Abundance and evolution of galaxy clusters in cosmological models with massive neutrino

The time evolution of the number density of galaxy clusters and their mass and temperature functions are used to constrain cosmological parameters in the spatially flat dark matter models containing a fraction of hot particles (massive neutrino) additional to cold and baryonic matter. We test the modified MDM models with cosmic gravitational waves and show that they neither pass the cluster evolution test nor reproduce the observed height of the first acoustic peak in $\Delta T/T$ spectrum, and therefore should be ruled out. The models with a non-zero cosmological constant are in better agreement with observations. We estimate the free cosmological parameters in $\Lambda$MDM with a negligible abundance of gravitational waves, and find that within the parameter ranges $h\in (0.6, 0.7)$, $n\in (0.9, 1.1)$, (i) the value of $\Omega_\Lambda$ is strongly affected by a small fraction of hot dark matter, $f_\nu\equiv\Omega_\nu /\Omega_m\in (0, 0.2)$: $0.45 <\Omega_\Lambda <0.7$ ($1\sigma$ CL), and (ii) the redshift evolution of galaxy clusters alone reveals the following explicit correlation between $\Omega_\Lambda$ and $f_\nu$: $\Omega_\Lambda +0.5f_\nu =0.65\pm 0.1$. The present accuracy of observational data allows only to bound the fraction of hot matter, $f_\nu\in (0, 0.2)$ (the number of massive neutrino species remains undelimited, $N_\nu =1, 2, 3$).Comment: 9 pages, 7 figures, submitted in A&

Autonomous nuclear waste management

Redundant and non-operational buildings at nuclear sites are decommissioned over a period of time. The process involves demolition of physical infrastructure resulting in large quantities of residual waste material. The resulting waste materials are packed into import containers to be delivered for post-processing, containing either sealed canisters or assortments of miscellaneous objects. At present post-processing does not happen within the United Kingdom. Sellafield Ltd. and National Nuclear Laboratory are developing a process for future operation so that upon an initial inspection, imported waste materials undergo two stages of post-processing before being packed into export containers, namely sort and segregate or sort and disrupt. The post-processing facility will remotely treat and export a wide range of wastes before downstream encapsulation. Certain wastes require additional treatment, such as disruption, before export to ensure suitability for long-term disposal. This article focuses on the design, development, and demonstration of a reconfigurable rational agent-based robotic system that aims to highly automate these processes removing the need for close human supervision. The proposed system is being demonstrated through a downsized, lab-based setup incorporating a small-scale robotic arm, a time-of-flight camera, and high-level rational agent-based decision making and control framework

Emergency department-based peer support for opioid use disorder: Emergent functions and forms

Emergency department (ED)-based peer support programs aimed at linking persons with opioid use disorder (OUD) to medication for addiction treatment and other recovery services are a promising approach to addressing the opioid crisis. This brief report draws on experiences from three states' experience with such programs funded by the SAMHSA Opioid State Targeted Repose (STR) grants. Core functions of such programs include: Integration of peer supports in EDs; Alerting peers of eligible patients and making the patient aware of peer services; and connecting patients with recovery services. Qualitative data were analyzed using a general inductive approach conducted in 3 steps in order to identify forms utilized to fulfill these functions. Peer integration differed in terms of peer's physical location and who hired and supervised peers. Peers often depend on ED staff to alert them to potential patients while people other than the peers often first introduce potential patients to programming. Programs generally schedule initial appointments for recovery services for patients, but some programs provide a range of other services aimed at supporting participation in recovery services. Future effectiveness evaluations of ED-based peer support programs for OUD should consistently report on forms used to fulfill core functions

GCIP water and energy budget synthesis (WEBS)

As part of the World Climate Research Program\u27s (WCRPs) Global Energy and Water-Cycle Experiment (GEWEX) Continental-scale International Project (GCIP), a preliminary water and energy budget synthesis (WEBS) was developed for the period 1996–1999 from the “best available” observations and models. Besides this summary paper, a companion CD-ROM with more extensive discussion, figures, tables, and raw data is available to the interested researcher from the GEWEX project office, the GAPP project office, or the first author. An updated online version of the CD-ROM is also available at http://ecpc.ucsd.edu/gcip/webs.htm/. Observations cannot adequately characterize or “close” budgets since too many fundamental processes are missing. Models that properly represent the many complicated atmospheric and near-surface interactions are also required. This preliminary synthesis therefore included a representative global general circulation model, regional climate model, and a macroscale hydrologic model as well as a global reanalysis and a regional analysis. By the qualitative agreement among the models and available observations, it did appear that we now qualitatively understand water and energy budgets of the Mississippi River Basin. However, there is still much quantitative uncertainty. In that regard, there did appear to be a clear advantage to using a regional analysis over a global analysis or a regional simulation over a global simulation to describe the Mississippi River Basin water and energy budgets. There also appeared to be some advantage to using a macroscale hydrologic model for at least the surface water budgets

