Brain mass estimation by head circumference and body mass methods in neonatal glycaemic modelling and control

Introduction

Hyperglycaemia is a common complication of stress and prematurity in extremely low-birth-weight infants. Model-based insulin therapy protocols have the ability to safely improve glycaemic control for this group. Estimating non-insulin-mediated brain glucose uptake by the central nervous system in these models is typically done using population-based body weight models, which may not be ideal.

Method

A head circumference-based model that separately treats small-for-gestational-age (SGA) and appropriate-for-gestational-age (AGA) infants is compared to a body weight model in a retrospective analysis of 48 patients with a median birth weight of 750 g and median gestational age of 25 weeks. Estimated brain mass, model-based insulin sensitivity (S_I) profiles, and projected glycaemic control outcomes are investigated. SGA infants (5) are also analyzed as a separate cohort.

Results

Across the entire cohort, estimated brain mass deviated by a median 10% between models, with a per-patient median difference in S_I of 3.5%. For the SGA group, brain mass deviation was 42%, and per-patient S_I deviation 13.7%. In virtual trials, 87–93% of recommended insulin rates were equal or slightly reduced (Δ < 0.16 mU/h) under the head circumference method, while glycaemic control outcomes showed little change.

Conclusion

The results suggest that body weight methods are not as accurate as head circumference methods. Head circumference-based estimates may offer improved modelling accuracy and a small reduction in insulin administration, particularly for SGA infants.     

Aromatic gas oil cracking under realistic FCC conditions in a microriser reactor

A paraffinic hydrowax feed spiked with naphthalene, anthracene, and phenanthrene was cracked in a once-through microriser reactor at 575 °C and with a catalyst-to-oil (CTO) ratio of 4.8 g_cat g_oil⁻¹. The conversion by cracking reactions is limited to the paraffinic fraction of the feed and the alkyl groups associated with the benzene ring in aromatic compounds; the aromatic probes did not crack under the applied conditions, and in fact an additional amount of naphthalene was formed by complex dealkylation and hydrogen transfer reactions. The ‘uncrackabilty’ of aromatics was directly demonstrated by processing an aromatic gas oil, containing 33.3 wt% aromatics. Experiments were performed with residence times between 0.05 and 8.2 s, keeping the temperature (525 °C) and CTO ratio (5.5 g_cat g_oil⁻¹) constant. The data was interpreted with a simplified first-order five-lump kinetic model, where approximately 19 wt% of the feed was found to be uncrackable. HCO (feedstock) conversion took mainly place during the first two seconds and coke was only formed during the first 50 ms of catalyst-oil contact. Gasoline was not overcracked to gas. Approximately 50 wt% of the LCO fraction was formed during this 50 ms and did not change thereafter.     

Characterization of the reactivity of limestones with SO2 in a fluidized bed reactor

The reaction between SO₂ and calcined limestone particles has been studied in a fluidized bed combustor. Measurements of sorbent reactivity with SO₂ were made for small batches of limestone injected into the combustor. Simultaneous continuous combustion of bituminous coal provided conditions like those of a boiler for study of the sulphation reaction. A semi-empirical rate model of the CaO-SO₂ reaction has been developed. External mass transfer of SO₂, diffusion within the particles and chemical reaction are taken into account. The limestone reactivity with SO₂ is characterized by two parameters which are dependent on the temperature and sorbent particle size. A model for predicting the limestone requirements in a fluidized bed boiler has been developed. Parameters from the batch experiments are included. The predictions for sulfur retention agree with the experimental results. In addition, effects of operating conditions (gas velocity, recycle, limestone particle size) on the retention of SO₂ were simulated using the model.     

