The ability for muscle to repeatedly generate force is limited by fatigue. The cellular mechanisms behind muscle fatigue are complex and potentially include breakdown at many points along the excitation-contraction pathway. In this paper we construct a mathematical model of the skeletal muscle excitation-contraction pathway based on the cellular biochemical events that link excitation to contraction. The model includes descriptions of membrane voltage, calcium cycling and crossbridge dynamics and was parameterised and validated using the response characteristics of mouse skeletal muscle to a range of electrical stimuli. This model was used to uncover the complexities of skeletal muscle fatigue. We also parameterised our model to describe force kinetics in fast and slow twitch fibre types, which have a number of biochemical and biophysical differences. How these differences interact to generate different force/fatigue responses in fast- and slow- twitch fibres is not well understood and we used our modelling approach to bring new insights to this relationship.

Analysis of the experimental data from tokamaks and linear divertor simulators leads to the conclusion that plasma recombination is a crucial element of plasma detachment. Different mechanisms of plasma recombination relevant to the experimental conditions of the tokamak scrape-off layer (SOL) and divertor simulators are considered. The physics of Molecular Activated Recombination (MAR) involving vibrationally excited molecular hydrogen are discussed. Although conventional Electron–Ion Recombination (EIR) alone can strongly alter the plasma parameters, MAR impact can be substantial for both tokamak SOL plasma and divertor simulators. Investigation of the effects of EIR on the plasma flow in divertor simulators shows that due to the balances of (a) energy transport and electron cooling, and (b) the plasma flow and recombination, that EIR extinguishes the simulator plasma at an electron temperature about 0.15 eV.

Dust particulates in the size range of 10nm-100µm are found in all fusion devices. Such dust can be generated during tokamak operation due to strong plasma/material-surface interactions. Some recent experiments and theoretical estimates indicate that dust particles can provide an important source of impurities in the tokamak plasma. Moreover, dust can be a serious threat to the safety of next-step fusion devices. In this paper, recent experimental observations on dust in fusion devices are reviewed. A physical model for dust transport simulation, and a newly developed code DUSTT, are discussed. The DUSTT code incorporates both dust dynamics due to comprehensive dust-plasma interactions as well as the effects of dust heating, charging, and evaporation. The code tracks test dust particles in realistic plasma backgrounds as provided by edge-plasma transport codes. Results are presented for dust transport in current and next-step tokamaks. The effect of dust on divertor plasma profiles and core plasma contamination is examined.3

It has been known for a long time that microscopic dust appears in plasmas in fusion devices. Recently it was shown that dust can be responsible for the termination of long-discharges. Also, in ITER-scale experiments dust can pose safety problems related to its chemical activity, tritium retention and radioactive content. In particular, the presence of dust in the vacuum chamber of ITER is one of the main concerns of the ITER licensing process. Here we review recent progress in the understanding of different experimental and theoretical aspects of the physics of dust dynamics and transport in fusion plasmas and discuss the remaining issues.

A mathematical model of biological mechanisms regulating lactation is constructed. In particular, the model allows prediction of the effect of milking frequency on milk yield and mammary regression, and the interaction of nutrition and milking frequency in determining yield. Possible interactions of nutrition with milking frequency on alveolar dynamics are highlighted. The model is based upon the association of prolonged engorgement (as a consequence of milk accumulation) of active secretory alveoli with changes in gene expression that result in impairment and, ultimately, cessation of milk secretion. The emptying of alveoli at milking, following alveolar contraction induced by oxytocin, prevents this process and also allows quiescent alveoli to reactivate. Prolonged engorgement results in apoptosis of the secretory cells and, hence, regression of the mammary gland. Milk yield is linked to alveolar populations, with secretion rates being modulated by nutrition and udder fill effects. The model was used to investigate different management scenarios, and is in agreement with experimental results. The model shows that while milking frequency drives alveolar population, and therefore potential milk production, actual production varies considerably with nutrition. A significant portion of the loss associated with once-daily milking was due to udder fill rather than loss of secretory tissue. The model showed qualitative agreement with experimental data, on the acute and chronic effects of temporary once-daily milking.