Transformation of propositional calculus statements into integer and mixed integer programs: An approach towards automatic reformulation

A systematic procedure for transforming a set of logical statements or logical conditions imposed on a model into an Integer Linear Progamming (ILP) formulation Mixed Integer Programming (MIP) formulation is presented. An ILP stated as a system of linear constraints involving integer variables and an objective function, provides a powerful representation of decision problems through a tightly interrelated closed system of choices. It supports direct representation of logical (Boolean or prepositional calculus) expressions. Binary variables (hereafter called logical variables) are first introduced and methods of logically connecting these to other variables are then presented. Simple constraints can be combined to construct logical relationships and the methods of formulating these are discussed. A reformulation procedure which uses the extended reverse polish representation of a compound logical form is then described. These reformulation procedures are illustrated by two examples. A scheme of implementation.ithin an LP modelling system is outlined

Multiscale lattice Boltzmann approach to modeling gas flows

For multiscale gas flows, kinetic-continuum hybrid method is usually used to balance the computational accuracy and efficiency. However, the kinetic-continuum coupling is not straightforward since the coupled methods are based on different theoretical frameworks. In particular, it is not easy to recover the non-equilibrium information required by the kinetic method which is lost by the continuum model at the coupling interface. Therefore, we present a multiscale lattice Boltzmann (LB) method which deploys high-order LB models in highly rarefied flow regions and low-order ones in less rarefied regions. Since this multiscale approach is based on the same theoretical framework, the coupling precess becomes simple. The non-equilibrium information will not be lost at the interface as low-order LB models can also retain this information. The simulation results confirm that the present method can achieve model accuracy with reduced computational cost

Dynamic of a non homogeneously coarse grained system

To study materials phenomena simultaneously at various length scales, descriptions in which matter can be coarse grained to arbitrary levels, are necessary. Attempts to do this in the static regime (i.e. zero temperature) have already been developed. In this letter, we present an approach that leads to a dynamics for such coarse-grained models. This allows us to obtain temperature-dependent and transport properties. Renormalization group theory is used to create new local potentials model between nodes, within the approximation of local thermodynamical equilibrium. Assuming that these potentials give an averaged description of node dynamics, we calculate thermal and mechanical properties. If this method can be sufficiently generalized it may form the basis of a Molecular Dynamics method with time and spatial coarse-graining.Comment: 4 pages, 4 figure

In Vivo Imaging of Vesicular Monoamine Transporters in Human Brain Using [ 11 C]Tetrabenazine and Positron Emission Tomography

The pharmacokinetics of [ 11 CJtetrabenazine, a high-affinity radioligand for the monoamine vesicular transporter, were determined in living human brain using in vivo imaging by positron emission tomography (PET). The radiotracer showed high brain uptake and rapid washout from all brain regions with relatively slower clearance from regions of highest concentrations of monoamine vesicular transporters (striatum), resulting in clear differential visualization of these structures at short intervals after injection (10–20 min). As the first human PET imaging study of a vesicular neurotransmitter transporter, these experiments demonstrate that external imaging of vesicular transporters forms a new and valuable approach to the in vivo quantification of monoaminergic neurons, with potential application to the in vivo study of neurodegenerative disorders such as Parkinson's disease.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/65743/1/j.1471-4159.1993.tb03521.x.pd

Use of the socio-ecological model to explore factors that influence the implementation of a diabetes structured education programme (EXTEND project) in Lilongwe, Malawi and Maputo, Mozambique : a qualitative study

Background: Diabetes Self-Management Education and Support (DSMES) programmes are vital for type 2 diabetes mellitus (T2DM) management. However, they are limited in Sub-Saharan Africa (SSA). To address this gap, a DSMES, namedEXTEND was developed in Lilongwe (Malawi) and Maputo (Mozambique). This qualitative study aimed to explore factors that influence the implementation of DSMES in these settings. Methods: The Socio-ecological model was applied to explore factors influencing the implementation of DSMES in SSA. Data was analysed using the Framework method and constant comparative techniques. Sixty-six people participated in the study: people with T2DM who participated in the EXTEND programme; healthcare professionals (HCPs), EXTEND educators, EXTEND trainers, and stakeholders. Results: Our findings indicate that there is a need to develop an integrated and dedicated diabetes services in SSA healthcare systems, incorporating culturally adapted DSMES and tailored diabetes training to all professions involved in diabetes management. Traditional media and the involvement of community leaders were proposed as important elements to help engage and promote DSMES programmes in local communities. During the design and implementation of DSMES, it is important to consider individual and societal barriers to self-care. Conclusion: Findings from this study suggest that multi-faceted factors play a significant role to the implementation of DSMES programmes in LICs. In the future, EXTEND could be incorporated in the development of diabetes training and dedicated diabetes services in SSA healthcare systems, acting as an educational tool for both people with T2DM and HCPs. This project was supported by the Medical Research Council GCRF NCDs Foundation Awards 2016 Development Pathway Funding

Multiscale simulation of nanofluidic networks of arbitrary complexity

We present a hybrid molecular-continuum method for the simulation of general nanofluidic networks of long and narrow channels. This builds on the multiscale method of Borg et al. (Microfluid Nanofluid 15(4):541–557, 2013; J Comput Phys 233:400–413, 2013) for systems with a high aspect ratio in three main ways: (a) the method has been generalised to accurately model any nanofluidic network of connected channels, regardless of size or complexity; (b) a versatile density correction procedure enables the modelling of compressible fluids; (c) the method can be utilised as a design tool by applying mass-flow-rate boundary conditions (and then inlet/outlet pressures are the output of the simulation). The method decomposes the network into smaller components that are simulated individually using, in the cases in this paper, molecular dynamics micro-elements that are linked together by simple mass conservation and pressure continuity relations. Computational savings are primarily achieved by exploiting length-scale separation, i.e. modelling long channels as hydrodynamically equivalent shorter channel sections. In addition, these small micro-elements reach steady state much quicker than a full simulation of the network does. We test our multiscale method on several steady, isothermal network flow cases and show that it converges quickly (within three iterations) to good agreement with full molecular simulations of the same cases