Fast algorithms for automatic mapping with space-limited covariance functions

In this paper we discuss a fast Bayesian extension to kriging algorithms which has been used successfully for fast, automatic mapping in emergency conditions in the Spatial Interpolation Comparison 2004 (SIC2004) exercise. The application of kriging to automatic mapping raises several issues such as robustness, scalability, speed and parameter estimation. Various ad-hoc solutions have been proposed and used extensively but they lack a sound theoretical basis. In this paper we show how observations can be projected onto a representative subset of the data, without losing significant information. This allows the complexity of the algorithm to grow as O(n m 2), where n is the total number of observations and m is the size of the subset of the observations retained for prediction. The main contribution of this paper is to further extend this projective method through the application of space-limited covariance functions, which can be used as an alternative to the commonly used covariance models. In many real world applications the correlation between observations essentially vanishes beyond a certain separation distance. Thus it makes sense to use a covariance model that encompasses this belief since this leads to sparse covariance matrices for which optimised sparse matrix techniques can be used. In the presence of extreme values we show that space-limited covariance functions offer an additional benefit, they maintain the smoothness locally but at the same time lead to a more robust, and compact, global model. We show the performance of this technique coupled with the sparse extension to the kriging algorithm on synthetic data and outline a number of computational benefits such an approach brings. To test the relevance to automatic mapping we apply the method to the data used in a recent comparison of interpolation techniques (SIC2004) to map the levels of background ambient gamma radiation. © Springer-Verlag 2007

Social Cohesion, Structural Holes, and a Tale of Two Measures

EMBARGOED - author can archive pre-print or post-print on any open access repository after 12 months from publication. Publication date is May 2013 so embargoed until May 2014.This is an author’s accepted manuscript (deposited at arXiv arXiv:1211.0719v2 [physics.soc-ph] ), which was subsequently published in Journal of Statistical Physics May 2013, Volume 151, Issue 3-4, pp 745-764. The final publication is available at link.springer.com http://link.springer.com/article/10.1007/s10955-013-0722-

The impacts of environmental warming on Odonata: a review

Climate change brings with it unprecedented rates of increase in environmental temperature, which will have major consequences for the earth's flora and fauna. The Odonata represent a taxon that has many strong links to this abiotic factor due to its tropical evolutionary history and adaptations to temperate climates. Temperature is known to affect odonate physiology including life-history traits such as developmental rate, phenology and seasonal regulation as well as immune function and the production of pigment for thermoregulation. A range of behaviours are likely to be affected which will, in turn, influence other parts of the aquatic ecosystem, primarily through trophic interactions. Temperature may influence changes in geographical distributions, through a shifting of species' fundamental niches, changes in the distribution of suitable habitat and variation in the dispersal ability of species. Finally, such a rapid change in the environment results in a strong selective pressure towards adaptation to cope and the inevitable loss of some populations and, potentially, species. Where data are lacking for odonates, studies on other invertebrate groups will be considered. Finally, directions for research are suggested, particularly laboratory studies that investigate underlying causes of climate-driven macroecological patterns

Patient advocacy: barriers and facilitators

BACKGROUND: During the two recent decades, advocacy has been a topic of much debate in the nursing profession. Although advocacy has embraced a crucial role for nurses, its extent is often limited in practice. While a variety of studies have been generated all over the world, barriers and facilitators in the patient advocacy have not been completely identified. This article presents the findings of a study exploring the barriers and facilitators influencing the role of advocacy among Iranian nurses. METHOD: This study was conducted by grounded theory method. Participants were 24 Iranian registered nurses working in a large university hospital in Tehran, Iran. Semi-structured interviews were used for data collection. All interviews were transcribed verbatim and simultaneously Constant comparative analysis was used according to the Strauss and Corbin method. RESULTS: Through data analysis, several main themes emerged to describe the factors that hindered or facilitated patient advocacy. Nurses in this study identified powerlessness, lack of support, law, code of ethics and motivation, limited communication, physicians leading, risk of advocacy, royalty to peers, and insufficient time to interact with patients and families as barriers to advocacy. As for factors that facilitated nurses to act as a patient advocate, it was found that the nature of nurse-patient relationship, recognizing patients' needs, nurses' responsibility, physician as a colleague, and nurses' knowledge and skills could be influential in adopting the advocacy role. CONCLUSION: Participants believed that in this context taking an advocacy role is difficult for nurses due to the barriers mentioned. Therefore, they make decisions and act as a patient's advocate in any situation concerning patient needs and status of barriers and facilitators. In most cases, they can not act at an optimal level; instead they accept only what they can do, which we called 'limited advocacy' in this study. It is concluded that advocacy is contextually complex, and is a controversial and risky component of the nursing practice. Further research is needed to determine the possibility of a correlation between identified barriers/ facilitators and the use of advocacy