Deterministically Driven Avalanche Models of Solar Flares

We develop and discuss the properties of a new class of lattice-based avalanche models of solar flares. These models are readily amenable to a relatively unambiguous physical interpretation in terms of slow twisting of a coronal loop. They share similarities with other avalanche models, such as the classical stick--slip self-organized critical model of earthquakes, in that they are driven globally by a fully deterministic energy loading process. The model design leads to a systematic deficit of small scale avalanches. In some portions of model space, mid-size and large avalanching behavior is scale-free, being characterized by event size distributions that have the form of power-laws with index values, which, in some parameter regimes, compare favorably to those inferred from solar EUV and X-ray flare data. For models using conservative or near-conservative redistribution rules, a population of large, quasiperiodic avalanches can also appear. Although without direct counterparts in the observational global statistics of flare energy release, this latter behavior may be relevant to recurrent flaring in individual coronal loops. This class of models could provide a basis for the prediction of large solar flares.Comment: 24 pages, 11 figures, 2 tables, accepted for publication in Solar Physic

Statistical Learning Methods to Identify Nonwear Periods From Accelerometer Data

Background: Accelerometers are used to objectively measure movement in free-living individuals. Distinguishing nonwear from sleep and sedentary behavior is important to derive accurate measures of physical activity, sedentary behavior, and sleep. We applied statistical learning approaches to examine their promise in detecting nonwear time and compared the results with commonly used wear time (WT) algorithms. Methods: Fifteen children, aged 4–17, wore an ActiGraph wGT3X- BT monitor on their hip during overnight polysomnography. We applied Hidden Markov Models (HMM) and Gaussian Mixture Models (GMM) to classify states of nonwear and wear in triaxial acceleration data. Performance of methods was compared with WT algorithms across two conditions with differing amounts of consecutive nonwear. Clinical scoring of polysomnography served as the gold standard. Results: When the length of nonwear was less than or equal to WT algorithms’ predefined thresholds for consecutive nonwear time, GMM methods yielded improved classification error, specificity, positive predictive value, and negative predictive value over commonly used algorithms. HMM was superior to one algorithm for sensitivity and negative predictive value. When the length of nonwear was longer, results were mixed, with the commonly used algorithms performing better on some parameters but GMM with the greatest specificity. However, all approached the upper limits of performance for almost all metrics. Conclusions: GMM and HMM demonstrated robust, consistently strong performance across multiple conditions, surpassing or remaining competitive with commonly used WT algorithms which had marked inaccuracy when nonwear time periods were shorter. Of the two statistical learning algorithms, GMM was superior to HMM

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

P. aeruginosa SGNH Hydrolase-Like Proteins AlgJ and AlgX Have Similar Topology but Separate and Distinct Roles in Alginate Acetylation

The O-acetylation of polysaccharides is a common modification used by pathogenic organisms to protect against external forces. Pseudomonas aeruginosa secretes the anionic, O-acetylated exopolysaccharide alginate during chronic infection in the lungs of cystic fibrosis patients to form the major constituent of a protective biofilm matrix. Four proteins have been implicated in the O-acetylation of alginate, AlgIJF and AlgX. To probe the biological function of AlgJ, we determined its structure to 1.83 Å resolution. AlgJ is a SGNH hydrolase-like protein, which while structurally similar to the N-terminal domain of AlgX exhibits a distinctly different electrostatic surface potential. Consistent with other SGNH hydrolases, we identified a conserved catalytic triad composed of D190, H192 and S288 and demonstrated that AlgJ exhibits acetylesterase activity in vitro. Residues in the AlgJ signature motifs were found to form an extensive network of interactions that are critical for O-acetylation of alginate in vivo. Using two different electrospray ionization mass spectrometry (ESI-MS) assays we compared the abilities of AlgJ and AlgX to bind and acetylate alginate. Binding studies using defined length polymannuronic acid revealed that AlgJ exhibits either weak or no detectable polymer binding while AlgX binds polymannuronic acid specifically in a length-dependent manner. Additionally, AlgX was capable of utilizing the surrogate acetyl-donor 4-nitrophenyl acetate to catalyze the O-acetylation of polymannuronic acid. Our results, combined with previously published in vivo data, suggest that the annotated O-acetyltransferases AlgJ and AlgX have separate and distinct roles in O-acetylation. Our refined model for alginate acetylation places AlgX as the terminal acetlytransferase and provides a rationale for the variability in the number of proteins required for polysaccharide O-acetylation