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The third observing season of PhOCAL (Physical Origins of Coupling to the upper Atmosphere by Lightning) was conducted over the U.S. High Plains during the late spring and summer of 2013. The goal was to capture using an intensified high-speed camera, a transient luminous event (TLE), especially a sprite, as well as its parent cloud-to-ground (SP+CG) lightning discharge, preferably within the domain of a 3-D lightning mapping array (LMA). The co-capture of sprite and its SP+CG was achieved within useful range of an interferometer operating near Rapid City. Other high-speed sprite video sequences were captured above the West Texas LMA. On several occasions the large mesoscale convective complexes (MCSs) producing the TLE-class lightning were also generating vertically propagating convectively generated gravity waves (CGGWs) at the mesopause which were easily visible using NIR-sensitive color cameras. These were captured concurrent with sprites. These observations were follow-ons to a case on 15 April 2012 in which CGGWs were also imaged by the new Day/Night Band on the Suomi NPP satellite system. The relationship between the CGGW and sprite initiation are being investigated. The past year was notable for a large number of elve+halo+sprite sequences sequences generated by the same parent CG. And on several occasions there appear to be prominent banded modulations of the elves' luminosity imaged at >3000 ips. These stripes appear coincident with the banded CGGW structure, and presumably its density variations. Several elves and a sprite from negative CGs were also noted. New color imaging systems have been tested and found capable of capturing sprites. Two cases of sprites with an aurora as a backdrop were also recorded. High speed imaging was also provided in support of the UPLIGHTS program near Rapid City, SD and the USAFA SPRITES II airborne campaign over the Great Plains.

\"Weather can be wild, freaky, and fascinating! Powerful twisters roar through homes; earthquakes shatter whole cities; hurricanes fly through towns. How does it all happen and how do we know what we do? All you need to know about weather and all of its wildness will be found in the pages of this colorful, energetic, and accessible book. Kids will also learn about real-life encounters with wild weather from National Geographic tornado chaser, Tim Samaras, featured in 'Explorer's Corners' throughout the book. Packed with fun facts and amazing photographs, this book gives kids an in-depth look at these amazing natural phenomena\"-- Provided by publisher.

Tornado research projects such as VORTEX 2 (Verification of the Origins of Rotation in Tornadoes Experiment 2), TWISTEX (Tactical Weatiier-Instrumented Sampling in/near Tornadoes/Thunderstorms Experiment), and others are trying to answer diese questions. On May 15, 2003, as I deployed one instrument in the padi of a tornado moving tiirough the northwest comer of the Texas Panhandle, Joshua Wurman of the Center for Severe Weatiier Research was running his mobile radar equipment on the same tornado at the same time several miles away.

\"To understand lightning, you have to start with a storm cloud. It is made of tiny water droplets and ice crystals. The water droplets and ice crystals zip and zoom around inside the cloud, banging into one another. This creates electric charges.\" (National Geographic Explorer!) Learn how lightning works. A quiz is included.

The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets. The number of publicly available proteomics datasets is growing rapidly, but a standardized approach for describing the associated metadata is lacking. Here, the authors propose a format and a software pipeline to present and validate metadata, and integrate them into ProteomeXchange repositories.

Four regional chemistry transport models were applied to simulate the concentration and composition of particulate matter (PM) in Europe for 2005 with horizontal resolution  ∼  20 km. The modelled concentrations were compared with the measurements of PM chemical composition by the European Monitoring and Evaluation Programme (EMEP) monitoring network. All models systematically underestimated PM10 and PM2.5 by 10–60 %, depending on the model and the season of the year, when the calculated dry PM mass was compared with the measurements. The average water content at laboratory conditions was estimated between 5 and 20 % for PM2.5 and between 10 and 25 % for PM10. For majority of the PM chemical components, the relative underestimation was smaller than it was for total PM, exceptions being the carbonaceous particles and mineral dust. Some species, such as sea salt and NO3−, were overpredicted by the models. There were notable differences between the models' predictions of the seasonal variations of PM, mainly attributable to different treatments or omission of some source categories and aerosol processes. Benzo(a)pyrene concentrations were overestimated by all the models over the whole year. The study stresses the importance of improving the models' skill in simulating mineral dust and carbonaceous compounds, necessity for high-quality emissions from wildland fires, as well as the need for an explicit consideration of aerosol water content in model–measurement comparison.

To investigate 1). associations between environmental factors (alcohol consumption, hormone replacement therapy [HRT], and physical activity) and insulin resistance and secretion, independent of genetic influences; 2). the contribution of abdominal adiposity to these relationships; and 3). whether gene-environment interactions mediate these associations. Reported effects of lifestyle factors on insulin resistance and secretion are inconsistent, possibly due to difficulty in dissecting environmental from genetic influences and to confounding by adiposity. We examined these relationships in 798 nondiabetic female twins. Insulin resistance and secretion were estimated by modified homeostasis model assessment (HOMA-R' and HOMA-beta', respectively). Percent total body fat and percent central abdominal fat (CAF) were measured by dual-energy X-ray absorptiometry. All categories of alcohol consumption were associated with lower insulin levels and HOMA-beta' than abstinence. Only moderate alcohol consumers (11-20 units/week) had lower HOMA-R' than abstainers (-0.16 +/- 0.09 vs. 0.14 +/- 0.13 SD, P = 0.048). This difference was attenuated after controlling for percent CAF (P = 0.57), which was lower in moderate drinkers. Controlling for genetic and smoking effects in cotwin case-control analysis, monozygotic pairs discordant for alcohol consumption had greater within-pair differences in HOMA-R' than concordant pairs (P = 0.02). Postmenopausal women using estrogen-only HRT had lower HOMA-R' than non-HRT users (-0.33 +/- 0.16 vs. 0.17 +/- 0.08 SD, P = 0.003), even after controlling for percent CAF. Lower fasting glucose levels and insulin resistance and secretion indexes in physically active subjects were partly explained by lower abdominal adiposity. Moderate alcohol consumption, estrogen replacement, and physical activity are associated with increased insulin sensitivity in female twins. The favorable effects of moderate alcohol consumption and physical activity on insulin sensitivity are partly mediated by lower abdominal adiposity.

