On the Association of Substorm Identification Methods

Substorms are a rapid release of energy that is redistributed throughout the magnetosphere‐ionosphere system, resulting in many observable signals, such as enhancements in the aurora, energetic particle injections, and ground magnetic field perturbations. Numerous substorm identification techniques and onset lists based on each of these signals have been provided in the literature, but often with no cross‐calibration. Since the signals produced are not necessarily unique to substorms and may not be sufficiently similar to be identified for each and every substorm, individual event lists may miss or misidentify substorms, hindering our understanding and the development and validation of substorm models. To gauge the scale of this problem, we use metrics derived from contingency tables to quantify the association between lists of substorms derived from Super MAG SML/SMU indices, midlatitude magnetometer data, particle injections, and auroral enhancements. Overall, although some degree of pairwise association is found between the lists, even lists generated by applying conceptually similar gradient‐based identification to ground magnetometer data achieve an association with less than 50% event coincidence. We discuss possible explanations of the levels of association seen from our results, as well as their implications for substorm analyses

Forecasting GOES 15 >2 MeV electron fluxes from solar wind data and geomagnetic indices

The flux of > 2 MeV electrons at geosynchronous orbit is used by space weather forecasters as a key indicator of enhanced risk of damage to spacecraft in low, medium or geosynchronous Earth orbits. We present a methodology that uses the amount of time a single input dataset (solar wind data or geomagnetic indices) exceeds a given threshold to produce deterministic and probabilistic forecasts of the > 2 MeV flux at GEO exceeding 1000 or 10000 cm‐2 s‐1 sr‐1 within up to 10 days. By comparing our forecasts with measured fluxes from GOES 15 between 2014 and 2016, we determine the optimum forecast thresholds for deterministic and probabilistic forecasts by maximising the ROC and Brier Skill Scores respectively. The training dataset gives peak ROC scores of 0.71 to 0.87 and peak Brier Skill Scores of ‐0.03 to 0.32. Forecasts from AL give the highest skill scores for forecasts of up to 6‐days. AL, solar wind pressure or SYM‐H give the highest skill scores over 7‐10 days. Hit rates range over 56‐89% with false alarm rates of 11‐53%. Applied to 2012, 2013 and 2017, our best forecasts have hit rates of 56‐83% and false alarm rates of 10‐20%. Further tuning of the forecasts may improve these. Our hit rates are comparable to those from operational fluence forecasts, that incorporate fluence measurements, but our false alarm rates are higher. This proof‐of‐concept shows that the geosynchronous electron flux can be forecast with a degree of success without incorporating a persistence element into the forecasts

Influence of Organic Acids on Diltiazem HCl Release Kinetics from Hydroxypropyl Methyl Cellulose Matrix Tablets

The matrix tablets of diltiazem hydrochloride were prepared by direct compression using hydroxypropyl methyl cellulose (HPMC) and various amounts (2.5%, 5.0%, 10% and 20%) of citric acid, malic acid and succinic acid. The characterization of physical mixture of drug and organic acids was performed by Infra-red spectroscopy. An organic acid was incorporated to set up a system bringing about gradual release of this drug. The influence of organic acids on the release rate were described by the Peppas equation: M t /M∞ = Kt n and Higuchi’s equation: Q t = K1t1/2. The addition of organic acids and the pH value of medium could notably influence the dissolution behavior and mechanism of drug-release from matrices. Increasing amounts of organic acid produced an increase in drug release rate, which showed a good linear relationship between contents of organic acid and drug accumulate release (%) in phosphate buffer, pH 7.4. The drug release increased significantly (P < 0.05) with use of succinic acid in tablet formulation. Increasing amounts of succinic acid above 10% produced decreasing values of n and increasing values of k, in a linear relationship, which indicated there was a burst release of drug from the matrix. Optimized formulations are found to be stable upon 3-month study

Evaluating auroral forecasts against satellite observations

The aurora is a readily visible phenomenon of interest to many members of the public. However, the aurora and associated phenomena can also significantly impact communications, ground-based infrastructure, and high-altitude radiation exposure. Forecasting the location of the auroral oval is therefore a key component of space weather forecast operations. A version of the OVATION-Prime 2013 auroral precipitation model (Newell et al., 2014, https://doi.org/10.1002/2014sw001056) was used by the UK Met Office Space Weather Operations Centre (MOSWOC). The operational implementation of the OVATION-Prime 2013 model at the UK Met Office delivered a 30-min forecast of the location of the auroral oval and the probability of observing the aurora. Using weather forecast evaluation techniques, we evaluate the ability of the OVATION-Prime 2013 model forecasts to predict the location and probability of the aurora occurring by comparing the forecasts with auroral boundaries determined from data from the IMAGE satellite between 2000 and 2002. Our analysis shows that the operational model performs well at predicting the location of the auroral oval, with a relative operating characteristic (ROC) score of 0.82. The model performance is reduced in the dayside local time sectors (ROC score = 0.59) and during periods of higher geomagnetic activity (ROC score of 0.55 for Kp = 8). As a probabilistic forecast, OVATION-Prime 2013 tends to underpredict the occurrence of aurora by a factor of 1.1–6, while probabilities of over 90% are overpredicted

Evaluating Auroral Forecasts Against Satellite Observations Under Different Levels of Geomagnetic Activity

The aurora and associated high energy particles and currents pose a space weather hazard to communication networks and ground-based infrastructure. Forecasting the location of the auroral oval forms an integral component of daily space weather operations. We evaluate a version of the OVATION-Prime 2013 auroral forecast model that was implemented for operational use at the UK Met Office Space Weather Operations Cent. Building on our earlier studies, we evaluate the ability of the OVATION-Prime 2013 model to predict the location of the auroral oval in all latitude and local time sectors under different levels of geomagnetic activity, defined by Kp. We compare the model predictions against auroral boundaries determined from IMAGE FUV data. Our analysis shows that the model performs well at predicting the equatorward extent of the auroral oval, particularly as the equatorward auroral boundary expands to lower latitudes for increasing Kp levels. The model performance is reduced in the high latitude region near the poleward auroral boundary, particularly in the nightside sectors where the model does not accurately capture the expansion and contraction of the polar cap as the open flux content of the magnetosphere changes. For increasing levels of geomagnetic activity (Kp ≥ 3), the performance of the model decreases, with the poleward edge of the auroral oval typically observed at lower latitudes than forecast. As such, the forecast poleward edge of the auroral oval is less reliable during more active and hazardous intervals

A connectome and analysis of the adult Drosophila central brain

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the fly’s brain

Velocity-space sensitivity of the time-of-flight neutron spectrometer at JET

The velocity-space sensitivities of fast-ion diagnostics are often described by so-called weight functions. Recently, we formulated weight functions showing the velocity-space sensitivity of the often dominant beam-target part of neutron energy spectra. These weight functions for neutron emission spectrometry (NES) are independent of the particular NES diagnostic. Here we apply these NES weight functions to the time-of-flight spectrometer TOFOR at JET. By taking the instrumental response function of TOFOR into account, we calculate time-of-flight NES weight functions that enable us to directly determine the velocity-space sensitivity of a given part of a measured time-of-flight spectrum from TOFOR

Search for leptophobic Z ' bosons decaying into four-lepton final states in proton-proton collisions at root s=8 TeV

Peer reviewe

Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

Peer reviewe