Magnetoelastic coupling in triangular lattice antiferromagnet CuCrS2

CuCrS2 is a triangular lattice Heisenberg antiferromagnet with a rhombohedral crystal structure. We report on neutron and synchrotron powder diffraction results which reveal a monoclinic lattice distortion at the magnetic transition and verify a magnetoelastic coupling. CuCrS2 is therefore an interesting material to study the influence of magnetism on the relief of geometrical frustration.Comment: 6 pages, 6 figures, 1 tabl

The Effect of AICAR-Induced AMPK Activation on Gene Expression in Sarcopenic Muscle

The loss of muscle mass and function (sarcopenia) afflicts 11-74% of all aging adults, with prevalence increasing with age. Exercise training is clearly effective in preventing or attenuating sarcopenia. The cellular mechanisms of exercise’s protective effects are not entirely clear, but AMP-activated protein kinase (AMPK) is thought to play an important role, in part by regulating gene expression. PURPOSE: To determine the effect of chronic pharmacological AMPK activation on skeletal muscle gene expression in sarcopenic muscle. METHODS: 24-month-old C57Bl/6J mice received either one acute injection or chronic daily saline injections of the AMPK-activating drug AICAR for 31 days. 5-month-old saline-injected mice served as young controls for reference. Treadmill running capacity was measured before and after treatment. Expression of genes relating to mitochondria, muscle size regulation, and inflammation was measured by real-time polymerase chain reaction (RT-PCR). RESULTS: One hour after a single injection of AICAR, raptor phosphorylation was increased in both young and old mice, indicating AMPK activation. Phosphorylation of the mTORC1 targets 4EBP1, and S6k were both elevated in old muscle, consistent with previous reports of hyperactivated mTORC1 in aged muscle. Acute AICAR injection returned 4EBP1 and S6k phosphorylation to young levels. RNA sequencing demonstrated that chronic AICAR injections restored the expression of many genes in old muscle to the levels observed in young muscle. Among these, mitochondrial splicing suppressor 51 (Mss51) expression, which is associated with impaired mitochondrial function and muscle loss, was elevated in sarcopenic muscle but attenuated by AICAR treatment, and this was confirmed by RT-PCR analysis. CONCLUSION: AICAR treatment reverses several critical age-related changes in gene expression and mTORC1 activity. Our findings support further investigation of AMPK activation and Mss51 repression as targets for therapeutic interventions in sarcopenia

SISS-MCO:large scale sparsity-induced spot selection for fast and fully-automated robust multi-criteria optimisation of proton plans

Objective. Intensity modulated proton therapy (IMPT) is an emerging treatment modality for cancer. However, treatment planning for IMPT is labour-intensive and time-consuming. We have developed a novel approach for multi-criteria optimisation (MCO) of robust IMPT plans (SISS-MCO) that is fully automated and fast, and we compare it for head and neck, cervix, and prostate tumours to a previously published method for automated robust MCO (IPBR-MCO, van de Water 2013). Approach. In both auto-planning approaches, the applied automated MCO of spot weights was performed with wish-list driven prioritised optimisation (Breedveld 2012). In SISS-MCO, spot weight MCO was applied once for every patient after sparsity-induced spot selection (SISS) for pre-selection of the most relevant spots from a large input set of candidate spots. IPBR-MCO had several iterations of spot re-sampling, each followed by MCO of the weights of the current spots. Main results. Compared to the published IPBR-MCO, the novel SISS-MCO resulted in similar or slightly superior plan quality. Optimisation times were reduced by a factor of 6 i.e. from 287 to 47 min. Numbers of spots and energy layers in the final plans were similar. Significance. The novel SISS-MCO automatically generated high-quality robust IMPT plans. Compared to a published algorithm for automated robust IMPT planning, optimisation times were reduced on average by a factor of 6. Moreover, SISS-MCO is a large scale approach; this enables optimisation of more complex wish-lists, and novel research opportunities in proton therapy.</p

SISS-MCO:large scale sparsity-induced spot selection for fast and fully-automated robust multi-criteria optimisation of proton plans

