Spontaneous and stimulated emission tuning characteristics of a Josephson junction in a microcavity

We have investigated theoretically the tuning characteristics of a Josephson junction within a microcavity for one-photon spontaneous emission and for one-photon and two-photon stimulated emission. For spontaneous emission, we have established the linear relationship between the magnetic induction and the voltage needed to tune the system to emit at resonant frequencies. For stimulated emission, we have found an oscillatory dependence of the emission rate on the initial Cooper pair phase difference and the phase of the applied field. Under specific conditions, we have also calculated the values of the applied radiation amplitude for the first few emission maxima of the system and for the first five junction-cavity resonances for each process. Since the emission of photons can be controlled, it may be possible to use such a system to produce photons on demand. Such sources will have applications in the fields of quantum cryptography, communications and computation

A Cartesian Grid Method for Shallow Waterflows over a Gravel Bed

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Antibacterial mechanisms identified through structural systems pharmacology

Background: The growing discipline of structural systems pharmacology is applied prospectively in this study to predict pharmacological outcomes of antibacterial compounds in Escherichia coli K12. This work builds upon previously established methods for structural prediction of ligand binding pockets on protein molecules and utilizes and expands upon the previously developed genome scale model of metabolism integrated with protein structures (GEM-PRO) for E. coli, structurally accounting for protein complexes. Carefully selected case studies are demonstrated to display the potential for this structural systems pharmacology framework in discovery and development of antibacterial compounds. Results: The prediction framework for antibacterial activity of compounds was validated for a control set of well-studied compounds, recapitulating experimentally-determined protein binding interactions and deleterious growth phenotypes resulting from these interactions. The antibacterial activity of fosfomycin, sulfathiazole, and trimethoprim were accurately predicted, and as a negative control glucose was found to have no predicted antibacterial activity. Previously uncharacterized mechanisms of action were predicted for compounds with known antibacterial properties, including (1-hydroxyheptane-1,1-diyl)bis(phosphonic acid) and cholesteryl oleate. Five candidate inhibitors were predicted for a desirable target protein without any known inhibitors, tryptophan synthase β subunit (TrpB). In addition to the predictions presented, this effort also included significant expansion of the previously developed GEM-PRO to account for physiological assemblies of protein complex structures with activities included in the E. coli K12 metabolic network. Conclusions: The structural systems pharmacology framework presented in this study was shown to be effective in the prediction of molecular mechanisms of antibacterial compounds. The study provides a promising proof of principle for such an approach to antibacterial development and raises specific molecular and systemic hypotheses about antibacterials that are amenable to experimental testing. This framework, and perhaps also the specific predictions of antibacterials, is extensible to developing antibacterial treatments for pathogenic E. coli and other bacterial pathogens

Restoration and Management of Healthy Wetland Ecosystems

fi=vertaisarvioitu|en=peerReviewed

Does gated beam delivery impact delivery accuracy on an Elekta linac?

In this study, we evaluated the performance of an Elekta linac in the delivery of gated radiotherapy. Delivery accuracy was examined with an emphasis on the impact of using short gating windows (low monitor unit beam-on segments) or long beam hold times. The performance was assessed using a 20cm by 20cm open field with the radiation delivered using a range of beam-on and beam-off time periods. Gated delivery measurements were also performed for two SBRT plans delivered using volumetric modulated arc therapy (VMAT). Tests included both free-breathing based gating (covering a variety of gating windows) and simulated breath-hold based gating. An IBA MatriXX 2D ion chamber array was used for data collection, and the gating accuracy at low MU was evaluated using gamma passing rates. For the 20 cm by 20 cm open field, the measurements generally showed close agreement between the gated and non-gated beam deliveries. Discrepancies, however, began to appear with a 5-to-1 ratio of the beam-off to beam-on times. The discrepancies observed for these tight gating windows can be attributed to the small number of monitor units delivered during each beam-on segment. Dose distribution analysis from the delivery of the two SBRT plans showed gamma passing rates (± 1%, 2%/1 mm) in the range of 95% to 100% for gating windows of 25%, 38%, 50%, 63%, 75%, and 83%. Using a simulated sinusoidal breathing signal with a 4 second period, the gamma passing rate of free-breathing gating and breath-hold gating deliveries were measured in the range of 95.7% to 100%. In conclusion, the results demonstrate that Elekta linacs can accurately deliver respiratory gated treatments for both free-breathing and breath-hold patients. Some caution should be exercised with the use of very tight gating windows

