Current driven electrostatic and electromagnetic ion cyclotron instabilities

Growth rates and parameter dependences are calculated for the current driven instabilities of electrostatic (with finite-beta corrections) and electromagnetic ion cyclotron waves. For 0.25 (T sub e)/(T sub i) 2.5, ion cyclotron waves have large growth rates, while ion acoustic waves are still stable. In fusion devices, where electrostatic waves may be stable, electromagnetic ion cyclotron waves are unstable for beta sub i 0.001

Influence of the Lower Hybrid Drift Instability on the onset of Magnetic Reconnection

Two-dimensional and three-dimensional kinetic simulation results reveal the importance of the Lower-Hybrid Drift Instability LHDI to the onset of magnetic reconnection. Both explicit and implicit kinetic simulations show that the LHDI heats electrons anisotropically and increases the peak current density. Linear theory predicts these modifications can increase the growth rate of the tearing instability by almost two orders of magnitude and shift the fastest growing modes to significantly shorter wavelengths. These predictions are confirmed by nonlinear kinetic simulations in which the growth and coalescence of small scale magnetic islands leads to a rapid onset of large scale reconnection

Cross-cultural adaptation and validation of the “spinal cord injury-falls concern scale” in the Italian population

Study design: Psychometrics study. Objective: The objective of this study was to develop an Italian version of the Spinal Cord Injury-Falls Concern Scale (SCI-FCS) and examine its reliability and validity. Setting: Multicenter study in spinal units in Northern and Southern Italy. The scale also was administered to non-hospitalized outpatient clinic patients. Methods: The original scale was translated from English to Italian using the “Translation and Cultural Adaptation of Patient-Reported Outcomes Measures” guidelines. The reliability and validity of the culturally adapted scale were assessed following the “Consensus-Based Standards for the Selection of Health Status Measurement Instruments” checklist. The SCI-FCS-I internal consistency, inter-rater, and intra-rater reliability were examined using Cronbach’s alpha coefficient and the intraclass correlation coefficient, respectively. Concurrent validity was evaluated using Pearson’s correlation coefficient with the Italian version of the short form of the Wheelchair Use Confidence Scale for Manual Wheelchair Users (WheelCon-M-I-short form). Results: The Italian version of the SCI-FCS-I was administered to 124 participants from 1 June to 30 September 2017. The mean ± SD of the SCI-FCS-I score was 16.73 ± 5.88. All SCI-FCS items were either identical or similar in meaning to the original version’s items. Cronbach’s α was 0.827 (p < 0.01), the inter-rater reliability was 0.972 (p < 0.01), and the intra-rater reliability was 0.973 (p < 0.01). Pearson’s correlation coefficient of the SCI-FCS-I scores with the WheelCon-M-I-short form was 0.56 (p < 0.01). Conclusions: The SCI-FCS-I was found to be reliable and a valid outcome measure for assessing manual wheelchair concerns about falling in the Italian population

Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper

Orthology assignment is ideally suited for functional inference. However, because predicting orthology is computationally intensive at large scale, and most pipelines relatively inaccessible, less precise homology-based functional transfer is still the default for (meta-)genome annotation. We therefore developed eggNOG-mapper, a tool for functional annotation of large sets of sequences based on fast orthology assignments using precomputed clusters and phylogenies from eggNOG. To validate our method, we benchmarked Gene Ontology predictions against two widely used homology-based approaches: BLAST and InterProScan. Compared to BLAST, eggNOG-mapper reduced by 7% the rate of false positive assignments, and increased by 19% the ratio of curated terms recovered over all terms assigned per protein. Compared to InterProScan, eggNOG-mapper achieved similar proteome coverage and precision, while predicting on average 32 more terms per protein and increasing by 26% the rate of curated terms recovered over total term assignments per protein. Through strict orthology assignments, eggNOG-mapper further renders more specific annotations than possible from domain similarity only (e.g. predicting gene family names). eggNOG-mapper runs ~15x than BLAST and at least 2.5x faster than InterProScan. The tool is available standalone or as an online service at http://eggnog-mapper.embl.de

