Correlated Lightning Mapping Array (LMA) and Radar Observations of the Initial Stages of Florida Triggered Lightning Discharges

We characterize the geometrical and electrical characteristics of the initial stages of nine Florida triggered lightning discharges using a Lightning Mapping Array (LMA), a C-band SMART radar, and measured channel-base currents. We determine initial channel and subsequent branch lengths, average initial channel and branch propagation speeds, and channel-base current at the time of each branch initiation. The channel-base current is found to not change significantly when branching occurs, an unexpected result. The initial stage of Florida triggered lightning typically transitions from vertical to horizontal propagation at altitudes of 3-6 km, near the typical 0 C level of 4-5 km and several kilometers below the expected center of the negative cloud-charge region at 7-8 km. The data presented potentially provide information on thunderstorm electrical and hydrometeor structure and discharge propagation physics. LMA source locations were obtained from VHF sources of positive impulsive currents as small as 10 A, in contrast to expectations found in the literature

A universally applicable method of operon map prediction on minimally annotated genomes using conserved genomic context.

An important step in understanding the regulation of a prokaryotic genome is the generation of its transcription unit map. The current strongest operon predictor depends on the distributions of intergenic distances (IGD) separating adjacent genes within and between operons. Unfortunately, experimental data on these distance distributions are limited to Escherichia coli and Bacillus subtilis. We suggest a new graph algorithmic approach based on comparative genomics to identify clusters of conserved genes independent of IGD and conservation of gene order. As a consequence, distance distributions of operon pairs for any arbitrary prokaryotic genome can be inferred. For E.coli, the algorithm predicts 854 conserved adjacent pairs with a precision of 85%. The IGD distribution for these pairs is virtually identical to the E.coli operon pair distribution. Statistical analysis of the predicted pair IGD distribution allows estimation of a genome-specific operon IGD cut-off, obviating the requirement for a training set in IGD-based operon prediction. We apply the method to a representative set of eight genomes, and show that these genome-specific IGD distributions differ considerably from each other and from the distribution in E.coli

D6.7 Report on the experience of conducting the case studies

One of the main aims of the case studies was to publish improved market reports. The data collected as part of the six case studies have been, or will shortly be, published in the five improved national organic market reports and one first regional market report (MOAN case study). This will make a contribution towards filling the many gaps that continue to exist in organic market data collection in Europe

Gene Function Classification Using Bayesian Models with Hierarchy-Based Priors

We investigate the application of hierarchical classification schemes to the annotation of gene function based on several characteristics of protein sequences including phylogenic descriptors, sequence based attributes, and predicted secondary structure. We discuss three Bayesian models and compare their performance in terms of predictive accuracy. These models are the ordinary multinomial logit (MNL) model, a hierarchical model based on a set of nested MNL models, and a MNL model with a prior that introduces correlations between the parameters for classes that are nearby in the hierarchy. We also provide a new scheme for combining different sources of information. We use these models to predict the functional class of Open Reading Frames (ORFs) from the E. coli genome. The results from all three models show substantial improvement over previous methods, which were based on the C5 algorithm. The MNL model using a prior based on the hierarchy outperforms both the non-hierarchical MNL model and the nested MNL model. In contrast to previous attempts at combining these sources of information, our approach results in a higher accuracy rate when compared to models that use each data source alone. Together, these results show that gene function can be predicted with higher accuracy than previously achieved, using Bayesian models that incorporate suitable prior information

Neurology Case Reporting: a call for all

From antiquity to present day, the act of recording and publishing our observations with patients remains essential to the art of medicine and the care of patients. Neurology is rich with case reports over the centuries. They contribute to our understanding and knowledge of disease entities, and are a cornerstone of our professional development as physicians and the care of our patients. This editorial seeks to enthuse and invigorate house staff and practicing physicians everywhere to continue the long and time-honored tradition of neurology case reporting

