A free boundary model for oxygen diffusion in a spherical medium

The goal of this article is to find a correct approximated solution using a polynomial of sixth degree for the free boundary problem corresponding to the diffusion of oxygen in a spherical medium with simultaneous absorption at a constant rate, and to show some mistakes in previously published solutions.Comment: 10 pages, 6 figures and 2 tables. Paper accepted, in press in Journal of Biological Systems (2015

The Adomian Decomposition Method for Solving a Moving Boundary Problem Arising from the Diffusion of Oxygen in Absorbing Tissue

This paper begins by giving the results obtained by the Crank-Gupta method and Gupta-Banik method for the oxygen diffusion problem in absorbing tissue, and then we propose a new resolution method for this problem by the Adomian decomposition method. An approximate analytical solution is obtained, which is demonstrated to be quite accurate by comparison with the numerical and approximate solutions obtained by Crank and Gupta. The study confirms the accuracy and efficiency of the algorithm for analytic approximate solutions of this problem

Investigating the impact of non-local parallel transport in tokamak edge plasmas

The thin region of plasma at the edge of a tokamak, as the boundary condition to the confined plasma in the core, plays an oversized role in the performance of such devices. As such, the topic of exhaust physics is central to the ongoing effort to make magnetically confined fusion a viable approach to clean energy generation. A defining feature of this edge plasma, called the scrape-off layer (SOL), is a large temperature gradient in the direction parallel to the magnetic field. Large temperature drops are probably crucial to avoid excessive heat loads to the solid components which make up the walls of the device. However, their presence means that classical transport models, which assume the plasma is at or close to local thermodynamic equilibrium (LTE) and which are used widely in SOL modelling, can lose their predictive power [1-3]. The aim of this thesis is to investigate the extent of this effect in detail by performing kinetic simulations of parallel transport in SOL plasmas, with a focus on the electrons. There is an emphasis on quantifying the modelling uncertainties that exist in classical ('fluid') approaches to SOL simulations by performing self-consistent comparisons between kinetic and fluid models. To do this, the one-dimensional SOL kinetic code SOL-KiT has been used [4]. By extending the capabilities of this code, reducing its computational expense, and developing a standalone atomic physics code (all of which are described), it has been possible to study electron kinetics in a range of conditions relevant to current and future tokamaks. A number of distinct investigations have been performed. Firstly, it has been shown that fluid models are in fact very good at capturing the transfer of energy between ions and electrons in SOL plasmas. Secondly, it is demonstrated that a kinetic treatment leads to significant differences in parallel conductive heat transport and behaviour at the wall boundary, both of which contribute to modified temperature profiles. A set of simple scaling laws for these effects has been proposed. Finally, the effect of non-LTE electrons on plasma-atomic physics has been investigated. Here, strongly enhanced reaction rates due to the form of the electron velocity distribution have been observed, but this effect is largely reversed when considered alongside the modified temperature profiles.Open Acces

92nd Annual Meeting of the Virginia Academy of Science: Proceedings

Full proceedings of the 92nd Annual Meeting of the Virginia Academy of Science, May 13-15, 2014, Virginia Commonwealth University, Richmond, Virgini

Microgravity science & applications. Program tasks and bibliography for FY 1995

This annual report includes research projects funded by the Office of Life and Microgravity Sciences and Applications, Microgravity Science and Applications Division, during FY 1994. It is a compilation of program tasks (objective, description, significance, progress, students funded under research, and bibliographic citations) for flight research and ground based research in five major scientific disciplines: benchmark science, biotechnology, combustion science, fluid physics, and materials science. Advanced technology development (ATD) program task descriptions are also included. The bibliography cites the related principle investigator (PI) publications and presentations for these program tasks in FY 1994. Three appendices include a Table of Acronyms, a Guest Investigator index and a Principle Investigator index

Accumulation of heavy metals by aquatic bryophytes in streams and rivers in northern England