Idle hands are the devil’s tools: The geopolitics and geoeconomics of hunger

In current geopolitical and geoeconomic discourses, hunger is understood as both a threat to be contained, resulting in an often severe social and spatial localization of food insecurity, and a humanitarian problem to be solved through diffuse global flows of food and other aid. The resulting scalar tensions demonstrate the potentially contradictory alignment of geopolitics and geoeconomics within processes of globalization and neoliberalization. This article examines the geopolitical and geoeconomic place of hunger and the hungry through a critical analysis of the food-for-work (FFW) approach to combating hunger. FFW programs distribute food aid in exchange for labor, and have long been used to plan and deliver food aid. While debate continues as to whether and under what conditions FFW programs are socially and economically just, governments, international institutions, and NGOs tout them as a flexible and efficient way to deliver targeted aid, promote community development, and improve long-term prospects for economic development and food security. In the post-9/11 period, FFW programs are also cited as effective deterrents to terrorist recruitment strategies, while development and food security more broadly have been incorporated into national security strategies, especially but not only in the United States. The food-for-work approach attempts to resolve the scalar contradictions of hunger through the imposition of a labor requirement that disciplines the threat of the hungry while enforcing global connection. Case studies of FFW programs in Bangladesh, Ethiopia, and Indonesia illustrate this contradiction, and highlight the development and possible future of approaches to hunger under neoliberal geopolitics

Sensitivity to Gravitational Waves from Compact Binary Coalescences Achieved during LIGO's Fifth and Virgo's First Science Run

We summarize the sensitivity achieved by the LIGO and Virgo gravitational wave detectors for compact binary coalescence (CBC) searches during LIGO's fifth science run and Virgo's first science run. We present noise spectral density curves for each of the four detectors that operated during these science runs which are representative of the typical performance achieved by the detectors for CBC searches. These spectra are intended for release to the public as a summary of detector performance for CBC searches during these science runs.Comment: 12 pages, 5 figure

Directional limits on persistent gravitational waves using LIGO S5 science data

The gravitational-wave (GW) sky may include nearby pointlike sources as well as astrophysical and cosmological stochastic backgrounds. Since the relative strength and angular distribution of the many possible sources of GWs are not well constrained, searches for GW signals must be performed in a model-independent way. To that end we perform two directional searches for persistent GWs using data from the LIGO S5 science run: one optimized for pointlike sources and one for arbitrary extended sources. The latter result is the first of its kind. Finding no evidence to support the detection of GWs, we present 90% confidence level (CL) upper-limit maps of GW strain power with typical values between 2-20x10^-50 strain^2 Hz^-1 and 5-35x10^-49 strain^2 Hz^-1 sr^-1 for pointlike and extended sources respectively. The limits on pointlike sources constitute a factor of 30 improvement over the previous best limits. We also set 90% CL limits on the narrow-band root-mean-square GW strain from interesting targets including Sco X-1, SN1987A and the Galactic Center as low as ~7x10^-25 in the most sensitive frequency range near 160 Hz. These limits are the most constraining to date and constitute a factor of 5 improvement over the previous best limits.Comment: 10 pages, 4 figure

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis

Enhancer Reprogramming Confers Dependence on Glycolysis and IGF Signaling in KMT2D Mutant Melanoma.

Histone methyltransferase KMT2D harbors frequent loss-of-function somatic point mutations in several tumor types, including melanoma. Here, we identify KMT2D as a potent tumor suppressor in melanoma through an in vivo epigenome-focused pooled RNAi screen and confirm the finding by using a genetically engineered mouse model (GEMM) based on conditional and melanocyte-specific deletion of KMT2D. KMT2D-deficient tumors show substantial reprogramming of key metabolic pathways, including glycolysis. KMT2D deficiency aberrantly upregulates glycolysis enzymes, intermediate metabolites, and glucose consumption rates. Mechanistically, KMT2D loss causes genome-wide reduction of H3K4me1-marked active enhancer chromatin states. Enhancer loss and subsequent repression of IGFBP5 activates IGF1R-AKT to increase glycolysis in KMT2D-deficient cells. Pharmacological inhibition of glycolysis and insulin growth factor (IGF) signaling reduce proliferation and tumorigenesis preferentially in KMT2D-deficient cells. We conclude that KMT2D loss promotes tumorigenesis by facilitating an increased use of the glycolysis pathway for enhanced biomass needs via enhancer reprogramming, thus presenting an opportunity for therapeutic intervention through glycolysis or IGF pathway inhibitors

Learning Sequences: Their Existence, Effect, and Evolution

Much is known about the importance of learning and some of the distinct learning processes that organizations use (e.g., trial-and-error learning, vicarious learning, experimental learning, and improvisational learning). Yet surprisingly little is known about whether these processes combine over time in ordered ways, because most research on learning explores one particular process. Using theory elaboration and theory-building methods and data on the accumulated country entries of entrepreneurial firms, we address this gap. Our core contribution is an emergent theoretical framework that develops the concept of learning sequences. We find that learning sequences exist and are influenced by initial conditions. We also find that learning sequences evolve in fundamentally distinct ways over time and with repeated use. Finally, data show how different learning sequences differentially affect both shorter- and longer-term performance, suggesting that it matters which learning processes are used and when. Overall, our findings on learning sequences have important implications for learning theory, international entrepreneurship, and the growing literature on process management