Queen Anne's ministers and the administration of Scotland, 1707-1714

The Union left the future of Scottish administration in the hands of the Queen's ministers. The methods adopted by Godolphin and Harley differed, partly because their political problems were different and partly because of temperament. Godolphin tried as far as he could to rule Scotland in the old way, through Queensberry1s Court Party. He hoped to strengthen the Court at Westminster with the Scottish representatives elected under influence. When the abolition of the Privy Council upset his full scheme he strove to keep the channel of administration between England and Scotland in the hands of the Court Party. Harley also wished to strengthen the Court at Westminster but he could not rule through a homogeneous Court Party in Scotland since he was hoping to draw support from too wide a field to risk giving offence. To solve the problem he tried to administer Scotland himself through the financial departments, advised by personal agents. He hoped to make the secretary?s office redundant. The scheme proved to be largely a system of centralised procrastination. Opportunity was provided for Bolingbroke as a secretary of State to expedite business in a bid for interest amongst the Scots. In self defence Harley had to appoint Mar as third secretary. As far as revenue departments were concerned Godolphin kept to the proper channels of business, observed precedent and set much store by official opinion. Patronage he left largely to the commissioners which probably meant putting it in the hands of the Scottish ministry. Harley trusted the revenue commissioners far less and was much less a respecter of the proper channels and forms of business. And, although it was done informally, patronage seems to have been directed much more from the Treasury under Harley.<p

Financial Doping in the English Premier League

Whilst the relationship between money and success in elite sport is acknowledged, the exact nature, extent and implications of this relationship is one that has not been carefully examined. In this paper we have three main aims. Firstly, to provide empirical evidence of the extent that money buys success in the English Premier League. Secondly, to evaluate this evidence from a sports ethics perspective, and, finally, to discuss potential solutions to the problem. We argue that the evident performance advantage teams gain through financial investments is contrary to the spirit of sport as it undermines athletic excellence and the ‘sweet tension of uncertainty of outcome’ that is central to good competition. Consequently, financial investments in elite football ought to be regulated and controlled. We argue, however, that current attempts to do so (via Financial Fair Play Regulations) are inadequate as they focus on issues concerning financial health, rather than the health of the game in terms of spirit and fairness

Systematic review identifies the design and methodological conduct of studies on machine learning-based prediction models

Background and ObjectivesWe sought to summarize the study design, modelling strategies, and performance measures reported in studies on clinical prediction models developed using machine learning techniques.MethodsWe search PubMed for articles published between 01/01/2018 and 31/12/2019, describing the development or the development with external validation of a multivariable prediction model using any supervised machine learning technique. No restrictions were made based on study design, data source, or predicted patient-related health outcomes.ResultsWe included 152 studies, 58 (38.2% [95% CI 30.8–46.1]) were diagnostic and 94 (61.8% [95% CI 53.9–69.2]) prognostic studies. Most studies reported only the development of prediction models (n = 133, 87.5% [95% CI 81.3–91.8]), focused on binary outcomes (n = 131, 86.2% [95% CI 79.8–90.8), and did not report a sample size calculation (n = 125, 82.2% [95% CI 75.4–87.5]). The most common algorithms used were support vector machine (n = 86/522, 16.5% [95% CI 13.5–19.9]) and random forest (n = 73/522, 14% [95% CI 11.3–17.2]). Values for area under the Receiver Operating Characteristic curve ranged from 0.45 to 1.00. Calibration metrics were often missed (n = 494/522, 94.6% [95% CI 92.4–96.3]).ConclusionOur review revealed that focus is required on handling of missing values, methods for internal validation, and reporting of calibration to improve the methodological conduct of studies on machine learning–based prediction models

A multi-scale comparison of modeled and observed seasonal methane emissions in northern wetlands

