A dynamic model with on-line identification for rotary sugar drying processes

A dynamic modelling methodology, which combines on-line variable estimation and parameter identification with physical laws to form an adaptive model for rotary sugar drying processes, is developed in this paper. In contrast to the conventional rate-based models using empirical transfer coefficients, the heat and mass transfer rates are estimated by using on-line measurements in the new model. Furthermore, a set of improved sectional solid transport equations with localized parameters is developed in this work to reidentified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.place the global correlation for the computation of solid retention time. Since a number of key model variables and parameters are identified on-line using measurement data, the model is able to closely track the dynamic behaviour of rotary drying processes within a broad range of operational conditions. This adaptive model is validated against experimental data obtained from a pilot-scale rotary sugar dryer. The proposed modelling methodology can be easily incorporated into nonlinear model based control schemes to form a unified modelling and control framework.

A dynamic role for HDAC7 in MEF2-mediated muscle differentiation

The overlapping expression profile of MEF2 and the class-II histone deacetylase, HDAC7, led us to investigate the functional interaction and relationship between these regulatory proteins. HDAC7 expression inhibits the activity of MEF2 (-A, -C, and -D), and in contrast MyoD and Myogenin activities are not affected. Glutathione S-transferase pulldown and immunoprecipitation demonstrate that the repression mechanism involves direct interactions between MEF2 proteins and HDAC7 and is associated with the ability of MEF2 to interact with the N-terminal 121 amino acids of HDAC7 that encode repression domain 1. The MADS domain of MEF2 mediates the direct interaction of MEF2 with HDAC7, MEF2 inhibition by HDAC7 is dependent on the N-terminal repression domain and surprisingly does not involve the C-terminal deacetylase domain. HDAC7 interacts with CtBP and other class-I and -II HDACs suggesting that silencing of MEF2 activity involves corepressor recruitment. Furthermore, we show that induction of muscle differentiation by serum withdrawal leads to the translocation of HDAC7 from the nucleus into the cytoplasm. This work demonstrates that HDAC7 regulates the function of MEF2 proteins and suggests that this class-II HDAC regulates this important transcriptional (and pathophysiological) target in heart and muscle tissue. The nucleocytoplasmic trafficking of HDAC7 and other class-II HDACs during myogenesis provides an ideal mechanism for the regulation of HDAC targets during mammalian development and differentiation.

The acquisition of movement skills: Practice enhances the dynamic stability of bimanual coordination

During bimanual movements, two relatively stable inherent patterns of coordination (in-phase and anti-phase) are displayed (e.g., Kelso, Am. J. Physiol. 246 (1984) R1000). Recent research has shown that new patterns of coordination can be learned. For example, following practice a 90 degrees out-of-phase pattern can emerge as an additional, relatively stable, state (e.g., Zanone & Kelso, J. Exp. Psychol.: Human Performance and Perception 18 (1992) 403). On this basis, it has been concluded that practice leads to the evolution and stabilisation of the newly learned pattern and that this process of learning changes the entire attractor layout of the dynamic system. A general feature of such research has been to observe the changes of the targeted pattern's stability characteristics during training at a single movement frequency. The present study was designed to examine how practice affects the maintenance of a coordinated pattern as the movement frequency is scaled. Eleven volunteers were asked to perform a bimanual forearm pronation-supination task. Time to transition onset was used as an index of the subjects' ability to maintain two symmetrically opposite coordinated patterns (target task - 90 degrees out-of-phase - transfer task - 270 degrees out-of-phase). Their ability to maintain the target task and the transfer task were examined again after five practice sessions each consisting of 15 trials of only the 90 degrees out-of-phase pattern. Concurrent performance feedback (a Lissajous figure) was available to the participants during each practice trial. A comparison of the time to transition onset showed that the target task was more stable after practice (p = 0.025). These changes were still observed one week (p = 0.05) and two months (p = 0.075) after the practice period. Changes in the stability of the transfer task were not observed until two months after practice (p = 0.025). Notably, following practice, transitions from the 90 degrees pattern were generally to the anti-phase (180 degrees) pattern, whereas, transitions from the 270 degrees pattern were to the 90 degrees pattern. These results suggest that practice does improve the stability of a 90 degrees pattern, and that such improvements are transferable to the performance of the unpractised 270 degrees pattern. In addition, the anti-phase pattern remained more stable than the practised 90 degrees pattern throughout. (C) 2001 Elsevier Science B.V. All rights reserved.