A Study was made of the ecology of aquatic bryophytes and their accumulation of metals in rivers of northern England. Field surveys and experiments in the field and laboratory examined the effectiveness of bryophytes as monitors of heavy metal pollution. A survey of 105 river sites (10-m reaches) with Rhynchostegium riparioides was carried out, together with a seasonal survey of this species at seven sites, which also included data for two other species. Details of the aquatic bryophytes present, water chemistry and metal concentrations in mosses are given. The ecological ubiquity of Rhynchostegium was described using principal components analysis and discussed in relation to other macrophytes. A biometric study revealed that marked interpopulation differences in gametophytic characters were correlated with water chemistry variables (NH(_4)-N, PO(_4)-P, Cl, Na) indicative of organic pollution. Significant linear regressions were found between accumulation and aqueous concentrations of Zn, Cd, Ba and Pb. A multiple regression of these and other chonical data suggested several factors had significant effects on accumulation. Seasonal effects were largely chemical in nature, rather than a function of the plants themselves. Experiments supported several findings from the surveys. Zinc uptake proceeded more rapidly than loss and was influenced by aqueous Mg, Ca and humic acids, but not PO(_4)-P, NO(_3)-N or Si. Accumulation was greater in tips of Rhynchostegium than Amblystegium riparium or Fontinalis antipyretica. Results indicate that bryophytes are useful as monitors of pollution. Rhynchostegium in particular is recommended for its ecological ubiquity, its presence in a wide range of aqueous metals and greater accumulation. Applications of bryophytes for specific uses are outlined, with recommendations for different situations. A new model, based on slopes of accumulation, is proposed as a predictive tool

Mechanical treatment of microorganisms using ultrasound, shock and shear technology

Microorganism disruption using ultrasound treatment is the focus of this thesis. There has been aboard spectrum of theoretical and experimental work on microorganisms disruption methods undertaken in the past. However, there is a lack of fundamental understanding on the actual reason of microorganism disruption using ultrasound. The reported literature in the microorganisms and cell disruption research field indicates that shock wave and shear effects occur together in typical ultrasound processing systems and may both contribute to microorganism disruption. However the question of whether the real cause of disruption is shock and/or shear remains unanswered. To address this issue, two independent mechanical devices – a shock apparatus and a shear apparatus were developed for this study. An ultrasound apparatus operated in a batch configuration was also used for microorganism disruption. The ultrasound work includes a detailed experimental characterisation of processing conditions associated with the ultrasound treatment. The heat transfer through the ultrasound chamber and the suspension mixing during the ultrasound treatment was evaluated using theoretical and experimental approaches. It was found that one second was sufficient to have complete suspension mixing in the ultrasound chamber and 13.5% of the total ultrasound energy was lost to the surroundings as heat. Saccharomyces cerevisiae was selected as a sample microorganism in this study, and a log reduction of 4 was achieved when ultrasound treatment was used. To determine how the yeast cell wall disrupts using a shock treatment, a finite element model was developed and the simulation results showed that von Mises stress generated due to dynamic external pressure loading was concentrated at the bottom part of the cell wall of the yeast. A vertical gas gun was commissioned to apply a dynamic load on a water-filled tube. To understand the relationship between the dynamic stress and the microorganism behaviour when subjected to external pressure, a plastic bag full of yeast suspension was placed at the bottom of the tube. The result showed that the yeast disruption rate using the shock wave treatment was relatively modest when an external shock loading pressure of around 115 MPa was used. In the case of shear stress treatment, analysis of the intense turbulent flow region of the apparatus combined with the experimental results demonstrated that when the energy dissipation rate in the turbulence region is high and the eddies are smaller than the size of the cell, the likehood of yeast disruption is high. The microorganism mechanical properties combined with the calculated energy dissipation rate were used to simulate the yeast disruption efficiency using shear stress. The results showed that a maximum yeast log reduction of 4 was achieved with the shear apparatus in the absence of pressure rise. The specific energy required for yeast disruption in these three mechanical methods was evaluated and a comparison was made with two relevant conventional methods: homogenizer and Ultra High Temperature (UHT) treatments. It was found that the specific energy required to achieve a log reduction of 2.5 was 108 MJ/kg in the case of shear and around 0.905 MJ/kg in the case of ultrasound. In the case of shock treatment, the maximum log reduction achieved was 0.57 which required 0.00477 MJ/kg. Therefore, on the assumption that log reduction is proportional to the specific treatment energy, for a 1 log reduction, 0.008 MJ/kg is required for the shock treatment, 0.46 MJ/kg is required for the ultrasound treatment, and around 48 MJ/kg is required for the shear treatment. These results show that shock wave treatment requires less specific energy to achieve the same yeast log reduction as the shear or ultrasound treatment. This implies that the cause of microorganism disruption using ultrasound is shock wave energy. Additional work in the finite element simulation and shock treatment apparatus is recommended to extend this study to different microorganisms and cells

