Theoretical photodetachment cross section for the negative atomic oxygen ion

Theoretical photodetachment cross section for negative atomic oxygen io

Deep carbon storage potential of buried floodplain soils.

Soils account for the largest terrestrial pool of carbon and have the potential for even greater quantities of carbon sequestration. Typical soil carbon (C) stocks used in global carbon models only account for the upper 1 meter of soil. Previously unaccounted for deep carbon pools (>1 m) were generally considered to provide a negligible input to total C contents and represent less dynamic C pools. Here we assess deep soil C pools associated with an alluvial floodplain ecosystem transitioning from agricultural production to restoration of native vegetation. We analyzed the soil organic carbon (SOC) concentrations of 87 surface soil samples (0-15 cm) and 23 subsurface boreholes (0-3 m). We evaluated the quantitative importance of the burial process in the sequestration of subsurface C and found our subsurface soils (0-3 m) contained considerably more C than typical C stocks of 0-1 m. This deep unaccounted soil C could have considerable implications for global C accounting. We compared differences in surface soil C related to vegetation and land use history and determined that flooding restoration could promote greater C accumulation in surface soils. We conclude deep floodplain soils may store substantial quantities of C and floodplain restoration should promote active C sequestration

A new B-dot probe-based diagnostic for amplitude, polarization, and wavenumber measurements of ion cyclotron range-of frequency fields on ASDEX Upgrade

A new B-dot probe-based diagnostic has been installed on an ASDEX Upgrade tokamak to characterize ion cyclotron range-of frequency (ICRF) wave generation and interaction with magnetized plasma. The diagnostic consists of a field-aligned array of B-dot probes, oriented to measure fast and slow ICRF wave fields and their field-aligned wavenumber (k(//)) spectrum on the low field side of ASDEX Upgrade. A thorough description of the diagnostic and the supporting electronics is provided. In order to compare the measured dominant wavenumber of the local ICRF fields with the expected spectrum of the launched ICRF waves, in-air near-field measurements were performed on the newly installed 3-strap ICRF antenna to reconstruct the dominant launched toroidal wavenumbers (k(tor)). Measurements during a strap current phasing scan in tokamak discharges reveal an upshift in k(//) as strap phasing is moved away from the dipole configuration. This result is the opposite of the k(tor) trend expected from in-air near-field measurements; however, the near-field based reconstruction routine does not account for the effect of induced radiofrequency (RF) currents in the passive antenna structures. The measured exponential increase in the local ICRF wave field amplitude is in agreement with the upshifted k(//), as strap phasing moves away from the dipole configuration. An examination of discharges heated with two ICRF antennas simultaneously reveals the existence of beat waves at 1 kHz, as expected from the difference of the two antennas' operating frequencies. Beats are observed on both the fast and the slow wave probes suggesting that the two waves are coupled outside the active antennas. Although the new diagnostic shows consistent trends between the amplitude and the phase measurements in response to changes applied by the ICRF antennas, the disagreement with the in-air near-field measurements remains. An electromagnetic model is currently under development to address this issue. (C) 2015 AIP Publishing LLC

The Arabidopsis Mei2 homologue AML1 binds AtRaptor1B, the plant homologue of a major regulator of eukaryotic cell growth

BACKGROUND: TOR, the target of the antibiotic rapamycin in both yeast and mammalian cells, is a potent cell growth regulator in all eukaryotes. It acts through the phosphorylation of downstream effectors that are recruited to it by the binding partner Raptor. In Arabidopsis, Raptor activity is essential for postembryonic growth. Though comparative studies suggest potential downstream effectors, no Raptor binding partners have been described in plants. RESULTS: AtRaptor1B, a plant Raptor homologue, binds the AML1 (Arabidopsis Mei2-like 1) protein in a yeast two-hybrid assay. This interaction is mediated by the N-terminal 219 residues of AML1, and marks AML1 as a candidate AtTOR kinase substrate in plants. The AML1 N-terminus additionally carries transcriptional activation domain activity. Plants homozygous for insertion alleles at the AML1 locus, as well as plants homozygous for insertion alleles at all five loci in the AML gene family, bolt earlier than wild-type plants. CONCLUSION: AML1 interacts with AtRaptor1B, homologue of a protein that recruits substrates for phosphorylation by the major cell-growth regulator TOR. Identification of AML1 as a putative downstream effector of TOR gives valuable insights into the plant-specific mode of action of this critical growth regulator

Isolation of a cDNA clone representing a gene with minimal expression in nit-4 mutant Neurospora crassa mycelia, yet not regulated by nitrate induction.

