Spike avalanches exhibit universal dynamics across the sleep-wake cycle.

BACKGROUND: Scale-invariant neuronal avalanches have been observed in cell cultures and slices as well as anesthetized and awake brains, suggesting that the brain operates near criticality, i.e. within a narrow margin between avalanche propagation and extinction. In theory, criticality provides many desirable features for the behaving brain, optimizing computational capabilities, information transmission, sensitivity to sensory stimuli and size of memory repertoires. However, a thorough characterization of neuronal avalanches in freely-behaving (FB) animals is still missing, thus raising doubts about their relevance for brain function. METHODOLOGY/PRINCIPAL FINDINGS: To address this issue, we employed chronically implanted multielectrode arrays (MEA) to record avalanches of action potentials (spikes) from the cerebral cortex and hippocampus of 14 rats, as they spontaneously traversed the wake-sleep cycle, explored novel objects or were subjected to anesthesia (AN). We then modeled spike avalanches to evaluate the impact of sparse MEA sampling on their statistics. We found that the size distribution of spike avalanches are well fit by lognormal distributions in FB animals, and by truncated power laws in the AN group. FB data surrogation markedly decreases the tail of the distribution, i.e. spike shuffling destroys the largest avalanches. The FB data are also characterized by multiple key features compatible with criticality in the temporal domain, such as 1/f spectra and long-term correlations as measured by detrended fluctuation analysis. These signatures are very stable across waking, slow-wave sleep and rapid-eye-movement sleep, but collapse during anesthesia. Likewise, waiting time distributions obey a single scaling function during all natural behavioral states, but not during anesthesia. Results are equivalent for neuronal ensembles recorded from visual and tactile areas of the cerebral cortex, as well as the hippocampus. CONCLUSIONS/SIGNIFICANCE: Altogether, the data provide a comprehensive link between behavior and brain criticality, revealing a unique scale-invariant regime of spike avalanches across all major behaviors.

All This the World Well Knows: a symphonic cantata in Sonnets and Proverbs for mixed chorus, four solo voices, and orchestra

All This the World Well Knows is a 30-minute symphonic cantata for mixed chorus, four solo voices (soprano, mezzo-soprano, tenor, and baritone), and orchestra. The libretto, adapted by the composer, weaves together texts from Shakespeare's Dark Lady sonnets and from the King James Bible's book of Proverbs in a loose narrative of love, betrayal, and reconciliation. The composition's pitch material includes microtonality that arises from the just intonation of sonorities derived from the harmonic series. In passages in which the solo voices express this microtonality, they are amplified in order to allow precise, non vibrato intonation. The modest size of the orchestra, which includes pairs of winds and only two percussionists, makes the composition practical for a wide range of performing groups.

Selecting renal replacement therapies: what do African American and non-African American patients and their families think others should know? A mixed methods study.

BACKGROUND: Little is known regarding the types of information African American and non-African American patients with chronic kidney disease (CKD) and their families need to inform renal replacement therapy (RRT) decisions. METHODS: In 20 structured group interviews, we elicited views of African American and non-African American patients with CKD and their families about factors that should be addressed in educational materials informing patients' RRT selection decisions. We asked participants to select factors from a list and obtained their open-ended feedback. RESULTS: Ten groups of patients (5 African American, 5 non-African American; total 68 individuals) and ten groups of family members (5 African American, 5 non-African American; total 62 individuals) participated. Patients and families had a range (none to extensive) of experiences with various RRTs. Patients identified morbidity or mortality, autonomy, treatment delivery, and symptoms as important factors to address. Family members identified similar factors but also cited the effects of RRT decisions on patients' psychological well-being and finances. Views of African American and non-African American participants were largely similar. CONCLUSIONS: Educational resources addressing the influence of RRT selection on patients' morbidity and mortality, autonomy, treatment delivery, and symptoms could help patients and their families select RRT options closely aligned with their values. Including information about the influence of RRT selection on patients' personal relationships and finances could enhance resources' cultural relevance for African Americans.

Bayesian Gaussian Copula Factor Models for Mixed Data.

Gaussian factor models have proven widely useful for parsimoniously characterizing dependence in multivariate data. There is a rich literature on their extension to mixed categorical and continuous variables, using latent Gaussian variables or through generalized latent trait models acommodating measurements in the exponential family. However, when generalizing to non-Gaussian measured variables the latent variables typically influence both the dependence structure and the form of the marginal distributions, complicating interpretation and introducing artifacts. To address this problem we propose a novel class of Bayesian Gaussian copula factor models which decouple the latent factors from the marginal distributions. A semiparametric specification for the marginals based on the extended rank likelihood yields straightforward implementation and substantial computational gains. We provide new theoretical and empirical justifications for using this likelihood in Bayesian inference. We propose new default priors for the factor loadings and develop efficient parameter-expanded Gibbs sampling for posterior computation. The methods are evaluated through simulations and applied to a dataset in political science. The models in this paper are implemented in the R package bfa.