TeleMed: An example of a new system developed with object technology

Los Alamos National Laboratory has developed a virtual patient record system called TeleMed which is based on a distributed national radiographic and patient record repository located throughout the country. Without leaving their offices, participating doctors can view clinical drug and radiographic data via a sophisticated multimedia interface. For example, a doctor can match a patient`s radiographic information with the data in the repository, review treatment history and success, and then determine the best treatment. Furthermore, the features of TeleMed that make it attractive to clinicians and diagnosticians make it valuable for teaching and presentation as well. Thus, a resident can use TeleMed for self-training in diagnostic techniques and a physician can use it to explain to a patient the course of their illness. In fact, the data can be viewed simultaneously by users at two or more distant locations for consultation with specialists in different fields. This capability is of enormous value to a wide spectrum of healthcare providers. It is made possible by the integration of multimedia information using commercial CORBA technology linking object-enabled databases with client interfaces using a three-tiered architecture

Antibiotic resistance genes in river biofilms: a metagenomic approach toward the identification of sources and candidate hosts

Treated wastewater is a major pathway by which antibiotic resistance genes (ARG) enter aquatic ecosystems. However, knowledge gaps remain concerning the dissemination of specific ARG and their association with bacterial hosts. Here, we employed shotgun metagenomics to track ARG and taxonomic markers in river biofilms along a gradient of fecal pollution depicted by crAssphage signatures. We found strong evidence for an impact of wastewater effluents on both community composition and resistomes. In the light of such simultaneity, we employed a model comparison technique to identify ARG-host relationships from nonassembled metagenomic DNA. Hereby, a major cause of spurious associations otherwise encountered in correlation-based ARG-host analyses was suppressed. For several families of ARG, namely those conferring resistance to beta-lactams, particular bacterial orders were identified as candidate hosts. The found associations of (bla)FOX and (cpf)A with Aeromonadales or (bla)PER with Chromatiales support the outcome of independent evolutionary analyses and thus confirm the potential of the methodology. For other ARG families including (bla)IMP or (tet), clusters of bacterial orders were identified which potentially harbor a major proportion of host species. For yet other ARG, like, for example, ant or erm, no particular host candidates were identifiable, indicating their spread across various taxonomic groups

Modeling emergency department visit patterns for infectious disease complaints: results and application to disease surveillance

BACKGROUND: Concern over bio-terrorism has led to recognition that traditional public health surveillance for specific conditions is unlikely to provide timely indication of some disease outbreaks, either naturally occurring or induced by a bioweapon. In non-traditional surveillance, the use of health care resources are monitored in "near real" time for the first signs of an outbreak, such as increases in emergency department (ED) visits for respiratory, gastrointestinal or neurological chief complaints (CC). METHODS: We collected ED CCs from 2/1/94 – 5/31/02 as a training set. A first-order model was developed for each of seven CC categories by accounting for long-term, day-of-week, and seasonal effects. We assessed predictive performance on subsequent data from 6/1/02 – 5/31/03, compared CC counts to predictions and confidence limits, and identified anomalies (simulated and real). RESULTS: Each CC category exhibited significant day-of-week differences. For most categories, counts peaked on Monday. There were seasonal cycles in both respiratory and undifferentiated infection complaints and the season-to-season variability in peak date was summarized using a hierarchical model. For example, the average peak date for respiratory complaints was January 22, with a season-to-season standard deviation of 12 days. This season-to-season variation makes it challenging to predict respiratory CCs so we focused our effort and discussion on prediction performance for this difficult category. Total ED visits increased over the study period by 4%, but respiratory complaints decreased by roughly 20%, illustrating that long-term averages in the data set need not reflect future behavior in data subsets. CONCLUSION: We found that ED CCs provided timely indicators for outbreaks. Our approach led to successful identification of a respiratory outbreak one-to-two weeks in advance of reports from the state-wide sentinel flu surveillance and of a reported increase in positive laboratory test results