We report the isolation of a cDNA clone containing a segment of DNA representing a gene which appears to require the nit-4 gene product for expression, yet is not regulated by nitrate induction. Such a cDNA is a novel finding with respect to the known function of the nit-4 gene

Development of an integrated cognitive behavioral therapy for anxiety and opioid use disorder: Study protocol and methods

Opioid use disorder is a highly disabling psychiatric disorder, and is associated with both significant functional disruption and risk for negative health outcomes such as infectious disease and fatal overdose. Even among those who receive evidence-based pharmacotherapy for opioid use disorder, many drop out of treatment or relapse, highlighting the importance of novel treatment strategies for this population. Over 60% of those with opioid use disorder also meet diagnostic criteria for an anxiety disorder; however, efficacious treatments for this common co-occurrence have not be established. This manuscript describes the rationale and methods for a behavioral treatment development study designed to develop and test an integrated cognitive-behavioral therapy for those with co-occurring opioid use disorder and anxiety disorders. The aims of the study are (1) to develop and pilot test a new manualized cognitive behavioral therapy for co-occurring opioid use disorder and anxiety disorders, (2) to test the efficacy of this treatment relative to an active comparison treatment that targets opioid use disorder alone, and (3) to investigate the role of stress reactivity in both prognosis and recovery from opioid use disorder and anxiety disorders. Our overarching aim is to investigate whether this new treatment improves both anxiety and opioid use disorder outcomes relative to standard treatment. Identifying optimal treatment strategies for this population are needed to improve outcomes among those with this highly disabling and life-threatening disorder.This study was funded by NIDA grant DA035297. The funding source had no involvement in the study design, analysis and interpretation of data, writing of the report, or the decision to submit the article for publication. (DA035297 - NIDA)Accepted manuscrip

A controlled experiment for the empirical evaluation of safety analysis techniques for safety-critical software

Context: Today's safety critical systems are increasingly reliant on software. Software becomes responsible for most of the critical functions of systems. Many different safety analysis techniques have been developed to identify hazards of systems. FTA and FMEA are most commonly used by safety analysts. Recently, STPA has been proposed with the goal to better cope with complex systems including software. Objective: This research aimed at comparing quantitatively these three safety analysis techniques with regard to their effectiveness, applicability, understandability, ease of use and efficiency in identifying software safety requirements at the system level. Method: We conducted a controlled experiment with 21 master and bachelor students applying these three techniques to three safety-critical systems: train door control, anti-lock braking and traffic collision and avoidance. Results: The results showed that there is no statistically significant difference between these techniques in terms of applicability, understandability and ease of use, but a significant difference in terms of effectiveness and efficiency is obtained. Conclusion: We conclude that STPA seems to be an effective method to identify software safety requirements at the system level. In particular, STPA addresses more different software safety requirements than the traditional techniques FTA and FMEA, but STPA needs more time to carry out by safety analysts with little or no prior experience.Comment: 10 pages, 1 figure in Proceedings of the 19th International Conference on Evaluation and Assessment in Software Engineering (EASE '15). ACM, 201

Used-habitat calibration plots: a new procedure for validating species distribution, resource selection, and step-selection models

“Species distribution modeling” was recently ranked as one of the top five “research fronts” in ecology and the environmental sciences by ISI's Essential Science Indicators (Renner and Warton 2013), reflecting the importance of predicting how species distributions will respond to anthropogenic change. Unfortunately, species distribution models (SDMs) often perform poorly when applied to novel environments. Compounding on this problem is the shortage of methods for evaluating SDMs (hence, we may be getting our predictions wrong and not even know it). Traditional methods for validating SDMs quantify a model's ability to classify locations as used or unused. Instead, we propose to focus on how well SDMs can predict the characteristics of used locations. This subtle shift in viewpoint leads to a more natural and informative evaluation and validation of models across the entire spectrum of SDMs. Through a series of examples, we show how simple graphical methods can help with three fundamental challenges of habitat modeling: identifying missing covariates, non-linearity, and multicollinearity. Identifying habitat characteristics that are not well-predicted by the model can provide insights into variables affecting the distribution of species, suggest appropriate model modifications, and ultimately improve the reliability and generality of conservation and management recommendations