The impact of the ATLAS zero-lepton, jets and missing momentum search on a CMSSM fit

Recent ATLAS data significantly extend the exclusion limits for supersymmetric particles. We examine the impact of such data on global fits of the constrained minimal supersymmetric standard model (CMSSM) to indirect and cosmological data. We calculate the likelihood map of the ATLAS search, taking into account systematic errors on the signal and on the background. We validate our calculation against the ATLAS determinaton of 95% confidence level exclusion contours. A previous CMSSM global fit is then re-weighted by the likelihood map, which takes a bite at the high probability density region of the global fit, pushing scalar and gaugino masses up.Comment: 16 pages, 7 figures. v2 has bigger figures and fixed typos. v3 has clarified explanation of our handling of signal systematic

Coherent states for compact Lie groups and their large-N limits

The first two parts of this article surveys results related to the heat-kernel coherent states for a compact Lie group K. I begin by reviewing the definition of the coherent states, their resolution of the identity, and the associated Segal-Bargmann transform. I then describe related results including connections to geometric quantization and (1+1)-dimensional Yang--Mills theory, the associated coherent states on spheres, and applications to quantum gravity. The third part of this article summarizes recent work of mine with Driver and Kemp on the large-N limit of the Segal--Bargmann transform for the unitary group U(N). A key result is the identification of the leading-order large-N behavior of the Laplacian on "trace polynomials."Comment: Submitted to the proceeding of the CIRM conference, "Coherent states and their applications: A contemporary panorama.

Pre-specification of statistical analysis approaches in published clinical trial protocols was inadequate

OBJECTIVES: Results from randomized trials can depend on the statistical analysis approach used. It is important to prespecify the analysis approach in the trial protocol to avoid selective reporting of analyses based on those which provide the most favourable results. We undertook a review of published trial protocols to assess how often the statistical analysis of the primary outcome was adequately prespecified. METHODS: We searched protocols of randomized trials indexed in PubMed in November 2016. We identified whether the following aspects of the statistical analysis approach for the primary outcome were adequately prespecified: (1) analysis population; (2) analysis model; (3) use of covariates; and (4) method of handling missing data. RESULTS: e identified 99 eligible protocols. Very few protocols adequately prespecified the analysis population (8/99, 8%), analysis model (27/99, 27%), covariates (40/99, 40%), or approach to handling missing data (10/99, 10%). Most protocols did not adequately predefine any of these four aspects of their statistical analysis approach (39%) or predefined only one aspect (36%). No protocols adequately predefined all four aspects of the analysis. CONCLUSION: The statistical analysis approach is rarely prespecified in published trial protocols. This may allow selective reporting of results based on different analyses

Transient stability analysis and enhancement of renewable energy conversion system during LVRT

Grid-connected renewable energy conversion systems (RECSs) are usually required by grid codes to possess the low voltage ride through (LVRT) and reactive power support capabilities so as to cope with grid voltage sags. During LVRT, RECS's terminal voltage becomes sensitive and changeable with its output current, which brings a great challenge for the RECS to resynchronize with the grid by means of phase-locked loops (PLLs). This paper indicates that loss of synchronism (LOS) of PLLs is responsible for the transient instability of grid-connected RECSs during LVRT, and the LOS is essentially due to the transient interaction between the PLL and the weak terminal voltage. For achieving a quantitative analysis, an equivalent swing equation model is developed to describe the transient interaction. Based on the model, the transient instability mechanism of RECSs during LVRT is clarified. Furthermore, a transient stability enhancement method is proposed to avoid the possibility of transient instability. Simulations performed on the New England 39-bus test system verify the effectiveness of the method

Effect of venting range hood flow rate on size-resolved ultrafine particle concentrations from gas stove cooking

Cooking is the main source of ultrafine particles (UFP) in homes. This study investigated the effect of venting range hood flow rate on size-resolved UFP concentrations from gas stove cooking. The same cooking protocol was conducted 60 times using three venting range hoods operated at six flow rates in twin research houses. Size-resolved particle (10–420 nm) concentrations were monitored using a NanoScan scanning mobility particle sizer (SMPS) from 15 min before cooking to 3 h after the cooking had stopped. Cooking increased the background total UFP number concentrations to 1.3 × 103 particles/cm3 on average, with a mean exposure-relevant source strength of 1.8 × 1012 particles/min. Total particle peak reductions ranged from 25% at the lowest fan flow rate of 36 L/s to 98% at the highest rate of 146 L/s. During the operation of a venting range hood, particle removal by deposition was less significant compared to the increasing air exchange rate driven by exhaust ventilation. Exposure to total particles due to cooking varied from 0.9 to 5.8 × 104 particles/cm3·h, 3 h after cooking ended. Compared to the 36 L/s range hood, higher flow rates of 120 and 146 L/s reduced the first-hour post-cooking exposure by 76% and 85%, respectively. © 2018 Crown Copyright. Published with license by Taylor & Francis Group, LLC

Sixteen years of bathymetry and waves at San Diego beaches.

