A last millennium perspective on North Atlantic variability: exploiting synergies between models and proxy data

The North Atlantic is a key region for decadal prediction as it has experienced significant multi-decadal variability over the observed period. This variability, which is thought to be intrinsic to the region, can potentially modulate, either by amplifying or mitigating, the global warming signal from anthropogenic greenhouse emissions. For example, studies suggest that the North Atlantic contributed to the recent hiatus period between 1998 and 2012, by triggering an atmospheric response which impacted on the eastern tropical Pacific (e.g. McGregor et al., 2014). The subpolar North Atlantic is also a major CO2 sink, and therefore of great importance for the global carbon cycle (Perez et al., 2013). One of the key players in the North Atlantic region is the Atlantic Meridional Overturning Circulation (AMOC), which is associated with sinking due to deep water formation in the Labrador and Nordic Seas. The AMOC is the primary control of the poleward heat transport in the Atlantic region. Therefore, the AMOC is associated with important climate impacts, and plays an active role in various feedback mechanisms with, for example, sea ice (Mahajan et al., 2011) and the atmospheric circulation (Gastineau and Frankignoul, 2012). The AMOC has exhibited abrupt variations in the past (e.g. the last glacial period, Rahmstorf, 2002) and could experience a major slowdown in the future due to the combined effect of surface warming and Greenland ice sheet melting on deep water formation (Bakker et al., 2016). The possibility of such a shutdown has stimulated considerable international efforts to observe and reconstruct the past AMOC changes. Only by understanding its natural variability will we be able to detect and anticipate an anthropogenic impact on the AMOC. Decadal modulations are also found in other large-scale modes of climate variability, such as the North Atlantic Oscillation (NAO) (Stephenson et al., 2000), the Subpolar Gyre strength (SPG) (Häkkinen and Rhines, 2004) and the Atlantic Multidecadal Variability (AMV) (Enfield et al., 2001), which have all been linked with widespread climate impacts over the surrounding continents. Modelling studies suggest that all these modes interact with the AMOC (Gastineau and Frankignoul, 2012; Hátún et al., 2005; Knight et al., 2005) but the exact interrelationships are complex and remain to be disentangled. Also to be determined are the underlying mechanisms responsible for the decadal and centennial AMOC modulations, with different climate models showing different key drivers (Menary et al., 2015a). Similarly, the exact impact of the natural external forcings (e.g. volcanic aerosols, solar irradiance) on the variability of these different largescale climate modes still remains unclear

Threading Through Macrocycles Enhances the Performance of Carbon Nanotubes as Polymer Fillers

In this work we study the reinforcement of polymers by mechanically interlocked derivatives of single-walled carbon nanotubes (SWNTs). We compare the mechanical properties of fibers made of polymers and of composites with pristine single-walled carbon nanotubes (SWNTs), mechanically interlocked derivatives of SWNTs (MINTs) and the corresponding supramolecular models. Improvements of both Young's modulus and tensile strength of up to 200 % were observed for the polystyrene-MINTs samples with an optimized loading of just 0.01 wt.%, while the supramolecular models with identical chemical composition and loading showed negligible or even detrimental influence. This behavior is found for three different types of SWNTs and two types of macrocycles. Molecular dynamics simulations show that the polymer adopts an elongated conformation parallel to the SWNT when interacting with MINT fillers, irrespective of the macrocycle chemical nature, whereas a more globular structure is taken upon facing with either pristine SWNTs or supramolecular models. The MINT composite architecture thus leads to a more efficient exploitation of the axial properties of the SWNTs and of the polymer chain at the interface, in agreement with experimental results. Our findings demonstrate that the mechanical bond imparts distinctive advantageous properties to SWNT derivatives as polymer fillers.Comment: 39 pages, 19 figure

Sexual abuse and psychotic phenomena: a directed acyclic graph analysis of affective symptoms using English national psychiatric survey data

Background Sexual abuse and bullying are associated with poor mental health in adulthood. We previously established a clear relationship between bullying and symptoms of psychosis. Similarly, we would expect sexual abuse to be linked to the emergence of psychotic symptoms, through effects on negative affect. Method We analysed English data from the Adult Psychiatric Morbidity Surveys, carried out in 2007 (N = 5954) and 2014 (N = 5946), based on representative national samples living in private households. We used probabilistic graphical models represented by directed acyclic graphs (DAGs). We obtained measures of persecutory ideation and auditory hallucinosis from the Psychosis Screening Questionnaire, and identified affective symptoms using the Clinical Interview Schedule. We included cannabis consumption and sex as they may determine the relationship between symptoms. We constrained incoming edges to sexual abuse and bullying to respect temporality. Results In the DAG analyses, contrary to our expectations, paranoia appeared early in the cascade of relationships, close to the abuse variables, and generally lying upstream of affective symptoms. Paranoia was consistently directly antecedent to hallucinations, but also indirectly so, via non-psychotic symptoms. Hallucinosis was also the endpoint of pathways involving non-psychotic symptoms. Conclusions Via worry, sexual abuse and bullying appear to drive a range of affective symptoms, and in some people, these may encourage the emergence of hallucinations. The link between adverse experiences and paranoia is much more direct. These findings have implications for managing distressing outcomes. In particular, worry may be a salient target for intervention in psychosis

