Review article: A comprehensive review of datasets and methodologies employed to produce thunderstorm climatologies

Thunderstorm and lightning climatological research is conducted with a view to increasing knowledge about the distribution of thunderstorm-related hazards and to gain an understanding of environmental factors increasing or decreasing their frequency. There are three main methodologies used in the construction of thunderstorm climatologies: Thunderstorm frequency, thunderstorm tracking or lightning flash density. These approaches utilise a wide variety of underpinning datasets and employ many different methods ranging from correlations with potential influencing factors and mapping the distribution of thunderstorm day frequencies to tracking individual thunderstorm cell movements. Meanwhile, lightning flash density climatologies are produced using lightning data alone, and these studies therefore follow a more standardised format. Whilst lightning flash density climatologies are primarily concerned with the occurrence of cloud-To-ground lightning, the occurrence of any form of lightning confirms the presence of a thunderstorm and can therefore be used in the compilation of a thunderstorm climatology. Regardless of approach, the choice of analysis method is heavily influenced by the coverage and quality (detection efficiency and location accuracy) of available datasets as well as by the controlling factors which are under investigation. The issues investigated must also reflect the needs of the end-use application to ensure that the results can be used effectively to reduce exposure to hazard, improve forecasting or enhance climatological understanding

Atomic Electrons in Strong Magnetic Fields: Transition from Elliptical to Helical Behavior.

The behavior of an atomic electron in a static magnetic field strong enough to correspond to the transition regime is examined. The field strength is characterized by the parameter L^, the effective component of angular momentum. A Floquet-Mathieu analysis shows that the bifurcation of classical trajectories into elliptical and helical families is related to the 2:1 resonance which occurs at L^=L^T. Quantum mechanics gives an avoided crossing at L^T; we examine the nature of the wave functions as L^ passes through the resonance. Semiclassical calculations accurately reproduce the quantum eigenvalues and produce trajectories which underlie the quantum wave functions. The avoided crossing is expressed in semiclassical terms as a switch between elliptical and helical families. The bifurcation of the classical motion means that, at the primitive semiclassical level, some states may be missed and others may be generated in both elliptical and helical representations

Thunderstorm tracking in Northwest Europe for enhanced hazard preparedness

The tracking of thunderstorms provides critical information on their frequency and behaviour for early warning, prediction and preparedness. Thunderstorm tracking has previously been constrained by the boundaries of a particular country or has focused on a particular category such as severe thunderstorms and mesoscale convective systems. However, less severe thunderstorms also pose a risk to life and property and occur more frequently and thus warrant inclusion in investigations of thunderstorm behaviour. In this paper, we present a new thunderstorm event catalogue, including all detected thunderstorms with at least three lightning flashes, derived from a tracking methodology applied to Northwest Europe within the bounds of 48° to 65°N and 15°W to 10°E between 2008 and 2018. The catalogue is based on ATDnet lightning flash data which was clustered into thunderstorms using a spatio-temporal proximity assessment lightning clustering code written in the R coding language. The thunderstorm lightning clusters enabled the production of thunderstorm behaviour statistics such as speed, direction of movement, lightning flashes per minute and duration. This revealed that in winter, thunderstorms are shorter lived and move faster than in summer as well as more typically tracking from the west rather than from the south-west. Thunderstorm behaviour characteristics were attributed to weather pattern types for the first time, providing probabilistic data that can be attributed to synoptic conditions. This can improve preparedness and early warning. Such results demonstrate how this new thunderstorm event catalogue, which includes all types and severities of thunderstorms unconstrained by political boundaries, can provide additional important information to enhance understanding of thunderstorm behaviour in the region. Our lightning clustering method may be useful for similar studies in other locales

Early antenatal prediction of gestational diabetes in obese women: development of prediction tools for targeted intervention

All obese women are categorised as being of equally high risk of gestational diabetes (GDM) whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0–18+6 weeks’ gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR) metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337) developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria). A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios) provided an area under the curve of 0.71 (95%CI 0.68–0.74). This increased to 0.77 (95%CI 0.73–0.80) with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c), fructosamine, adiponectin, sex hormone binding globulin, triglycerides), but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74–0.81). Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value) later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described which could enable targeted interventions for GDM prevention in women who will benefit the most

A randomised controlled trial comparing standard or intensive management of reduced fetal movements after 36 weeks gestation-a feasibility study