Defining functional distances over Gene Ontology

<p>Abstract</p> <p>Background</p> <p>A fundamental problem when trying to define the functional relationships between proteins is the difficulty in quantifying functional similarities, even when well-structured ontologies exist regarding the activity of proteins (i.e. 'gene ontology' -GO-). However, functional metrics can overcome the problems in the comparing and evaluating functional assignments and predictions. As a reference of proximity, previous approaches to compare GO terms considered linkage in terms of ontology weighted by a probability distribution that balances the non-uniform 'richness' of different parts of the Direct Acyclic Graph. Here, we have followed a different approach to quantify functional similarities between GO terms.</p> <p>Results</p> <p>We propose a new method to derive 'functional distances' between GO terms that is based on the simultaneous occurrence of terms in the same set of Interpro entries, instead of relying on the structure of the GO. The coincidence of GO terms reveals natural biological links between the GO functions and defines a distance model <it>D</it>_{<it>f </it>}which fulfils the properties of a Metric Space. The distances obtained in this way can be represented as a hierarchical 'Functional Tree'.</p> <p>Conclusion</p> <p>The method proposed provides a new definition of distance that enables the similarity between GO terms to be quantified. Additionally, the 'Functional Tree' defines groups with biological meaning enhancing its utility for protein function comparison and prediction. Finally, this approach could be for function-based protein searches in databases, and for analysing the gene clusters produced by DNA array experiments.</p

Timing Calibration and Windowing Technique Comparison for Lightning Mapping Arrays

Since their introduction 22 years ago, lightning mapping arrays (LMA) have played a central role in the investigation of lightning physics. Even in recent years with the proliferation of digital interferometers and the introduction of the LOw Frequency ARray (LOFAR) radio telescope, LMAs still play an important role in lightning science. LMA networks use a simple windowing technique that records the highest pulse in either 80 μs or 10 μs fixed windows in order to apply a time-of-arrival location technique. In this work, we develop an LMA-emulator that uses lightning data recorded by LOFAR to simulate an LMA, and we use it to test three new styles of pulse windowing. We show that they produce very similar results as the more traditional LMA windowing, implying that LMA lightning mapping results are relatively independent of windowing technique. In addition, each LMA station has its GPS-conditioned clock. While the timing accuracy of GPS receivers has improved significantly over the years, they still significantly limit the timing measurements of the LMA. Recently, new time-of-arrival techniques have been introduced that can be used to self-calibrate systematic offsets between different receiving stations. Applying this calibration technique to a set of data with 32 ns uncertainty, observed by the Colorado LMA, improves the timing uncertainty to 19 ns. This technique is not limited to LMAs and could be used to help calibrate future multi-station lightning interferometers

Observations of the Origin of Downward Terrestrial Gamma-Ray Flashes

In this paper we report the first close, high-resolution observations of downward-directed terrestrial gamma-ray flashes (TGFs) detected by the large-area Telescope Array cosmic ray observatory, obtained in conjunction with broadband VHF interferometer and fast electric field change measurements of the parent discharge. The results show that the TGFs occur during strong initial breakdown pulses (IBPs) in the first few milliseconds of negative cloud-to-ground and low-altitude intracloud flashes and that the IBPs are produced by a newly identified streamer-based discharge process called fast negative breakdown. The observations indicate the relativistic runaway electron avalanches (RREAs) responsible for producing the TGFs are initiated by embedded spark-like transient conducting events (TCEs) within the fast streamer system and potentially also by individual fast streamers themselves. The TCEs are inferred to be the cause of impulsive sub-pulses that are characteristic features of classic IBP sferics. Additional development of the avalanches would be facilitated by the enhanced electric field ahead of the advancing front of the fast negative breakdown. In addition to showing the nature of IBPs and their enigmatic sub-pulses, the observations also provide a possible explanation for the unsolved question of how the streamer to leader transition occurs during the initial negative breakdown, namely, as a result of strong currents flowing in the final stage of successive IBPs, extending backward through both the IBP itself and the negative streamer breakdown preceding the IBP