Objective. Intensity modulated proton therapy (IMPT) is an emerging treatment modality for cancer. However, treatment planning for IMPT is labour-intensive and time-consuming. We have developed a novel approach for multi-criteria optimisation (MCO) of robust IMPT plans (SISS-MCO) that is fully automated and fast, and we compare it for head and neck, cervix, and prostate tumours to a previously published method for automated robust MCO (IPBR-MCO, van de Water 2013). Approach. In both auto-planning approaches, the applied automated MCO of spot weights was performed with wish-list driven prioritised optimisation (Breedveld 2012). In SISS-MCO, spot weight MCO was applied once for every patient after sparsity-induced spot selection (SISS) for pre-selection of the most relevant spots from a large input set of candidate spots. IPBR-MCO had several iterations of spot re-sampling, each followed by MCO of the weights of the current spots. Main results. Compared to the published IPBR-MCO, the novel SISS-MCO resulted in similar or slightly superior plan quality. Optimisation times were reduced by a factor of 6 i.e. from 287 to 47 min. Numbers of spots and energy layers in the final plans were similar. Significance. The novel SISS-MCO automatically generated high-quality robust IMPT plans. Compared to a published algorithm for automated robust IMPT planning, optimisation times were reduced on average by a factor of 6. Moreover, SISS-MCO is a large scale approach; this enables optimisation of more complex wish-lists, and novel research opportunities in proton therapy.</p

Statistical Inference in a Directed Network Model with Covariates

Networks are often characterized by node heterogeneity for which nodes exhibit different degrees of interaction and link homophily for which nodes sharing common features tend to associate with each other. In this paper, we propose a new directed network model to capture the former via node-specific parametrization and the latter by incorporating covariates. In particular, this model quantifies the extent of heterogeneity in terms of outgoingness and incomingness of each node by different parameters, thus allowing the number of heterogeneity parameters to be twice the number of nodes. We study the maximum likelihood estimation of the model and establish the uniform consistency and asymptotic normality of the resulting estimators. Numerical studies demonstrate our theoretical findings and a data analysis confirms the usefulness of our model.Comment: 29 pages. minor revisio

Muscle strength, gait, and balance in 20 patients with hip osteoarthritis followed for 2 years after THA

Background Patients with hip osteoarthritis (OA) have muscular weakness, impaired balance, and limp. Deficits in the different limb muscles and their recovery courses are largely unknown, however. We hypothesized that there is persisting muscular weakness in lower limb muscles and an impaired balance and gait 2 years after THA

Choosing Meteorological Input for the Global Modeling Initiative Assessment of High Speed Aircraft

The Global Modeling Initiative (GMI) science team is developing a three dimensional chemistry and transport model (CTM) to be used in assessment of the atmospheric effects of aviation. Requirements are that this model be documented, be validated against observations, use a realistic atmospheric circulation, and contain numerical transport and photochemical modules representing atmospheric processes. The model must also retain computational efficiency to be tractable to use for multiple scenarios and sensitivity studies. To meet these requirements, a facility model concept was developed in which the different components of the CTM are evaluated separately. The first use of the GMI model will be to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. The assessment calculations will depend strongly on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere are available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS DAS), and the Goddard Institute for Space Studies general circulation model (GISS). Objective criteria were established by the GMI team to identify the data set which provides the best representation of the stratosphere. Simulations of gases with simple chemical control were chosen to test various aspects of model transport. The three meteorological data sets were evaluated and graded based on their ability to simulate these aspects of stratospheric measurements. This paper describes the criteria used in grading the meteorological fields. The meteorological data set which has the highest score and therefore was selected for GMI is CCM2. This type of objective model evaluation establishes a physical basis for interpretation of differences between models and observations. Further, the method provides a quantitative basis for defining model errors, for discriminating between different models, and for ready re-evaluation of improved models. These in turn will lead to a higher level of confidence in assessment calculations

Finite-Element Discretization of Static Hamilton-Jacobi Equations Based on a Local Variational Principle

We propose a linear finite-element discretization of Dirichlet problems for static Hamilton-Jacobi equations on unstructured triangulations. The discretization is based on simplified localized Dirichlet problems that are solved by a local variational principle. It generalizes several approaches known in the literature and allows for a simple and transparent convergence theory. In this paper the resulting system of nonlinear equations is solved by an adaptive Gauss-Seidel iteration that is easily implemented and quite effective as a couple of numerical experiments show.Comment: 19 page