A generalised dynamic model for char particle gasification with structure evolution and peripheral fragmentation

A generalised model for the prediction of single char particle gasification dynamics, accounting for multi-component mass transfer with chemical reaction, heat transfer, as well as structure evolution and peripheral fragmentation is developed in this paper. Maxwell-Stefan analysis is uniquely applied to both micro and macropores within the framework of the dusty-gas model to account for the bidisperse nature of the char, which differs significantly from the conventional models that are based on a single pore type. The peripheral fragmentation and random-pore correlation incorporated into the model enable prediction of structure/reactivity relationships. The occurrence of chemical reaction within the boundary layer reported by Biggs and Agarwal (Chem. Eng. Sci. 52 (1997) 941) has been confirmed through an analysis of CO/CO2 product ratio obtained from model simulations. However, it is also quantitatively observed that the significance of boundary layer reaction reduces notably with the reduction of oxygen concentration in the flue gas, operational pressure and film thickness. Computations have also shown that in the presence of diffusional gradients peripheral fragmentation occurs in the early stages on the surface, after which conversion quickens significantly due to small particle size. Results of the early commencement of peripheral fragmentation at relatively low overall conversion obtained from a large number of simulations agree well with experimental observations reported by Feng and Bhatia (Energy & Fuels 14 (2000) 297). Comprehensive analysis of simulation results is carried out based on well accepted physical principles to rationalise model prediction. (C) 2001 Elsevier Science Ltd. AH rights reserved.

EphB2 and two of its ligands have dynamic protein expression patterns in the developing olfactory system

Primary olfactory neurons are located in the olfactory neuroepithelium lining the nasal cavity. Their axons converge and form glomeruli with the dendrites of second-order neurons in the olfactory bulb. The molecular basis of primary olfactory axon guidance, targeting and subsequent arborisation is largely unknown. In this study we examined the spatio-temporal expression of the Eph receptor EphB2 and its ligands, ephrin-B1 and ephrin-B2, during development of the rat primary olfactory system. Unlike in other regions of the nervous system where receptor and ligand expression patterns are usually non-overlapping, EphB2, ephrin-B1 and ephrin-B2 were all expressed by primary and second-order olfactory neurons. In the embryonic animal we found that these three proteins had distinct and different expression patterns. EphB2 was first expressed at E18.5 by the perikarya of primary olfactory neurons. In contrast, ephrin-B1 was expressed from E13.5 and was localised to the axons of these cells up to E18.5 but was then restricted to the perikarya. Ephrin-B2, however, was expressed by olfactory ensheathing cells. EphB2, ephrin-B1 and ephrin-B2 were also expressed in the prenatal olfactory bulb and were restricted to the perikarya of mitral cells. In the post-natal olfactory bulb there was a shift in the localisation of both EphB2 and ephrin-B1 to the dendritic arborisations of mitral cells. The dynamic and tightly regulated spatio-temporal expression patterns of EphB2, ephrin-B1 and ephrin-B2 by specific olfactory cell populations suggest that these molecules have the potential to regulate important developmental events in the olfactory system. (C) 2001 Elsevier Science B.V. All rights reserved.

Dynamic assessment of tongue function in children with dysarthria associated with acquired brain injury using electromagnetic articulography

The study to be presented is the first to use a new physiological device, the electromagnetic articulograph, to assess articulatory dysfunction in children with acquired brain injury. Two children with dysarthria subsequent to acquired brain injury participated in the study. One child, a female aged 12 years 9 months exhibited a mild-moderate ataxic dysarthria following traumatic head injury while the other, a male aged 13 years 10 months, demonstrated a moderate-severe flaccid-ataxic dysarthria also following traumatic head injury. The speed and accuracy of their tongue movements was assessed using the Carstens AG100 electromagnetic articulograph. Movement trajectories together with a range of quantitative kinematic parameters were estimated during performance of ten repetitions of the lingual consonants /t, s, k/ and consonant cluster /kl/ in the word initial position of single syllable words. A group of ten non-neurologically impaired children served as controls. Examination of the kinematic parameters, including movement trajectories, velocity, acceleration, deceleration, distance travelled and duration of movement, revealed differences in the speed and accuracy of the tongue movements in both children with acquired brain injury compared to those produced by the non-neurologically impaired controls. The results are discussed in relation to contemporary theories of the effects of acquired brain injury on neuromuscular function. The implications of the findings for the treatment of articulatory dysfunction in children with motor speech disorders associated with acquired brain injury are highlighted.

