Electrostatic considerations affecting the calculated HOMO-LUMO gap in protein molecules.

A detailed study of energy differences between the highest occupied and lowest unoccupied molecular orbitals (HOMO-LUMO gaps) in protein systems and water clusters is presented. Recent work questioning the applicability of Kohn-Sham density-functional theory to proteins and large water clusters (E. Rudberg, J. Phys.: Condens. Mat. 2012, 24, 072202) has demonstrated vanishing HOMO-LUMO gaps for these systems, which is generally attributed to the treatment of exchange in the functional used. The present work shows that the vanishing gap is, in fact, an electrostatic artefact of the method used to prepare the system. Practical solutions for ensuring the gap is maintained when the system size is increased are demonstrated. This work has important implications for the use of large-scale density-functional theory in biomolecular systems, particularly in the simulation of photoemission, optical absorption and electronic transport, all of which depend critically on differences between energies of molecular orbitals.Comment: 13 pages, 4 figure

Remembering the past and imagining the future in autism spectrum disorder

Recent research has revealed that episodic memory (remembering past experiences) and episodic future thinking (imagining future experiences) rely on the same underlying neuro-cognitive system. Consistent with this suggestion, individuals with autism spectrum disorder (ASD) have been shown to experience difficulties in both domains. In the present study, 18 adults with ASD and 18 typical adults performed sentence completion tasks assessing the ability to generate past and future events. Contrary to previous research findings, results demonstrated that adults with ASD performed at an equivalent level to typical adults when generating both past and future events; generating a higher number of specific events when recalling past (relative to simulating future) events, and a higher number of semantic associates when simulating future (relative to recalling past) events. Results are discussed with respect to methodological factors affecting task performance in ASD including the social nature of the research, the need to verbalise memories to the experimenter, and whether or not the specific memory request is explicit

Linear-scaling quantum Monte Carlo technique with non-orthogonal localized orbitals

We have reformulated the quantum Monte Carlo (QMC) technique so that a large part of the calculation scales linearly with the number of atoms. The reformulation is related to a recent alternative proposal for achieving linear-scaling QMC, based on maximally localized Wannier orbitals (MLWO), but has the advantage of greater simplicity. The technique we propose draws on methods recently developed for linear-scaling density functional theory. We report tests of the new technique on the insulator MgO, and show that its linear-scaling performance is somewhat better than that achieved by the MLWO approach. Implications for the application of QMC to large complex systems are pointed out

Understanding the Mind or Predicting Signal-Dependent Action? Performance of Children With and Without Autism on Analogues of the False-Belief Task

To evaluate the claim that correct performance on unexpected transfer false-belief tasks specifically involves mental-state understanding, two experiments were carried out with children with autism, intellectual disabilities, and typical development. In both experiments, children were given a standard unexpected transfer false-belief task and a mental-state-free, mechanical analogue task in which participants had to predict the destination of a train based on true or false signal information. In both experiments, performance on the mechanical task was found to correlate with that on the false-belief task for all groups of children. Logistic regression showed that performance on the mechanical analogue significantly predicted performance on the false-belief task even after accounting for the effects of verbal mental age. The findings are discussed in relation to possible common mechanisms underlying correct performance on the two tasks

O(N) methods in electronic structure calculations

Linear scaling methods, or O(N) methods, have computational and memory requirements which scale linearly with the number of atoms in the system, N, in contrast to standard approaches which scale with the cube of the number of atoms. These methods, which rely on the short-ranged nature of electronic structure, will allow accurate, ab initio simulations of systems of unprecedented size. The theory behind the locality of electronic structure is described and related to physical properties of systems to be modelled, along with a survey of recent developments in real-space methods which are important for efficient use of high performance computers. The linear scaling methods proposed to date can be divided into seven different areas, and the applicability, efficiency and advantages of the methods proposed in these areas is then discussed. The applications of linear scaling methods, as well as the implementations available as computer programs, are considered. Finally, the prospects for and the challenges facing linear scaling methods are discussed.Comment: 85 pages, 15 figures, 488 references. Resubmitted to Rep. Prog. Phys (small changes

ERP Correlates of Recognition Memory in Autism Spectrum Disorder

Recognition memory in autism spectrum disorder (ASD) tends to be undiminished compared to that of typically developing (TD) individuals (Bowler et al. 2007), but it is still unknown whether memory in ASD relies on qualitatively similar or different neurophysiology. We sought to explore the neural activity underlying recognition by employing the old/new word repetition event-related potential effect. Behavioural recognition performance was comparable across both groups, and demonstrated superior recognition for low frequency over high frequency words. However, the ASD group showed a parietal rather than anterior onset (300–500 ms), and diminished right frontal old/new effects (800–1500 ms) relative to TD individuals. This study shows that undiminished recognition performance results from a pattern of differing functional neurophysiology in ASD

Second Stage String Fragmentation Model

A string model, advocated by Bowler, provides a physical and intuitive picture of heavy quark fragmentation. When supplemented by an ad hoc factor of (1-z), to suppress fragmentation near z=1, it supplies an excellent fit to the data. We extend Bowler's model by accounting for the further decay of the massive mesonic states produced by the initial string breaking. We find that each subsequent string break and cascade decay beyond the first, introduces a factor of (1-z). Furthermore we find that including a finite mass for the quarks, which pop out of the vacuum and split the string, forces the first string breaking to produce massive states requiring further decay. This sequence terminates at the second stage of fragmentation where only relatively "light" heavy meson systems are formed. Thus we naturally account for the phenomenologically required factor of (1-z). We also predict that the ratio of (primary) fragments-vector/(vector plus scalar) should be .61. Our second stage string fragmentation model provides an appealing picture of heavy quark fragmentation.Comment: 15 page