Sustained, quantitative observations of nearshore waves and sand levels are essential for testing beach evolution models, but comprehensive datasets are relatively rare. We document beach profiles and concurrent waves monitored at three southern California beaches during 2001-2016. The beaches include offshore reefs, lagoon mouths, hard substrates, and cobble and sandy (medium-grained) sediments. The data span two energetic El Niño winters and four beach nourishments. Quarterly surveys of 165 total cross-shore transects (all sites) at 100 m alongshore spacing were made from the backbeach to 8 m depth. Monthly surveys of the subaerial beach were obtained at alongshore-oriented transects. The resulting dataset consists of (1) raw sand elevation data, (2) gridded elevations, (3) interpolated elevation maps with error estimates, (4) beach widths, subaerial and total sand volumes, (5) locations of hard substrate and beach nourishments, (6) water levels from a NOAA tide gauge (7) wave conditions from a buoy-driven regional wave model, and (8) time periods and reaches with alongshore uniform bathymetry, suitable for testing 1-dimensional beach profile change models

A Profile Likelihood Analysis of the Constrained MSSM with Genetic Algorithms

The Constrained Minimal Supersymmetric Standard Model (CMSSM) is one of the simplest and most widely-studied supersymmetric extensions to the standard model of particle physics. Nevertheless, current data do not sufficiently constrain the model parameters in a way completely independent of priors, statistical measures and scanning techniques. We present a new technique for scanning supersymmetric parameter spaces, optimised for frequentist profile likelihood analyses and based on Genetic Algorithms. We apply this technique to the CMSSM, taking into account existing collider and cosmological data in our global fit. We compare our method to the MultiNest algorithm, an efficient Bayesian technique, paying particular attention to the best-fit points and implications for particle masses at the LHC and dark matter searches. Our global best-fit point lies in the focus point region. We find many high-likelihood points in both the stau co-annihilation and focus point regions, including a previously neglected section of the co-annihilation region at large m_0. We show that there are many high-likelihood points in the CMSSM parameter space commonly missed by existing scanning techniques, especially at high masses. This has a significant influence on the derived confidence regions for parameters and observables, and can dramatically change the entire statistical inference of such scans.Comment: 47 pages, 8 figures; Fig. 8, Table 7 and more discussions added to Sec. 3.4.2 in response to referee's comments; accepted for publication in JHE

Optimizing the computation of overriding

We introduce optimization techniques for reasoning in DLN---a recently introduced family of nonmonotonic description logics whose characterizing features appear well-suited to model the applicative examples naturally arising in biomedical domains and semantic web access control policies. Such optimizations are validated experimentally on large KBs with more than 30K axioms. Speedups exceed 1 order of magnitude. For the first time, response times compatible with real-time reasoning are obtained with nonmonotonic KBs of this size

On SUSY GUTs with a degenerate Higgs mass matrix

Certain supersymmetric grand unified models predict that the coefficients of the quadratic terms in the MSSM Higgs potential should be degenerate at the GUT scale. We discuss some examples for such models, and we analyse the implications of this peculiar condition of a GUT-scale degenerate Higgs mass matrix for low-scale MSSM phenomenology. To this end we explore the parameter space which is consistent with existing experimental constraints by means of a Markov Chain Monte Carlo analysis.Comment: 31 pages, 27 figures; v2: typos correcte

Eurasian Arctic greening reveals teleconnections and the potential for novel ecosystems

Arctic warming has been linked to observed increases in tundra shrub cover and growth in recent decades on the basis of significant relationships between deciduous shrub growth/biomass and temperature. These vegetation trends have been linked to Arctic sea ice decline and thus to the sea ice/albedo feedback known as Arctic amplification. However, the interactions between climate, sea ice and tundra vegetation remain poorly understood. Here we reveal a 50- year growth response over a >100,000 km2 area to a rise in summer temperature for alder (Alnus) and willow (Salix), the most abundant shrub genera respectively at and north of the continental treeline. We demonstrate that whereas plant productivity is related to sea ice in late spring, the growing season peak responds to persistent synoptic-scale air masses over West Siberia associated with Fennoscandian weather systems through the Rossby wave train. Substrate is important for biomass accumulation, yet a strong correlation between growth and temperature encompasses all observed soil types. Vegetation is especially responsive to temperature in early summer. These results have significant implications for modelling present and future Low Arctic vegetation responses to climate change, and emphasize the potential for structurally novel ecosystems to emerge fromwithin the tundra zone.Vertaisarviointia edeltävä käsikirjoitu