Advances in application of climate prediction in agriculture

Agricultural ecosystems and their associated business and government systems are diverse and varied. They range from farms, to input supply businesses, to marketing and government policy systems, among others. These systems are dynamic and responsive to fluctuations in climate. Skill in climate prediction offers considerable opportunities to managers via its potential to realise system improvements (i.e. increased food production and profit and/or reduced risks). Realising these opportunities, however, is not straightforward as the forecasting skill is imperfect and approaches to applying the existing skill to management issues have not been developed and tested extensively. While there has been much written about impacts of climate variability, there has been relatively little done in relation to applying knowledge of climate predictions to modify actions ahead of likely impacts. However, a considerable body of effort in various parts of the world is now being focused on this issue of applying climate predictions to improve agricultural systems. In this paper, we outline the basis for climate prediction, with emphasis on the El Nino-Southern Oscillation phenomenon, and catalogue experiences at field, national and global scales in applying climate predictions to agriculture. These diverse experiences are synthesised to derive general lessons about approaches to applying climate prediction in agriculture. The case studies have been selected to represent a diversity of agricultural systems and scales of operation. They also represent the on-going activities of some of the key research and development groups in this field around the world. The case studies include applications at field/farm scale to dryland cropping systems in Australia, Zimbabwe, and Argentina. This spectrum covers resource-rich and resource-poor farming with motivations ranging from profit to food security. At national and global scale we consider possible applications of climate prediction in commodity forecasting (wheat in Australia) and examine implications on global wheat trade and price associated with global consequences of climate prediction. In cataloguing these experiences we note some general lessons. Foremost is the value of an interdisciplinary systems approach in connecting disciplinary Knowledge in a manner most suited to decision-makers. This approach often includes scenario analysis based oil simulation with credible models as a key aspect of the learning process. Interaction among researchers, analysts and decision-makers is vital in the development of effective applications all of the players learn. Issues associated with balance between information demand and supply as well as appreciation of awareness limitations of decision-makers, analysts, and scientists are highlighted. It is argued that understanding and communicating decision risks is one of the keys to successful applications of climate prediction. We consider that advances of the future will be made by better connecting agricultural scientists and practitioners with the science of climate prediction. Professions involved in decision making must take a proactive role in the development of climate forecasts if the design and use of climate predictions are to reach their full potential. (C) 2001 Elsevier Science Ltd. All rights reserved.

Spatially dynamic expression of Sry in mouse genital ridges

We have studied the spatial dynamics of Sry transcription in the genital ridges of mouse embryos. We find that Sry is expressed in a dynamic wave that emanates from the central and/or anterior regions, extends subsequently to both poles, and ends in the caudal pole. This dynamism may explain the relative positioning of ovarian and testicular tissue seen in ovotestes in mice. Since direct regulatory targets of SRY ought to be expressed in a corresponding or complimentary wave, our observations pave the way for identification of target genes. Sry is expressed in internal cells but not in coelomic surface epithelial cells, indicating that its effect on proliferation of surface cells is achieved non-cell-autonomously. The cellular dynamism of Sry expression revealed in this study thus provides important insights into both the cellular and molecular mode of action of SRY, and how perturbations in Sry expression can lead to anomalies of sexual development. (C) 2001 Wiley-Liss, Inc.

Benchmarking nitrogen removal suspended-carrier biofilm systems using dynamic simulation

We are witnessing an enormous growth in biological nitrogen removal from wastewater. It presents specific challenges beyond traditional COD (carbon) removal. A possibility for optimised process design is the use of biomass-supporting media. In this paper, attached growth processes (AGP) are evaluated using dynamic simulations. The advantages of these systems that were qualitatively described elsewhere, are validated quantitatively based on a simulation benchmark for activated sludge treatment systems. This simulation benchmark is extended with a biofilm model that allows for fast and accurate simulation of the conversion of different substrates in a biofilm. The economic feasibility of this system is evaluated using the data generated with the benchmark simulations. Capital savings due to volume reduction and reduced sludge production are weighed out against increased aeration costs. In this evaluation, effluent quality is integrated as well.