Lognormal and gamma mixed negative binomial regression

In regression analysis of counts, a lack of simple and efficient algorithms for posterior computation has made Bayesian approaches appear unattractive and thus underdeveloped. We propose a lognormal and gamma mixed negative binomial (NB) regression model for counts, and present efficient closed-form Bayesian inference; unlike conventional Poisson models, the proposed approach has two free parameters to include two different kinds of random effects, and allows the incorporation of prior information, such as sparsity in the regression coefficients. By placing a gamma distribution prior on the NB dispersion parameter r, and connecting a log-normal distribution prior with the logit of the NB probability parameter p, efficient Gibbs sampling and variational Bayes inference are both developed. The closed-form updates are obtained by exploiting conditional conjugacy via both a compound Poisson representation and a Polya-Gamma distribution based data augmentation approach. The proposed Bayesian inference can be implemented routinely, while being easily generalizable to more complex settings involving multivariate dependence structures. The algorithms are illustrated using real examples. Copyright 2012 by the author(s)/owner(s).

Health coaching for glaucoma care: a pilot study using mixed methods.

INTRODUCTION: Adherence to glaucoma medications is essential for successful treatment of the disease but is complex and difficult for many of our patients. Health coaching has been used successfully in the treatment of other chronic diseases. This pilot study explores the use of health coaching for glaucoma care. METHODS: A mixed methods study design was used to assess the health coaching intervention for glaucoma patients. The health coaching intervention consisted of four to six health coaching sessions with a certified health coach via telephone. Quantitative measures included demographic and health information, adherence to glaucoma medications (using the visual analog adherence scale and medication event monitoring system), and an exit survey rating the experience. Qualitative measures included a precoaching health questionnaire, notes made by the coach during the intervention, and an exit interview with the subjects at the end of the study. RESULTS: Four glaucoma patients participated in the study; all derived benefits from the health coaching. Study subjects demonstrated increased glaucoma drop adherence in response to the coaching intervention, in both visual analog scale and medication event monitoring system. Study subjects' qualitative feedback reflected a perceived improvement in both eye and general health self-care. The subjects stated that they would recommend health coaching to friends or family members. CONCLUSION: Health coaching was helpful to the glaucoma patients in this study; it has the potential to improve glaucoma care and overall health.

Neurology and psychiatry: waking up to opportunities of sleep. State of the art and clinical/research priorities for the next decade.

In recent years, evidence has emerged for a bidirectional relationship between sleep and neurological and psychiatric disorders. First, sleep-wake disorders (SWDs) are very common and may be the first/main manifestation of underlying neurological and psychiatric disorders. Secondly, SWDs may represent an independent risk factor for neuropsychiatric morbidities. Thirdly, sleep-wake function (SWF) may influence the course and outcome of neurological and psychiatric disorders. This review summarizes the most important research and clinical findings in the fields of neuropsychiatric sleep and circadian research and medicine, and discusses the promise they bear for the next decade. The findings herein summarize discussions conducted in a workshop with 26 European experts in these fields, and formulate specific future priorities for clinical practice and translational research. More generally, the conclusion emerging from this workshop is the recognition of a tremendous opportunity offered by our knowledge of SWF and SWDs that has unfortunately not yet entered as an important key factor in clinical practice, particularly in Europe. Strengthening pre-graduate and postgraduate teaching, creating academic multidisciplinary sleep-wake centres and simplifying diagnostic approaches of SWDs coupled with targeted treatment strategies yield enormous clinical benefits for these diseases.

Revisiting the carrier-phase source-term formulation in mixed Lagrangian-Eulerian particle models

The formulation of the carrier-phase momentum and enthalpy source terms in mixed Lagrangian-Eulerian models of particle-laden flows is frequently reported inaccurately. Under certain circumstances, this can lead to erroneous implementations, which violate physical laws. A particle- rather than carrier-based approach is suggested for a consistent treatment of these terms.

Hydrocarbon field size distributions: a case study in mixed integer nonlinear programming

Of key importance to oil and gas companies is the size distribution of fields in the areas that they are drilling. Recent arguments suggest that there are many more fields yet to be discovered in mature provinces than had previously been thought because the underlying distribution is monotonic not peaked. According to this view the peaked nature of the distribution for discovered fields reflects not the underlying distribution but the effect of economic truncation. This paper contributes to the discussion by analysing up-to-date exploration and discovery data for two mature provinces using the discovery-process model, based on sampling without replacement and implicitly including economic truncation effects. The maximum likelihood estimation involved generates a high-dimensional mixed-integer nonlinear optimization problem. A highly efficient solution strategy is tested, exploiting the separable structure and handling the integer constraints by treating the problem as a masked allocation problem in dynamic programming.

Complexity of mixed shop scheduling problems: A survey

We survey recent results on the computational complexity of mixed shop scheduling problems. In a mixed shop, some jobs have fixed machine orders (as in the job shop), while the operations of the other jobs may be processed in arbitrary order (as in the open shop). The main attention is devoted to establishing the boundary between polynomially solvable and NP-hard problems. When the number of operations per job is unlimited, we focus on problems with a fixed number of jobs.

A mixed Eulerian-Lagrangian approach for metal extrusion

In this paper a mixed Eulerian-Lagrangian approach for the modelling metal extrusion processes is presented. The approach involves the solution of non-Newtonian fluid flow equations in an Eulerian context, using a free-surface algorithm to track the behaviour of the workpiece and its extrusion. The solid mechanics equations associated with the tools are solved in Lagangrian context. Thermal interactions between the workpiece are modelled and a fluid-structure interaction technique is employed to model the effect of the fluid traction load imposed by the workpiece on the tools. Two extrusion test cases are investigated and the results obtained show the potential of the model with regard to representing the physics of the process and the simulation time.