Ground-State Magnetization for Interacting Fermions in a Disordered Potential : Kinetic Energy, Exchange Interaction and Off-Diagonal Fluctuations

We study a model of interacting fermions in a disordered potential, which is assumed to generate uniformly fluctuating interaction matrix elements. We show that the ground state magnetization is systematically decreased by off-diagonal fluctuations of the interaction matrix elements. This effect is neglected in the Stoner picture of itinerant ferromagnetism in which the ground-state magnetization is simply determined by the balance between ferromagnetic exchange and kinetic energy, and increasing the interaction strength always favors ferromagnetism. The physical origin of the demagnetizing effect of interaction fluctuations is the larger number of final states available for interaction-induced scattering in the lower spin sectors of the Hilbert space. We analyze the energetic role played by these fluctuations in the limits of small and large interaction $U$. In the small $U$ limit we do second-order perturbation theory and identify explicitly transitions which are allowed for minimal spin and forbidden for higher spin. These transitions then on average lower the energy of the minimal spin ground state with respect to higher spin. For large interactions $U$ we amplify on our earlier work [Ph. Jacquod and A.D. Stone, Phys. Rev. Lett. 84, 3938 (2000)] which showed that minimal spin is favored due to a larger broadening of the many-body density of states in the low-spin sectors. Numerical results are presented in both limits.Comment: 35 pages, 24 figures - final, shortened version, to appear in Physical Review

Challenges and opportunities for quantifying roots and rhizosphere interactions through imaging and image analysis

The morphology of roots and root systems influences the efficiency by which plants acquire nutrients and water, anchor themselves and provide stability to the surrounding soil. Plant genotype and the biotic and abiotic environment significantly influence root morphology, growth and ultimately crop yield. The challenge for researchers interested in phenotyping root systems is, therefore, not just to measure roots and link their phenotype to the plant genotype, but also to understand how the growth of roots is influenced by their environment. This review discusses progress in quantifying root system parameters (e.g. in terms of size, shape and dynamics) using imaging and image analysis technologies and also discusses their potential for providing a better understanding of root:soil interactions. Significant progress has been made in image acquisition techniques, however trade-offs exist between sample throughput, sample size, image resolution and information gained. All of these factors impact on downstream image analysis processes. While there have been significant advances in computation power, limitations still exist in statistical processes involved in image analysis. Utilizing and combining different imaging systems, integrating measurements and image analysis where possible, and amalgamating data will allow researchers to gain a better understanding of root:soil interactions

Category structure and the two learning systems of COVIS

An influential multi-process model of category learning, COVIS, suggests that a verbal or a procedural category learning process is adopted, depending on the nature of the learning problem. While the architectural assumptions of COVIS have been widely supported, there is still uncertainty regarding the types of category structures that are likely to engage each of the COVIS systems. We examined COVIS in an fMRI study with two novel (in terms of COVIS research) categorizations. One of the categorizations could be described by a simple, unidimensional, rule that was expected to favor the verbal system. The other categorization possessed characteristics typically associated with the procedural system, but could also potentially be verbalized using a rule more complex than the ones previously associated with the verbal system. We found that both categorizations engaged regions associated with the verbal system. Additionally, for both categorizations, frontal lobe regions (including left ventrolateral frontal cortex) were more engaged in the first compared to the second session, possibly reflecting the greater use of hypothesis–testing processes in the initial stages of category acquisition. In sum, our results extend our knowledge of the conditions under which the verbal system will operate. These findings indicate that much remains to be understood concerning the precise interplay of the verbal and procedural categorization systems

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Comparison of adult shift and non-shift workers’ physical activity and sleep behaviours: cross-sectional analysis from the Household Income and Labour Dynamics of Australia (HILDA) cohort

Aim: This study compares the pattern of physical activity and sleep between shift and non-shift workers using a novel physical activity–sleep index. By drawing from a diverse occupational population, this research aims to reduce any occupational specific biases which are prevalent in shift-work research. Subject and methods: Current data included 7607 workers (shift workers n = 832) from the Household Income and Labour Dynamics of Australia cohort study. The combined physical activity–sleep index comprised three physical activity components and three sleep health components: achieving moderate (1pt) or high (2pts) IPAQ classification; accruing ≥30% of physical activity as vigorous intensity (1pt); meeting sleep duration recommendations on a work night (1pt); and non-work night (1pt); and reporting no insomnia symptoms (1pt) (higher score = healthy behaviour, max. 6). Generalised linear modelling was used to compare behaviours of shift and non-shift workers. Results: Findings showed shift workers reported significantly lower activity–sleep scores (3.59 vs 3.73, p < 0.001), lower sleep behaviour sub-score (2.01 vs. 2.22, p < 0.001) and were more likely to report insomnia symptoms (p < 0.001) compared to non-shift workers. No difference was reported for overall physical activity (shift = 1.58 vs. non-shift = 1.51, p = 0.383). Conclusion: When viewed in conjunction using the combined activity–sleep index, shift workers displayed significantly poorer combined behaviours when compared to non-shift workers

Category structure and the two learning systems of COVIS

An influential multi-process model of category learning, COVIS, suggests that a verbal or a procedural category learning process is adopted, depending on the nature of the learning problem. While the architectural assumptions of COVIS have been widely supported, there is still uncertainty regarding the types of category structures that are likely to engage each of the COVIS systems. We examined COVIS in an fMRI study with two novel (in terms of COVIS research) categorizations. One of the categorizations could be described by a simple, unidimensional, rule that was expected to favor the verbal system. The other categorization possessed characteristics typically associated with the procedural system, but could also potentially be verbalized using a rule more complex than the ones previously associated with the verbal system. We found that both categorizations engaged regions associated with the verbal system. Additionally, for both categorizations, frontal lobe regions (including left ventrolateral frontal cortex) were more engaged in the first compared to the second session, possibly reflecting the greater use of hypothesis–testing processes in the initial stages of category acquisition. In sum, our results extend our knowledge of the conditions under which the verbal system will operate. These findings indicate that much remains to be understood concerning the precise interplay of the verbal and procedural categorization systems

A Comparison of the neural correlates that underlie rule-based and information-integration category learning

The influential Competition between Verbal and Implicit Systems (COVIS) model proposes that category learning is driven by two competing neural systems – an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based, category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The rule-based and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the rule-based and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the rule-based condition. No regions were more activated in rule-based than information-integration category learning. The implications of these results for theories of category learning are discussed.The support of a South West Doctoral Training Centre (SWDTC) Economic and Social Research Council (ESRC) Studentship Award (ES/J50015X/1) to the first author is appreciatively acknowledged. We also thank Todd Maddox for supplying the stimuli used in this study and Greg Ashby for his comments on this work. The participation of University of Exeter student volunteers is also greatly appreciated

Identification of a novel TGFB1 variant in a patient with Camurati-Engelmann disease responsive to alendronate

Whole genome sequencing and alendronate may be of value in diagnosing and managing CED, respectively