A framework for extreme-event control in wastewater treatment

In this paper an approach to extreme event control in wastewater treatment plant operation by use of automatic supervisory control is discussed. The framework presented is based on the fact that different operational conditions manifest themselves as clusters in a multivariate measurement space. These clusters are identified and linked to specific and corresponding events by use of principal component analysis and fuzzy c-means clustering. A reduced system model is assigned to each type of extreme event and used to calculate appropriate local controller set points. In earlier work we have shown that this approach is applicable to wastewater treatment control using look-up tables to determine current set points. In this work we focus on the automatic determination of appropriate set points by use of steady state and dynamic predictions. The performance of a relatively simple steady-state supervisory controller is compared with that of a model predictive supervisory controller. Also, a look-up table approach is included in the comparison, as it provides a simple and robust alternative to the steady-state and model predictive controllers, The methodology is illustrated in a simulation study.

Dynamic Behavior of the Jahn-Teller distorted Cu(H2O)(6)(2+) ion in Cu2+ doped Cs-2[Zn(H2O)(6)](ZrF6)(2) and the crystal structure of the host lattice

The temperature dependence of the X- and Q-band EPR spectra of Cs-2[Zn(H2O)(6)](ZrF6)(2) containing similar to1% Cu2+ is reported. All three molecular g-values vary with temperature, and their behavior is interpreted using a model in which the potential surface of the Jahn-Teller distorted Cu(H2O)(6)(2+) ion is perturbed by an orthorhombic strain induced by interactions with the surrounding lattice. The strain parameters are significantly smaller than those reported previously for the Cu(H2O)(6)(2+) ion in similar lattices. The temperature dependence of the two higher g-values suggests that in the present compound the lattice interactions change slightly with temperature. The crystal structure of the Cs-2[Zn(H2O)(6)](ZrF6)(2) host is reported, and the geometry of the Zn(H2O)(6)(2+) ion is correlated with lattice strain parameters derived from the EPR spectrum of the guest Cu2+ complex.

Control of chaotic motion in a dual-spin spacecraft with nutational damping

Control of chaotic vibrations in a dual-spin spacecraft with an axial nutational damper is achieved using two techniques. The control methods are implemented on two realistic spacecraft parameter configurations that have been found to exhibit chaotic instability when a sinusoidally varying torque is applied to the spacecraft for a range of forcing amplitudes and frequencies. Such a torque, in practice, may arise under malfunction of the control system or from an unbalanced rotor. Chaotic instabilities arising from these torques could introduce uncertainties and irregularities into a spacecraft's attitude motion and, consequently, could have disastrous effects on its operation. The two control methods, recursive proportional feedback and continuous delayed feedback, are recently developed techniques for control of chaotic motion in dynamic systems. Each technique is outlined and the effectiveness on this model compared and contrasted. Numerical simulations are performed, and the results are studied by means of time history, phase space, Poincare map, Lyapunov characteristic exponents, and bifurcation diagrams.

Enriched behavioral prediction equation and its impact on structured learning and the dynamic calculus

This theoretical note describes an expansion of the behavioral prediction equation, in line with the greater complexity encountered in models of structured learning theory (R. B. Cattell, 1996a). This presents learning theory with a vector substitute for the simpler scalar quantities by which traditional Pavlovian-Skinnerian models have hitherto been represented. Structured learning can be demonstrated by vector changes across a range of intrapersonal psychological variables (ability, personality, motivation, and state constructs). Its use with motivational dynamic trait measures (R. B. Cattell, 1985) should reveal new theoretical possibilities for scientifically monitoring change processes (dynamic calculus model; R. B. Cattell, 1996b), such as encountered within psycho therapeutic settings (R. B. Cattell, 1987). The enhanced behavioral prediction equation suggests that static conceptualizations of personality structure such as the Big Five model are less than optimal.