Links between psychotic and neurotic symptoms in the general population: an analysis of longitudinal British National Survey data using Directed Acyclic Graphs

BACKGROUND: Non-psychotic affective symptoms are important components of psychotic syndromes. They are frequent and are now thought to influence the emergence of paranoia and hallucinations. Evidence supporting this model of psychosis comes from recent cross-fertilising epidemiological and intervention studies. Epidemiological studies identify plausible targets for intervention but must be interpreted cautiously. Nevertheless, causal inference can be strengthened substantially using modern statistical methods. METHODS: Directed Acyclic Graphs were used in a dynamic Bayesian network approach to learn the overall dependence structure of chosen variables. DAG-based inference identifies the most likely directional links between multiple variables, thereby locating them in a putative causal cascade. We used initial and 18-month follow-up data from the 2000 British National Psychiatric Morbidity survey (N = 8580 and N = 2406). RESULTS: We analysed persecutory ideation, hallucinations, a range of affective symptoms and the effects of cannabis and problematic alcohol use. Worry was central to the links between symptoms, with plausible direct effects on insomnia, depressed mood and generalised anxiety, and recent cannabis use. Worry linked the other affective phenomena with paranoia. Hallucinations were connected only to worry and persecutory ideation. General anxiety, worry, sleep problems, and persecutory ideation were strongly self-predicting. Worry and persecutory ideation were connected over the 18-month interval in an apparent feedback loop. CONCLUSIONS: These results have implications for understanding dynamic processes in psychosis and for targeting psychological interventions. The reciprocal influence of worry and paranoia implies that treating either symptom is likely to ameliorate the other

Advanced radiometric and interferometric milimeter-wave scene simulations

Smart munitions and weapons utilize various imaging sensors (including passive IR, active and passive millimeter-wave, and visible wavebands) to detect/identify targets at short standoff ranges and in varied terrain backgrounds. In order to design and evaluate these sensors under a variety of conditions, a high-fidelity scene simulation capability is necessary. Such a capability for passive millimeter-wave scene simulation exists at TRW. TRW's Advanced Radiometric Millimeter-Wave Scene Simulation (ARMSS) code is a rigorous, benchmarked, end-to-end passive millimeter-wave scene simulation code for interpreting millimeter-wave data, establishing scene signatures and evaluating sensor performance. In passive millimeter-wave imaging, resolution is limited due to wavelength and aperture size. Where high resolution is required, the utility of passive millimeter-wave imaging is confined to short ranges. Recent developments in interferometry have made possible high resolution applications on military platforms. Interferometry or synthetic aperture radiometry allows the creation of a high resolution image with a sparsely filled aperture. Borrowing from research work in radio astronomy, we have developed and tested at TRW scene reconstruction algorithms that allow the recovery of the scene from a relatively small number of spatial frequency components. In this paper, the TRW modeling capability is described and numerical results are presented

Electrospun amplified fiber optics

A lot of research is focused on all-optical signal processing, aiming to obtain effective alternatives to existing data transmission platforms. Amplification of light in fiber optics, such as in Erbium-doped fiber amplifiers, is especially important for an efficient signal transmission. However, the complex fabrication methods, involving high-temperature processes performed in highly pure environment, slow down the fabrication and make amplified components expensive with respect to an ideal, high-throughput and room temperature production. Here, we report on near infrared polymer fiber amplifiers, working over a band of about 20 nm. The fibers are cheap, spun with a process entirely carried out at room temperature, and show amplified spontaneous emission with good gain coefficients as well as low optical losses (a few cm^-1). The amplification process is favoured by the high fiber quality and low self-absorption. The found performance metrics promise to be suitable for short-distance operation, and the large variety of commercially-available doping dyes might allow for effective multi-wavelength operation by electrospun amplified fiber optics.Comment: 27 pages, 8 figure

Using directed acyclic graphs in epidemiological research in psychosis:an analysis of the role of bullying in psychosis

Modern psychiatric epidemiology researches complex interactions between multiple variables in large datasets. This creates difficulties for causal inference. We argue for the use of probabilistic models represented by directed acyclic graphs (DAGs). These capture the dependence structure of multiple variables and, used appropriately, allow more robust conclusions about the direction of causation. We analyzed British national survey data to assess putative mediators of the association between bullying victimization and persecutory ideation. We compared results using DAGs and the Karlson-Holm-Breen (KHB) logistic regression commands in STATA. We analyzed data from the 2007 English National Survey of Psychiatric Morbidity, using the equivalent 2000 survey in an instant replication. Additional details of methods and results are provided in the supplementary material. DAG analysis revealed a richer structure of relationships than could be inferred using the KHB logistic regression commands. Thus, bullying had direct effects on worry, persecutory ideation, mood instability, and drug use. Depression, sleep and anxiety lay downstream, and therefore did not mediate the link between bullying and persecutory ideation. Mediation by worry and mood instability could not be definitively ascertained. Bullying led to hallucinations indirectly, via persecutory ideation and depression. DAG analysis of the 2000 dataset suggested the technique generates stable results. While causality cannot be fully determined from cross-sectional data, DAGs indicate the relationships providing the best fit. They thereby advance investigation of the complex interactions seen in psychiatry, including the mechanisms underpinning psychiatric symptoms. It may consequently be used to optimize the choice of intervention targets.</p