Wetlands are the largest global natural methane (CH4/ source, and emissions between 50 and 70° N latitude contribute 10-30% to this source. Predictive capability of land models for northern wetland CH4 emissions is still low due to limited site measurements, strong spatial and temporal variability in emissions, and complex hydrological and biogeochemical dynamics. To explore this issue, we compare wetland CH4 emission predictions from the Community Land Model 4.5 (CLM4.5-BGC) with siteto regional-scale observations. A comparison of the CH4 fluxes with eddy flux data highlighted needed changes to the model's estimate of aerenchyma area, which we implemented and tested. The model modification substantially reduced biases in CH4 emissions when compared with CarbonTracker CH4 predictions. CLM4.5 CH4 emission predictions agree well with growing season (May-September) CarbonTracker Alaskan regional-level CH4 predictions and sitelevel observations. However, CLM4.5 underestimated CH4 emissions in the cold season (October-April). The monthly atmospheric CH4 mole fraction enhancements due to wetland emissions are also assessed using the Weather Research and Forecasting-Stochastic Time-Inverted Lagrangian Transport (WRF-STILT) model coupled with daily emissions from CLM4.5 and compared with aircraft CH4 mole fraction measurements from the Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) campaign. Both the tower and aircraft analyses confirm the underestimate of cold-season CH4 emissions by CLM4.5. The greatest uncertainties in predicting the seasonal CH4 cycle are from the wetland extent, coldseason CH4 production and CH4 transport processes. We recommend more cold-season experimental studies in highlatitude systems, which could improve the understanding and parameterization of ecosystem structure and function during this period. Predicted CH4 emissions remain uncertain, but we show here that benchmarking against observations across spatial scales can inform model structural and parameter improvements

Investigating patterns of pond and lake distributions to enhance the modeling of future Arctic surface inundation

Permafrost acts as an impermeable subsurface in Arctic lowland landscapes. This hydrological barrier results in carbon-rich, water-saturated soils as well as many ponds and lakes. The rapidly warming Arctic climate very likely will affect the surface inundation in Arctic lowlands due to changes in precipitation, evapotranspiration, and permafrost degradation. Drying and wetting of the surface may occur in different regions and potentially alter the exchange of energy and carbon between the surface and the atmosphere. With increased permafrost thaw, for example, water may drain to deeper soil layers or drainage maybe enhanced due to newly forming drainage networks. Melting ground ice and subsequent inundation, on the other hand, may enhance formation of new ponds and wet areas. The current distribution of ponds and lakes in the Arctic is the result of complex interactions between climate, ground ice volume, topography, age and sediment characteristics. Because lake formation and growth processes occur at spatial scales orders of magnitude below those of the resolution for global or pan-arctic models land surface models, statistical representations of lake size distributions and other properties to inform such processes in future models are needed that can be related to macroscopic landcape properties. This study proposes basic observationally-constrained relationships to enhance the modeling of future Arctic surface inundation. We mapped ponds and lakes in 21 circum-arctic sites representing different permafrost-soil landscapes, i.e., physiographic regions with similar surface geology, regional climate, and biomes. We used high-resolution optical and radar satellite imagery with spatial resolutions of 4 m or better to create detailed water body maps and derive representative probability density functions (PDF). PDFs of ponds and lakes vary little within the same ecoregion. Significant differences, however, do occur between landscapes. We used regional permafrost-soil landscape maps of Alaska, Canada, and Siberia to upscale the water body distributions to the circum-arctic. We here present regional distribution parameters, i.e. pond and lake fractions as well as PDF moments (mean surface area, standard deviation, and skewness) and their uncertainties. Younger landscapes, that developed in the early Holocene exhibit very skewed water body distributions. These landscapes are dominated by many ponds and feature only very few large lakes. Older landscapes, on the other hand, show more larger lakes but also a higher variability in pond and lake size. For lakes smaller than 5*10⁵ m², PDFs change in a regular fashion across all sites: Relationships between mean surface area and standard deviation show a linear behaviour whereas the correlation between mean and skewness log-normal. We hypothesize that these relationships are an expression of pond and lake growth and/or lake formation in the landscapes and discuss the potential of the observed patterns to improve predictions of future distributions of Arctic ponds and lakes