Selecting the forgetting factor in subset autoregressive modelling

Abstract. Conventional methods to determine the forgetting factors in autoregressive (AR) models are mostly based on arbitrary or personal choices. In this paper, we present two procedures which can be used to select the forgetting factor in subset AR modelling. The first procedure uses the bootstrap to determine the value of a fixed forgetting factor. The second procedure starts from this base and applies the time-recursive maximum likelihood estimation to a variable forgetting factor. In one illustration using real exchange rates, we demonstrate the effect of the forgetting factor in subset AR modelling on ex ante forecasting of non-stationary time series. In a second illustration, these two procedures are applied to time-update forecasts for a stock market index. Subset AR models not including a forgetting factor act as a set of benchmarks for assessing ex ante forecasting performance, and consistently improved forecasting performance is demonstrated for these proposed procedures.     

Analytical and numerical study of the densification of carbon/carbon composites by a film-boiling chemical vapor infiltration process

The film-boiling chemical vapor infiltration (CVI) process is a fast process developed for composite material fabrication, and especially carbon/carbon composites. In order to help define optimal conditions, a local 1D model has been developed to study the densification front which establishes itself during the processing of a carbon/carbon fibrous preform. The model features heat conduction, precursor gas diffusion, densification reactions and structural evolution of the porous medium. The effects of total mass flux, Thiele modulus, porous medium geometry on front behavior parameters such as width, velocity and residual porosity are presented as semi-analytical correlations. An existence criterion is produced, which involves a minimal heat flux. Comparison between process-scale experiments and simulation is then possible by inserting the semi-analytical results achieved in the local study of the front into a light numerical model involving the entire preform. The model has been validated with respect to previous experimental and numerical data.     

NH3-NO/NO2 SCR for diesel exhausts after treatment: mechanism and modelling of a catalytic converter

We review herein the key mechanistic and kinetic features of the reactions involved in the NH₃-NO/NO₂ SCR system investigated by dynamic reactive experiments over a V-based commercial powdered catalyst, eventually leading to the proposal of an original redox scheme which accounts for stoichiometry, selectivity and intrinsic kinetics of the global SCR process.     

Dynamic systems modelling using genetic programming

In this contribution genetic programming (GP) is used to evolve dynamic process models. An innovative feature of the GP algorithm is its ability to automatically discover the appropriate time history of model terms required to build an accurate model. Two case studies are used to compare the performance of the GP algorithm with that of filter-based neural networks (FBNNs). Although the models generated using GP have comparable prediction performance to the FBNN models, a disadvantage is that they required greater computational effort to develop. However, we show that a major benefit of the GP approach is that additional model performance criteria can be included during the model development process. The parallel nature of GP means that it can evolve a set of candidate solutions with varying levels of performance in each objective. Although any combination of model performance criteria could be used as objectives within a multi-objective GP (MOGP) framework, the correlation tests outlined by Billings and Voon (Int. J. Control 44 (1986) 235) were used in this work.     

Kinetic studies of the pyrolysis of sewage sludge by tga and comparison with fluidized beds

The pyrolysis of sewage sludge was examined by thermogravimetric analysis using different heating rates, particle sizes and final temperatures. A semi-empirical model was developed with four global consecutive/competitive reactions to volatile and solid products including also a heat balance. This model was extrapolated to isothermal reactor conditions and compared to experimental data on fluidized bed pyrolysis. Depending on the particle size and reactor temperature, about 90% of the maximum conversion in a fluidized bed takes place under external heat transfer control, the rest under kinetic control. Incomplete conversion occurs at short particle residence times, which were calculated approximately by the model.     

The imaginary planes method for the calculation of radiative heat transfer in industrial furnaces

Radiation is usually the dominant mode of heat transfer in furnace enclosures. The imaginary planes method is one of the new methods for calculating the radiative heat transfer in such systems. In this study, a general procedure was developed for its application in furnace modelling. Various case studies were carried out for a number of furnaces, and the results were compared with those of the zone method. It was found that the new method combines good accuracy with low computation time and appears to be a promising method for the determination of heat flux and temperature distributions within furnace enclosures.