BACKGROUND: Women presenting with reduced fetal movements (RFM) in the third trimester are at increased risk of stillbirth or fetal growth restriction. These outcomes after RFM are related to smaller fetal size on ultrasound scan, oligohydramnios and lower human placental lactogen (hPL) in maternal serum. We performed this study to address whether a randomised controlled trial (RCT) of the management of RFM was feasible with regard to: i) maternal recruitment and retention ii) patient acceptability, iii) adherence to protocol. Additionally, we aimed to confirm the prevalence of poor perinatal outcomes defined as: stillbirth, birthweight <10(th) centile, umbilical arterial pH <7.1 or unexpected admission to the neonatal intensive care unit. METHODS: Women with RFM ≥36 weeks gestation were invited to participate in a RCT comparing standard management (ultrasound scan if indicated, induction of labour (IOL) based on consultant decision) with intensive management (ultrasound scan, maternal serum hPL, IOL if either result was abnormal). Anxiety was assessed by state-trait anxiety index (STAI) before and after investigations for RFM. Rates of protocol compliance and IOL for RFM were calculated. Participant views were assessed by questionnaires. RESULTS: 137 women were approached, 120 (88%) participated, 60 in each group, 2 women in the standard group did not complete the study. 20% of participants had a poor perinatal outcome. All women in the intensive group had ultrasound assessment of fetal size and liquor volume vs. 97% in the standard group. 50% of the intensive group had IOL for abnormal scan or low hPL after RFM vs. 26% of controls (p < 0.01). STAI reduced for all women after investigations, but this reduction was greater in the standard group (p = 0.02). Participants had positive views about their involvement in the study. CONCLUSION: An RCT of management of RFM is feasible with a low rate of attrition. Investigations decrease maternal anxiety. Participants in the intensive group were more likely to have IOL for RFM. Further work is required to determine the likely level of intervention in the standard care arm in multiple centres, to develop additional placental biomarkers and to confirm that the composite outcome is valid. TRIAL REGISTRATION: ISRCTN0794430

Meteorites on the Nullarbor Plain, Insights from Synchrotron Powder Diffraction

eid: 1361 adsurl: https://ui.adsabs.harvard.edu/abs/2019LPI....50.1361B adsnote: Provided by the SAO/NASA Astrophysics Data Syste

Multiple Cytokines Are Released When Blood from Patients with Tuberculosis Is Stimulated with Mycobacterium tuberculosis Antigens

Mycobacterium tuberculosis (Mtb) infection may cause overt disease or remain latent. Interferon gamma release assays (IGRAs) detect Mtb infection, both latent infection and infection manifesting as overt disease, by measuring whole-blood interferon gamma (IFN-γ) responses to Mtb antigens such as early secreted antigenic target-6 (ESAT-6), culture filtrate protein 10 (CFP-10), and TB7.7. Due to a lack of adequate diagnostic standards for confirming latent Mtb infection, IGRA sensitivity for detecting Mtb infection has been estimated using patients with culture-confirmed tuberculosis (CCTB) for whom recovery of Mtb confirms the infection. In this study, cytokines in addition to IFN-γ were assessed for potential to provide robust measures of Mtb infection.Cytokine responses to ESAT-6, CFP-10, TB7.7, or combinations of these Mtb antigens, for patients with CCTB were compared with responses for subjects at low risk for Mtb infection (controls). Three different multiplexed immunoassays were used to measure concentrations of 9 to 20 different cytokines. Responses were calculated by subtracting background cytokine concentrations from cytokine concentrations in plasma from blood stimulated with Mtb antigens.Two assays demonstrated that ESAT-6, CFP-10, ESAT-6+CFP-10, and ESAT-6+CFP-10+TB7.7 stimulated the release of significantly greater amounts of IFN-γ, IL-2, IL-8, MCP-1 and MIP-1β for CCTB patients than for controls. Responses to combination antigens were, or tended to be, greater than responses to individual antigens. A third assay, using whole blood stimulation with ESAT-6+CFP-10+TB7.7, revealed significantly greater IFN-γ, IL-2, IL-6, IL-8, IP-10, MCP-1, MIP-1β, and TNF-α responses among patients compared with controls. One CCTB patient with a falsely negative IFN-γ response had elevated responses with other cytokines.Multiple cytokines are released when whole blood from patients with CCTB is stimulated with Mtb antigens. Measurement of multiple cytokine responses may improve diagnostic sensitivity for Mtb infection compared with assessment of IFN-γ alone

Non-destructive analysis of sucrose, caffeine and trigonelline on single green coffee beans by hyperspectral imaging

Hyperspectral imaging (HSI) is a novel technology for the food sector that enables rapid non-contact analysis of food materials. HSI was applied for the first time to whole green coffee beans, at a single seed level, for quantitative prediction of sucrose, caffeine and trigonelline content. In addition, the intra-bean distribution of coffee constituents was analysed in Arabica and Robusta coffees on a large sample set from 12 countries, using a total of 260 samples. Individual green coffee beans were scanned by reflectance HSI (980–2500 nm) and then the concentration of sucrose, caffeine and trigonelline analysed with a reference method (HPLC-MS). Quantitative prediction models were subsequently built using Partial Least Squares (PLS) regression. Large variations in sucrose, caffeine and trigonelline were found between different species and origin, but also within beans from the same batch. It was shown that estimation of sucrose content is possible for screening purposes (R2 = 0.65; prediction error of ~ 0.7% w/w coffee, with observed range of ~ 6.5%), while the performance of the PLS model was better for caffeine and trigonelline prediction (R2 = 0.85 and R2 = 0.82, respectively; prediction errors of 0.2 and 0.1%, on a range of 2.3 and 1.1% w/w coffee, respectively). The prediction error is acceptable mainly for laboratory applications, with the potential application to breeding programmes and for screening purposes for the food industry. The spatial distribution of coffee constituents was also successfully visualised for single beans and this enabled mapping of the analytes across the bean structure at single pixel level