Properties and Applications of Graphene and Its Derivatives

Graphene is a two-dimensional, one-atom-thick material made entirely of carbon atoms, arranged in a honeycomb lattice. Because of its distinctive mechanical (e.g., high strength and flexibility) and electronic (great electrical and thermal conductivities) properties, graphene is an ideal candidate in myriad applications. Thus, it has just begun to be engineered in electronics, photonics, biomedicine, and polymer-based composites, to name a few. The broad family of graphene nanomaterials (including graphene nanoplatelets, graphene oxide, graphene quantum dots, and many more) go beyond and aim higher than mere single-layer (‘pristine’) graphene, and thus, their potential has sparked the current Special Issue. In it, 18 contributions (comprising 14 research articles and 4 reviews) have portrayed probably the most interesting lines as regards future and tangible uses of graphene derivatives. Ultimately, understanding the properties of the graphene family of nanomaterials is crucial for developing advanced applications to solve important challenges in critical areas such as energy and health

Efficient Methods for Exploring Chemical Space in Computational Drug Discovery

In this work novel computational methods will be developed to efficiently explore chemical space in the search for compounds with desirable properties. To improve the efficiency of exploration two methods will be used: reducing the cost of evaluating a point in chemical space, or reducing the number of points which require evaluating to find the desired compound. The first chapter of this work will introduce the topics relevant to this work, place them in the wider context of drug design and outline the theory used to generate the results presented in subsequent chapters. The first result of this thesis, discussed in chapter 2, is for the application of free energy methods to the problem of computational fluorine scanning. The application made in this work will allow for all fluorinated analogues of a compound to be tested five times faster than existing computational methods and with comparable predictive accuracy. In chapters 3 and 4 we will consider the application of numerical methods to ligand-protein binding problems in order to optimize the charge/steric parameters of the ligand and maximize binding affinity of these ligands to a given protein target. In these two optimization-based chapters we will use free energy methods to calculate gradients of the binding free energy with respect to the parameters which describe the ligand, thus allowing optimal sets of parameters to be found efficiently. In chapter 3 we search for optimized sets of charge parameters from which design ideas can be generated and tested; 73% of the design ideas were found to beneficially improve binding affinity. In chapter 4 we find optimized sets of steric parameters from which beneficial growth vectors for methyl groups can be predicted. These predictions correlate with existing free energy methods with a Spearman's rank order correlation of 0.59. The advantage of the optimization methods presented in these chapters are: 1) the methods can generate ideas for mutations which improve ligand binding free energy and 2) these methods require less computational time to explore the same volume of chemical space than existing free energy methods. Finally, chapter 5 will discuss a collaborative open source work to find new malaria therapeutics. Ligand based machine learning methods will be applied to generate and evaluate the potency of hundreds of thousands of compounds in a manner far faster than is possible with free energy methods. Based on the computational predictions, compounds are selected and evaluated experimentally with one compound tested and verified to be active with a pIC50 of 6.2 in good agreement with the computational prediction of 6.42 +- 0.75.EPSRC Centre for Doctoral Training in Computational Methods for Materials Science, grant number EP/L015552/1