Multiple single-point imaging (mSPI) as a tool for capturing and characterizing MR signals and repetitive signal disturbances with high temporal resolution: The MRI scanner as a high-speed camera

In this paper we aim to lay down and demonstrate the use of multiple single-point imaging (mSPI) as a tool for capturing and characterizing steady-state MR signals and repetitive disturbances thereof with high temporal resolution.     

Quantification of superparamagnetic iron oxide using inversion recovery balanced steady-state free precession

Cellular and molecular MRI trafficking studies using superparamagnetic iron oxide (SPIO) have greatly improved non-invasive investigations of disease progression and drug efficacy, but thus far, these studies have largely been restricted to qualitative assessment of hypo- or hyperintense areas near SPIO. In this work, SPIO quantification using inversion recovery balanced steady-state free precession (IR-bSSFP) was demonstrated at 3 T by extracting R₂ values from a monoexponential model (P. Schmitt et al., 2004). A low flip angle was shown to reduce the apparent recovery rate of the IR-bSSFP time course, thus extending the dynamic range of quantification. However, low flip angle acquisitions preclude the use of traditional methods for combining RF phase-cycled images to reduce banding artifacts arising from off-resonance due to B₀ inhomogeneity. To achieve R₂ quantification of SPIO, we present a new algorithm applicable to low flip angle IR-bSSFP acquisitions that is specifically designed to identify on-resonance acquisitions. We demonstrate in this work, using both theoretical and empirical methods, that the smallest estimated R₂ from multiple RF phase-cycled acquisitions correspond well to the on-resonance time course. Using this novel minimum R₂ algorithm, homogeneous R₂ maps and linear R₂ calibration curves were created up to 100 μg(Fe)/mL with 20° flip angles, despite substantial B₀ inhomogeneity. In addition, we have shown this technique to be feasible for pre-clinical research: the minimum R₂ algorithm was resistant to off-resonance in a single slice mouse R₂ map, whereas maximum intensity projection resulted in banding artifacts and overestimated R₂ values. With the application of recent advances in accelerated acquisitions, IR-bSSFP has the potential to quantify SPIO in vivo, thus providing important information for oncology, immunology, and regenerative medicine MRI studies.     

Weak and strong fillability of higher dimensional contact manifolds

For contact manifolds in dimension three, the notions of weak and strong symplectic fillability and tightness are all known to be inequivalent. We extend these facts to higher dimensions: in particular, we define a natural generalization of weak fillings and prove that it is indeed weaker (at least in dimension five), while also being obstructed by all known manifestations of “overtwistedness”. We also find the first examples of contact manifolds in all dimensions that are not symplectically fillable but also cannot be called overtwisted in any reasonable sense. These depend on a higher dimensional analogue of Giroux torsion, which we define via the existence in all dimensions of exact symplectic manifolds with disconnected contact boundary.     

METAPHORS AND OTHER LINGUISTIC POINTERS TO CHILDREN'S MENTAL REPRESENTATIONS

The mental representations that 6- and 7-year-old pupils form as a result of their interactions with their teacher's verbal, written, pictorial and concrete material representations has to be inferred from the language they use. In this study many pupils seem to have mental representations which capture surface characteristics of a particular teachers’ representation and use metaphoric language associated with that representation when describing their calculations. Pupils’ use of ‘you’ is characteristic of those who adopt a representation-specific procedure, whilst ‘if’ and ‘like’ are linguistic pointers to their use of generic examples to describe a procedure. Individual pupils show a preference for the same style of mental representation when describing images and procedures in mathematical and non-mathematical contexts.     

THE INFLUENCE OF TEACHERS’ PRESENTATIONS ON PUPILS’ MENTAL REPRESENTATIONS

Teachers use a variety of external representations to communicate mathematical ideas to their pupils. This paper reports a preliminary study of the internal mental representations that 6- and 7- year-old pupils form as a result of their interactions with the teacher's verbal, written, pictorial and concrete material representations, involving two-digit numbers and operations on them. The results presented here concern the picture-like mental representations that pupils use in performing two-digit calculations mentally. The evidence suggests that pupils seldom spontaneously visualise teachers’ representations or attempt mental manipulation of visual images to help with calculation. Pupils can, however, have mental representations which reproduce some aspects of the teachers’ representations.     