Lineage‐based functional types: characterising functional diversity to enhance the representation of ecological behaviour in Land Surface Models

Process‐based vegetation models attempt to represent the wide range of trait variation in biomes by grouping ecologically similar species into plant functional types (PFTs). This approach has been successful in representing many aspects of plant physiology and biophysics but struggles to capture biogeographic history and ecological dynamics that determine biome boundaries and plant distributions. Grass‐dominated ecosystems are broadly distributed across all vegetated continents and harbour large functional diversity, yet most Land Surface Models (LSMs) summarise grasses into two generic PFTs based primarily on differences between temperate C3 grasses and (sub)tropical C4 grasses. Incorporation of species‐level trait variation is an active area of research to enhance the ecological realism of PFTs, which form the basis for vegetation processes and dynamics in LSMs. Using reported measurements, we developed grass functional trait values (physiological, structural, biochemical, anatomical, phenological, and disturbance‐related) of dominant lineages to improve LSM representations. Our method is fundamentally different from previous efforts, as it uses phylogenetic relatedness to create lineage‐based functional types (LFTs), situated between species‐level trait data and PFT‐level abstractions, thus providing a realistic representation of functional diversity and opening the door to the development of new vegetation models

Modeling infectious disease dynamics in the complex landscape of global health.

Despite some notable successes in the control of infectious diseases, transmissible pathogens still pose an enormous threat to human and animal health. The ecological and evolutionary dynamics of infections play out on a wide range of interconnected temporal, organizational, and spatial scales, which span hours to months, cells to ecosystems, and local to global spread. Moreover, some pathogens are directly transmitted between individuals of a single species, whereas others circulate among multiple hosts, need arthropod vectors, or can survive in environmental reservoirs. Many factors, including increasing antimicrobial resistance, increased human connectivity and changeable human behavior, elevate prevention and control from matters of national policy to international challenge. In the face of this complexity, mathematical models offer valuable tools for synthesizing information to understand epidemiological patterns, and for developing quantitative evidence for decision-making in global health

Single Spin Asymmetry ANA_N in Polarized Proton-Proton Elastic Scattering at s=200\sqrt{s}=200 GeV

We report a high precision measurement of the transverse single spin asymmetry $A_N$ at the center of mass energy $\sqrt{s}=200$ GeV in elastic proton-proton scattering by the STAR experiment at RHIC. The $A_N$ was measured in the four-momentum transfer squared $t$ range $0.003 \leqslant |t| \leqslant 0.035$ \GeVcSq, the region of a significant interference between the electromagnetic and hadronic scattering amplitudes. The measured values of $A_N$ and its $t$-dependence are consistent with a vanishing hadronic spin-flip amplitude, thus providing strong constraints on the ratio of the single spin-flip to the non-flip amplitudes. Since the hadronic amplitude is dominated by the Pomeron amplitude at this $\sqrt{s}$, we conclude that this measurement addresses the question about the presence of a hadronic spin flip due to the Pomeron exchange in polarized proton-proton elastic scattering.Comment: 12 pages, 6 figure

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe

J/ψ polarization in p+p collisions at s=200 GeV in STAR

AbstractWe report on a polarization measurement of inclusive J/ψ mesons in the di-electron decay channel at mid-rapidity at 2<pT<6 GeV/c in p+p collisions at s=200 GeV. Data were taken with the STAR detector at RHIC. The J/ψ polarization measurement should help to distinguish between different models of the J/ψ production mechanism since they predict different pT dependences of the J/ψ polarization. In this analysis, J/ψ polarization is studied in the helicity frame. The polarization parameter λθ measured at RHIC becomes smaller towards high pT, indicating more longitudinal J/ψ polarization as pT increases. The result is compared with predictions of presently available models