A preliminary optical visibility model

A model is being created to describe the effect of weather on optical communications links between space and ground sites. This article describes the process by which the model is developed and gives preliminary results for two sites. The results indicate nighttime attenuation of optical transmission at five wavelengths. It is representative of a sampling of nights at Table Mountain Observatory from January to June and Mount Lemmon Observatory from May and June. The results are designed to predict attenuation probabilities for optical communications links

Enhanced Bovine Colostrum Supplementation Shortens the Duration of Respiratory Disease in Thoroughbred Yearlings

AbstractBovine colostrum (BC) is used in humans as a nutritional supplement for immune support and has been shown to reduce Respiratory disease (RD). Other nutritional supplements, minerals and vitamins including mannan oligosaccharides (MOS), zinc and vitamins A, C and E have also been used for immune support. The aim of this prospective blinded randomized clinical trial was to evaluate the effects of a BC, MOS, zinc and vitamin based enhanced bovine colostrum supplement (BCS) on incidence and duration of RD occurring in yearling horses. 109 yearlings on two Thoroughbred farms in Central Kentucky were randomly assigned to treatment or placebo groups. Yearlings were supplemented once daily for 17 to 25 weeks with 100 g of a high quality commercial BCS (containing 50 g BC) or a full fat soy flour placebo, which were applied as a “top-dress” to feed. Yearlings were observed daily and evaluated weekly for signs of RD. All yearlings completed the study. The proportion of the study period during which each yearling exhibited illness was considerably shorter for BCS yearlings (least squares mean = 23% of the study period) than placebo yearlings (least squares mean = 34% of the study period, P = .002). The average duration of illness was shorter for BCS yearlings (1.96 weeks) than placebo yearlings (4.39 weeks, P < .0001). There was no statistical difference in the incidence of RD in these study yearlings

Enhancement and suppression effects resulting from information structuring in sentences

Information structuring through the use of cleft sentences increases the processing efficiency of references to elements within the scope of focus. Furthermore, there is evidence that putting certain types of emphasis on individual words not only enhances their subsequent processing, but also protects these words from becoming suppressed in the wake of subsequent information, suggesting mechanisms of enhancement and suppression. In Experiment 1, we showed that clefted constructions facilitate the integration of subsequent sentences that make reference to elements within the scope of focus, and that they decrease the efficiency with reference to elements outside of the scope of focus. In Experiment 2, using an auditory text-change-detection paradigm, we showed that focus has similar effects on the strength of memory representations. These results add to the evidence for enhancement and suppression as mechanisms of sentence processing and clarify that the effects occur within sentences having a marked focus structure

Understanding Face and Shame: A Servant-Leadership and Face Management Model

Clergy can have a negative impact on churches and other individuals when they knowingly or unknowingly attempt to save face, that is, try to protect their standing or reputation. The desire to gain face and the fear of losing face and feeling ashamed will likely permeate clergy’s decision-making processes without even being noticed. This study explores the essence of face and face management and the relationship between face management and two characteristics of servant-leadership—awareness and healing—in both Chinese and American churches through the methodology of hermeneutic phenomenology. Prior to this study, to my knowledge, no hermeneutic phenomenological research of face management has been conducted in a church setting. Through a review of the literature, four areas are explored: face and shame, face management, servant-leadership, and face, shame, and face management within the church. This study obtained approval from the Institutional Review Board and informed consent from the participants. Three Chinese and three American Christian ministers were chosen to complete a question sheet and participate in two semi-structured interview sessions. A first cycle of open coding and second cycle of pattern coding were used during data analysis. Face experiences are discussed in light of eight major themes: body, triggers, becoming, face concepts, strategies, emotions, servant-leadership, and the church. Findings from the study help build a servant-leadership and face management model, which can offer an anchored approach for clergy and pastoral counselors to address face and shame and to develop therapeutic interventions

Biodiversity-productivity relationships are key to nature-based climate solutions

The global impacts of biodiversity loss and climate change are interlinked, but the feedbacks between them are rarely assessed. Areas with greater tree diversity tend to be more productive, providing a greater carbon sink, and biodiversity loss could reduce these natural carbon sinks. Here, we quantify how tree and shrub species richness could affect biomass production on biome, national and regional scales. We find that GHG mitigation could help maintain tree diversity and thereby avoid a 9–39% reduction in terrestrial primary productivity across different biomes, which could otherwise occur over the next 50 years. Countries that will incur the greatest economic damages from climate change stand to benefit the most from conservation of tree diversity and primary productivity, which contribute to climate change mitigation. Our results emphasize an opportunity for a triple win for climate, biodiversity and society, and highlight that these co-benefits should be the focus of reforestation programmes

Grand challenges in biodiversity-ecosystem functioning research in the era of science-policy platforms require explicit consideration of feedbacks

Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and—critically—the feedbacks among them

Using Markov chain Monte Carlo methods for estimating parameters with gravitational radiation data

We present a Bayesian approach to the problem of determining parameters for coalescing binary systems observed with laser interferometric detectors. By applying a Markov Chain Monte Carlo (MCMC) algorithm, specifically the Gibbs sampler, we demonstrate the potential that MCMC techniques may hold for the computation of posterior distributions of parameters of the binary system that created the gravity radiation signal. We describe the use of the Gibbs sampler method, and present examples whereby signals are detected and analyzed from within noisy data.Comment: 21 pages, 10 figure

II: Bayesian Methods for Cosmological Parameter Estimation from Cosmic Microwave Background Measurements

We present a strategy for a statistically rigorous Bayesian approach to the problem of determining cosmological parameters from the results of observations of anisotropies in the cosmic microwave background. Our strategy relies on Markov chain Monte Carlo methods, specifically the Metropolis-Hastings algorithm, to perform the necessary high-dimensional integrals. We describe the Metropolis-Hastings algorithm in detail and discuss the results of our test on simulated data.Comment: This paper expands on the work presented in astro-ph/0006401, and now includes a test of the method. 15 pages, 1 figur

Inferring signalling networks from longitudinal data using sampling based approaches in the R-package 'ddepn'

<p>Abstract</p> <p>Background</p> <p>Network inference from high-throughput data has become an important means of current analysis of biological systems. For instance, in cancer research, the functional relationships of cancer related proteins, summarised into signalling networks are of central interest for the identification of pathways that influence tumour development. Cancer cell lines can be used as model systems to study the cellular response to drug treatments in a time-resolved way. Based on these kind of data, modelling approaches for the signalling relationships are needed, that allow to generate hypotheses on potential interference points in the networks.</p> <p>Results</p> <p>We present the R-package 'ddepn' that implements our recent approach on network reconstruction from longitudinal data generated after external perturbation of network components. We extend our approach by two novel methods: a Markov Chain Monte Carlo method for sampling network structures with two edge types (activation and inhibition) and an extension of a prior model that penalises deviances from a given reference network while incorporating these two types of edges. Further, as alternative prior we include a model that learns signalling networks with the scale-free property.</p> <p>Conclusions</p> <p>The package 'ddepn' is freely available on R-Forge and CRAN <url>http://ddepn.r-forge.r-project.org</url>, <url>http://cran.r-project.org</url>. It allows to conveniently perform network inference from longitudinal high-throughput data using two different sampling based network structure search algorithms.</p