique have achieved great progress. However, we consider military applications here. Differing from civil applications, military MIMO system may face many kinds of interferences, and the interference source may even not be equipped with multiple antennas. So the military MIMO system may receive some kind of strong interference coming from certain direction. Therefore, the military MIMO system must have capability to suppress directional interference. This paper presents a scheme to suppress directional interference for STBC MIMO system based on beam-forming. Simulation result shows that the scheme is valid to suppress directional strong interference for STBC MIMO system although with some performance loss compared with the ideal case of non-interference.

Determination of the degradation kinetics of anthocyanins in a model juice system using isothermal and non-isothermal methods

The effect of temperature on the degradation of blackcurrant anthocyanins in a model juice system was determined over a temperature range of 4–140 °C. The thermal degradation of anthocyanins followed pseudo first-order kinetics. From 4–100 °C an isothermal method was used to determine the kinetic parameters. In order to mimic the temperature profile in retort systems, a non-isothermal method was applied to determine the kinetic parameters in the model juice over the temperature range 110–140 °C. The results from both isothermal and non-isothermal methods fit well together, indicating that the non-isothermal procedure is a reliable mathematical method to determine the kinetics of anthocyanin degradation. The reaction rate constant (k) increased from 0.16 (±0.01) × 10−3 to 9.954 (±0.004) h−1 at 4 and 140 °C, respectively. The temperature dependence of the rate of anthocyanin degradation was modelled by an extension of the Arrhenius equation, which showed a linear increase in the activation energy with temperature.

The system identification and control of Hammerstein system using non-uniform rational B-spline neural network and particle swarm optimization

In this paper a new system identification algorithm is introduced for Hammerstein systems based on observational input/output data. The nonlinear static function in the Hammerstein system is modelled using a non-uniform rational B-spline (NURB) neural network. The proposed system identification algorithm for this NURB network based Hammerstein system consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a model based controller are utilized to demonstrate the efficacy of the proposed approach. The controller consists of computing the inverse of the nonlinear static function approximated by NURB network, followed by a linear pole assignment controller.

Fractional order and non-linear system identification algorithms for biomedical applications

We discuss the modelling of dielectric responses of amorphous biological samples. Such samples are commonly encountered in impedance spectroscopy studies as well as in UV, IR, optical and THz transient spectroscopy experiments and in pump-probe studies. In many occasions, the samples may display quenched absorption bands. A systems identification framework may be developed to provide parsimonious representations of such responses. To achieve this, it is appropriate to augment the standard models found in the identification literature to incorporate fractional order dynamics. Extensions of models using the forward shift operator, state space models as well as their non-linear Hammerstein-Wiener counterpart models are highlighted. We also discuss the need to extend the theory of electromagnetically excited networks which can account for fractional order behaviour in the non-linear regime by incorporating nonlinear elements to account for the observed non-linearities. The proposed approach leads to the development of a range of new chemometrics tools for biomedical data analysis and classification.

TNF-alpha mediated transport of NF-kappaB to the nucleus is independent of the cytoskeleton-based transport system in non-neuronal cells

In unstimulated cells, proteins of the nuclear factor kappaB (NF-kappaB) transcription factor family are sequestered in the cytoplasm through interactions with IkappaB inhibitor proteins. Tumor necrosis factor alpha (TNF-alpha) activates the degradation of IkappaB-alpha and the nuclear import of cytoplasmic NF-kappaB. Nuclear localization of numerous cellular proteins is mediated by the ability of the cytoskeleton, usually microtubules, to direct their perinuclear accumulation. In a former study we have shown that activated NF-kappaB rapidly moves from distal processes in neurons towards the nucleus. The fast transport rate suggests the involvement of motor proteins in the transport of NF-kappaB. Here we address the question how NF-kappaB arrives at the nuclear membrane before import in non-neuronal cells, i.e., by diffusion alone or with the help of active transport mechanisms. Using confocal microscopy imaging and analysis of nuclear protein extracts, we show that NF-kappaB movement through the cytoplasm to the nucleus is independent of the cytoskeleton, in the three cell lines investigated here. Additionally we demonstrate that NF-kappaB p65 is not associated with the dynein/dynactin molecular motor complex. We propose that cells utilize two distinct mechanisms of NF-kappaB transport: (1) signaling via diffusion over short distances in non-neuronal cells and (2) transport via motor proteins that move along the cytoskeleton in neuronal processes where the distances between sites of NF-kappaB activation and nucleus can be vast.