Moderate Alcohol Consumption, Estrogen Replacement Therapy, and Physical Activity Are Associated With Increased Insulin Sensitivity Is abdominal adiposity the mediator? Jerry R. Greenfield , MBBS, BSC (MED), FRACP 1 , Katherine Samaras , MBBS, PHD, FRACP 1 , Arthur B. Jenkins , BSC, PHD 2 , Paul J. Kelly , MBBS, MD, FRACP 3 , Tim D. Spector , MSC, MD, FRCP 4 and Lesley V. Campbell , MBBS, FRCP, FRACP 1 5 1 Department of Endocrinology, St. Vincent’s Hospital, Sydney, Australia 2 Department of Biomedical Science, University of Wollongong, Wollongong, Australia 3 Sequenom, Inc., San Diego, California 4 Twin Research and Genetic Epidemiology Unit, St. Thomas’ Hospital, London, U.K 5 Diabetes Centre, St. Vincent’s Hospital, Sydney, Australia Address correspondence and reprint requests to Prof. Lesley Campbell, St. Vincent’s Hospital, Victoria St., Darlinghurst, 2010, Sydney, Australia. E-mail: l.campbell{at}garvan.org.au Abstract OBJECTIVE —To investigate 1 ) associations between environmental factors (alcohol consumption, hormone replacement therapy [HRT], and physical activity) and insulin resistance and secretion, independent of genetic influences; 2 ) the contribution of abdominal adiposity to these relationships; and 3 ) whether gene-environment interactions mediate these associations. RESEARCH DESIGN AND METHODS —Reported effects of lifestyle factors on insulin resistance and secretion are inconsistent, possibly due to difficulty in dissecting environmental from genetic influences and to confounding by adiposity. We examined these relationships in 798 nondiabetic female twins. Insulin resistance and secretion were estimated by modified homeostasis model assessment (HOMA-R′ and HOMA-β′, respectively). Percent total body fat and percent central abdominal fat (CAF) were measured by dual-energy X-ray absorptiometry. RESULTS —All categories of alcohol consumption were associated with lower insulin levels and HOMA-β′ than abstinence. Only moderate alcohol consumers (11–20 units/week) had lower HOMA-R′ than abstainers (−0.16 ± 0.09 vs. 0.14 ± 0.13 SD, P = 0.048). This difference was attenuated after controlling for percent CAF ( P = 0.57), which was lower in moderate drinkers. Controlling for genetic and smoking effects in cotwin case-control analysis, monozygotic pairs discordant for alcohol consumption had greater within-pair differences in HOMA-R′ than concordant pairs ( P = 0.02). Postmenopausal women using estrogen-only HRT had lower HOMA-R′ than non–HRT users (−0.33 ± 0.16 vs. 0.17 ± 0.08 SD, P = 0.003), even after controlling for percent CAF. Lower fasting glucose levels and insulin resistance and secretion indexes in physically active subjects were partly explained by lower abdominal adiposity. CONCLUSIONS —Moderate alcohol consumption, estrogen replacement, and physical activity are associated with increased insulin sensitivity in female twins. The favorable effects of moderate alcohol consumption and physical activity on insulin sensitivity are partly mediated by lower abdominal adiposity. CAF, central abdominal fat FPG, fasting plasma glucose FPI, fasting plasma insulin HOMA, homeostasis model assessment HRT, hormone replacement therapy WHR, waist-to-hip ratio Footnotes A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. P.J.K. serves on the board of directors of AgaMatrix, Inc.. Accepted June 21, 2003. Received May 9, 2003. DIABETES CARE

The amount of public proteomics data is increasing at an extraordinary rate. Hundreds of datasets are submitted each month to ProteomeXchange repositories, representing many types of proteomics studies, focusing on different aspects such as quantitative experiments, post-translational modifications, protein-protein interactions, or subcellular localization, among many others. For every proteomics dataset, two levels of data are captured: the dataset description, and the data files (encoded in different file formats). Whereas the dataset description and data file formats are supported by all ProteomeXchange partner repositories, there is no standardized format to properly describe the sample metadata and their relationship with the dataset files in a way that fully allows their understanding or re-analysis. It is left to the user’s choice whether to provide or not an ad hoc document containing this information. Therefore, in many cases, understanding the study design and data requires going back to the associated publication. This can be tedious and may be restricted in the case of non-open access publications. In many cases, this problem limits the generalization and reuse of public proteomics data. Here we present a standard representation for sample metadata tailored to proteomics datasets produced by the HUPO Proteomics Standards Initiative and supported by ProteomeXchange resources. We repurposed the existing data format MAGE-TAB used routinely in the transcriptomics field to represent and annotate proteomics datasets. MAGETAB-Proteomics defines a set of annotation rules that the datasets submitted to ProteomeXchange should follow, ranging from sample properties to data analysis protocols. We also introduce a crowdsourcing project that enabled the manual curation of over 200 public datasets using MAGE-TAB-Proteomics. In addition, we describe an ecosystem of tools and libraries that were developed to validate and submit sample metadata-related information to ProteomeXchange. We expect that these tools will improve the reproducibility of published results and facilitate the reanalysis and integration of public proteomics datasets.