Cross-cultural validation of the Health Care Provider HIV/AIDS Stigma Scale (HPASS) in China

The study aimed to validate the Health Care Provider HIV/AIDS Stigma Scale among medical staff in China. The validation was conducted in four steps from March to December 2017: translation and back-translation; content validity test with six experts; test–retest reliability testing with 63 medical staff with 2 weeks interval; and structural validation with 349 medical staff from 52 hospitals with a convenience sample,using exploratory factor analysis,including principal component analysis and varimax rotation. The scale content validity index average was 0.88, while for test–retest reliability, the ICC was 0.87. Three factors of “discrimination”, “prejudice” and “stereotype” with 16 items were extracted and explained 59.61% variance. The Cronbach’s alpha value for the total scale was of 0.88, and for the three factors, the values were 0.89, 0.86 and 0.74, respectively. The discrimination factor showed identical means between Canadian medical students and Chinese medical staff, while the prejudice and stereotype factors had higher mean scores in the Chinese sample. The three-factor structure of Health Care Provider HIV/AIDS Stigma Scale was confirmed in Chinese medical staff with a simpler solution. This could provide a basis for trans-cultural application and comparison

Rapid oxygenation of Earths atmosphere 2.33 billion years ago

Molecular oxygen (O[subscript 2]) is, and has been, a primary driver of biological evolution and shapes the contemporary landscape of Earth’s biogeochemical cycles. Although “whiffs” of oxygen have been documented in the Archean atmosphere, substantial O2 did not accumulate irreversibly until the Early Paleoproterozoic, during what has been termed the Great Oxygenation Event (GOE). The timing of the GOE and the rate at which this oxygenation took place have been poorly constrained until now. We report the transition (that is, from being mass-independent to becoming mass-dependent) in multiple sulfur isotope signals of diagenetic pyrite in a continuous sedimentary sequence in three coeval drill cores in the Transvaal Supergroup, South Africa. These data precisely constrain the GOE to 2.33 billion years ago. The new data suggest that the oxygenation occurred rapidly—within 1 to 10 million years—and was followed by a slower rise in the ocean sulfate inventory. Our data indicate that a climate perturbation predated the GOE, whereas the relationships among GOE, “Snowball Earth” glaciation, and biogeochemical cycling will require further stratigraphic correlation supported with precise chronologies and paleolatitude reconstructions.National Science Foundation (U.S.) (EAR-1338810)National Natural Science Foundation (China) ((grant no. 41472170)Wellcome Trust Sanger Institute ( 111 Project grant no. B08030)National Basic Research Program of China (973 Program)United States. National Aeronautics and Space Administration (NASA Astrobiology Institute award NNA13AA90A

Using Decision Forest to Classify Prostate Cancer Samples on the Basis of SELDI-TOF MS Data: Assessing Chance Correlation and Prediction Confidence

Class prediction using “omics” data is playing an increasing role in toxicogenomics, diagnosis/prognosis, and risk assessment. These data are usually noisy and represented by relatively few samples and a very large number of predictor variables (e.g., genes of DNA microarray data or m/z peaks of mass spectrometry data). These characteristics manifest the importance of assessing potential random correlation and overfitting of noise for a classification model based on omics data. We present a novel classification method, decision forest (DF), for class prediction using omics data. DF combines the results of multiple heterogeneous but comparable decision tree (DT) models to produce a consensus prediction. The method is less prone to overfitting of noise and chance correlation. A DF model was developed to predict presence of prostate cancer using a proteomic data set generated from surface-enhanced laser deposition/ionization time-of-flight mass spectrometry (SELDI-TOF MS). The degree of chance correlation and prediction confidence of the model was rigorously assessed by extensive cross-validation and randomization testing. Comparison of model prediction with imposed random correlation demonstrated biologic relevance of the model and the reduction of overfitting in DF. Furthermore, two confidence levels (high and low confidences) were assigned to each prediction, where most misclassifications were associated with the low-confidence region. For the high-confidence prediction, the model achieved 99.2% sensitivity and 98.2% specificity. The model also identified a list of significant peaks that could be useful for biomarker identification. DF should be equally applicable to other omics data such as gene expression data or metabolomic data. The DF algorithm is available upon request