A Bayesian method for evaluating and discovering disease loci associations

Background: A genome-wide association study (GWAS) typically involves examining representative SNPs in individuals from some population. A GWAS data set can concern a million SNPs and may soon concern billions. Researchers investigate the association of each SNP individually with a disease, and it is becoming increasingly commonplace to also analyze multi-SNP associations. Techniques for handling so many hypotheses include the Bonferroni correction and recently developed Bayesian methods. These methods can encounter problems. Most importantly, they are not applicable to a complex multi-locus hypothesis which has several competing hypotheses rather than only a null hypothesis. A method that computes the posterior probability of complex hypotheses is a pressing need. Methodology/Findings: We introduce the Bayesian network posterior probability (BNPP) method which addresses the difficulties. The method represents the relationship between a disease and SNPs using a directed acyclic graph (DAG) model, and computes the likelihood of such models using a Bayesian network scoring criterion. The posterior probability of a hypothesis is computed based on the likelihoods of all competing hypotheses. The BNPP can not only be used to evaluate a hypothesis that has previously been discovered or suspected, but also to discover new disease loci associations. The results of experiments using simulated and real data sets are presented. Our results concerning simulated data sets indicate that the BNPP exhibits both better evaluation and discovery performance than does a p-value based method. For the real data sets, previous findings in the literature are confirmed and additional findings are found. Conclusions/Significance: We conclude that the BNPP resolves a pressing problem by providing a way to compute the posterior probability of complex multi-locus hypotheses. A researcher can use the BNPP to determine the expected utility of investigating a hypothesis further. Furthermore, we conclude that the BNPP is a promising method for discovering disease loci associations. © 2011 Jiang et al

First narrow-band search for continuous gravitational waves from known pulsars in advanced detector data

Spinning neutron stars asymmetric with respect to their rotation axis are potential sources of continuous gravitational waves for ground-based interferometric detectors. In the case of known pulsars a fully coherent search, based on matched filtering, which uses the position and rotational parameters obtained from electromagnetic observations, can be carried out. Matched filtering maximizes the signalto- noise (SNR) ratio, but a large sensitivity loss is expected in case of even a very small mismatch between the assumed and the true signal parameters. For this reason, narrow-band analysis methods have been developed, allowing a fully coherent search for gravitational waves from known pulsars over a fraction of a hertz and several spin-down values. In this paper we describe a narrow-band search of 11 pulsars using data from Advanced LIGO’s first observing run. Although we have found several initial outliers, further studies show no significant evidence for the presence of a gravitational wave signal. Finally, we have placed upper limits on the signal strain amplitude lower than the spin-down limit for 5 of the 11 targets over the bands searched; in the case of J1813-1749 the spin-down limit has been beaten for the first time. For an additional 3 targets, the median upper limit across the search bands is below the spin-down limit. This is the most sensitive narrow-band search for continuous gravitational waves carried out so far

Biological and climate controls on North Atlantic marine carbon dynamics over the last millennium: Insights from an absolutely-dated shell based record from the North Icelandic Shelf

Given the rapid increase in atmospheric carbon dioxide concentrations (pCO2) over the industrial era, there is a pressing need to construct long‐term records of natural carbon cycling prior to this perturbation and to develop a more robust understanding of the role the oceans play in the sequestration of atmospheric carbon. Here we reconstruct the past biological and climate controls on the carbon isotopic (δ13Cshell) composition of the North Icelandic shelf waters over the last millennium, derived from the shells of the long‐lived marine bivalve mollusk Arctica islandica. Variability in the annually resolved δ13Cshell record is dominated by multidecadal variability with a negative trend (−0.003 ± 0.002‰ yr−1) over the industrial era (1800–2000 Common Era). This trend is consistent with the marine Suess effect brought about by the sequestration of isotopically light carbon (δ13C of CO2) derived from the burning of fossil fuels. Comparison of the δ13Cshell record with Contemporaneous proxy archives, over the last millennium, and instrumental data over the twentieth century, highlights that both biological (primary production) and physical environmental factors, such as relative shifts in the proportion of Subpolar Mode Waters and Arctic Intermediate Waters entrained onto the North Icelandic shelf, atmospheric circulation patterns associated with the winter North Atlantic Oscillation, and sea surface temperature and salinity of the subpolar gyre, are the likely mechanisms that contribute to natural variations in seawater δ13C variability on the North Icelandic shelf. Contrasting δ13C fractionation processes associated with these biological and physical mechanisms likely cause the attenuated marine Suess effect signal at this locality