Locating starting points in differential equations: a realistic mathematics education approach

The paper reports on ongoing developmental research efforts to adapt the instructional design perspective of Realistic Mathematics Education (RME) to the learning and teaching of collegiate mathematics, using differential equations as a specific case. This report focuses on the RME design heuristic of guided reinvention as a means to locate a starting point for an instructional sequence for first-order differential equations and highlights the cyclical process instructional design and analysis of student learning. The instance of starting with a rate of change equation as an experientially real mathematical context is taken as a case for illustrating how university students might experience the creation of mathematical ideas. In particular, it is shown how three students came to reason conceptually about rate and in the process, develop their own informal Euler method for approximating solution functions to differential equations.     

Integrated distribution and loading planning via a compact metaheuristic algorithm

The present article examines a vehicle routing problem integrated with two-dimensional loading constraints, called 2L-CVRP. The problem is aimed at generating the optimal route set for satisfying customer demand. In addition, feasible loading arrangements have to be determined for the transported products. To solve 2L-CVRP, we propose a metaheuristic solution approach. The basic advantage of our approach lies at its compact structure, as in total, only two parameters affect the algorithmic performance. To optimize the routing aspects, we propose a local-search method equipped with an effective diversification component based on the regional aspiration criteria. The problem’s loading requirements are tackled by employing a two-dimensional packing heuristic which repetitively attempts to develop feasible loading patterns. These attempts are effectively coordinated via an innovative, simple-structured memory mechanism. The overall solution framework makes use of several memory components for drastically reducing the computational effort required. The performance of our metaheuristic development has been successfully evaluated on benchmark instances considering two distinct versions of the loading constraints. More specifically, the algorithm managed to improve or match the majority of best known solution scores for both problem versions.     

Covariance Decompositions for Accurate Computation in Bayesian Scale-Usage Models

Analyses of multivariate ordinal probit models typically use data augmentation to link the observed (discrete) data to latent (continuous) data via a censoring mechanism defined by a collection of “cutpoints.” Most standard models, for which effective Markov chain Monte Carlo (MCMC) sampling algorithms have been developed, use a separate (and independent) set of cutpoints for each element of the multivariate response. Motivated by the analysis of ratings data, we describe a particular class of multivariate ordinal probit models where it is desirable to use a common set of cutpoints. While this approach is attractive from a data-analytic perspective, we show that the existing efficient MCMC algorithms can no longer be accurately applied. Moreover, we show that attempts to implement these algorithms by numerically approximating required multivariate normal integrals over high-dimensional rectangular regions can result in severely degraded estimates of the posterior distribution. We propose a new data augmentation that is based on a covariance decomposition and that admits a simple and accurate MCMC algorithm. Our data augmentation requires only that univariate normal integrals be evaluated, which can be done quickly and with high accuracy. We provide theoretical results that suggest optimal decompositions within this class of data augmentations, and, based on the theory, recommend default decompositions that we demonstrate work well in practice. This article has supplementary material online.     

Comparative study of microscopic charge dynamics in crystalline acceptor-substituted oligothiophenes

By performing microscopic charge transport simulations for a set of crystalline dicyanovinyl-substituted oligothiophenes, we find that the internal acceptor-donor-acceptor molecular architecture combined with thermal fluctuations of dihedral angles results in large variations of local electric fields, substantial energetic disorder, and pronounced Poole-Frenkel behavior, which is unexpected for crystalline compounds. We show that the presence of static molecular dipoles causes large energetic disorder, which is mostly reduced not by compensation of dipole moments in a unit cell but by molecular polarizabilities. In addition, the presence of a well-defined π-stacking direction with strong electronic couplings and short intermolecular distances turns out to be disadvantageous for efficient charge transport since it inhibits other transport directions and is prone to charge trapping.