Anisotropic expansion of a thermal dipolar Bose gas

We report on the anisotropic expansion of ultracold bosonic dysprosium gases at temperatures above quantum degeneracy and develop a quantitative theory to describe this behavior. The theory expresses the post-expansion aspect ratio in terms of temperature and microscopic collisional properties by incorporating Hartree-Fock mean-field interactions, hydrodynamic effects, and Bose-enhancement factors. Our results extend the utility of expansion imaging by providing accurate thermometry for dipolar thermal Bose gases, reducing error in expansion thermometry from tens of percent to only a few percent. Furthermore, we present a simple method to determine scattering lengths in dipolar gases, including near a Feshbach resonance, through observation of thermal gas expansion.Comment: main text and supplement, 11 pages total, 4 figure

Neutrophilia and NETopathy as Key Pathologic Drivers of Progressive Lung Impairment in Patients With COVID-19

There is an urgent need for new therapeutic strategies to contain the spread of the novel coronavirus disease 2019 (COVID-19) and to curtail its most severe complications. Severely ill patients experience pathologic manifestations of acute respiratory distress syndrome (ARDS), and clinical reports demonstrate striking neutrophilia, elevated levels of multiple cytokines, and an exaggerated inflammatory response in fatal COVID-19. Mechanical respirator devices are the most widely applied therapy for ARDS in COVID-19, yet mechanical ventilation achieves strikingly poor survival. Many patients, who recover, experience impaired cognition or physical disability. In this review, we argue the need to develop therapies aimed at inhibiting neutrophil recruitment, activation, degranulation, and neutrophil extracellular trap (NET) release. Moreover, we suggest that currently available pharmacologic approaches should be tested as treatments for ARDS in COVID-19. In our view, targeting host-mediated immunopathology holds promise to alleviate progressive pathologic complications of ARDS and reduce morbidities and mortalities in severely ill patients with COVID-19

Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Huntzinger, D. N., Schaefer, K., Schwalm, C., Fisher, J. B., Hayes, D., Stofferahn, E., Carey, J., Michalak, A. M., Wei, Y., Jain, A. K., Kolus, H., Mao, J., Poulter, B., Shi, X., Tang, J., & Tian, H. Evaluation of simulated soil carbon dynamics in Arctic-Boreal ecosystems. Environmental Research Letters, 15(2), (2020): 025005, doi:10.1088/1748-9326/ab6784.Given the magnitude of soil carbon stocks in northern ecosystems, and the vulnerability of these stocks to climate warming, land surface models must accurately represent soil carbon dynamics in these regions. We evaluate soil carbon stocks and turnover rates, and the relationship between soil carbon loss with soil temperature and moisture, from an ensemble of eleven global land surface models. We focus on the region of NASA's Arctic-Boreal vulnerability experiment (ABoVE) in North America to inform data collection and model development efforts. Models exhibit an order of magnitude difference in estimates of current total soil carbon stocks, generally under- or overestimating the size of current soil carbon stocks by greater than 50 PgC. We find that a model's soil carbon stock at steady-state in 1901 is the prime driver of its soil carbon stock a hundred years later—overwhelming the effect of environmental forcing factors like climate. The greatest divergence between modeled and observed soil carbon stocks is in regions dominated by peat and permafrost soils, suggesting that models are failing to capture the frozen soil carbon dynamics of permafrost regions. Using a set of functional benchmarks to test the simulated relationship of soil respiration to both soil temperature and moisture, we find that although models capture the observed shape of the soil moisture response of respiration, almost half of the models examined show temperature sensitivities, or Q10 values, that are half of observed. Significantly, models that perform better against observational constraints of respiration or carbon stock size do not necessarily perform well in terms of their functional response to key climatic factors like changing temperature. This suggests that models may be arriving at the right result, but for the wrong reason. The results of this work can help to bridge the gap between data and models by both pointing to the need to constrain initial carbon pool sizes, as well as highlighting the importance of incorporating functional benchmarks into ongoing, mechanistic modeling activities such as those included in ABoVE.This work was supported by NASA'S Arctic Boreal Vulnerability Experiment (ABoVE; https://above.nasa.gov); NNN13D504T. Funding for the Multi-scale synthesis and Terrestrial Model Intercomparison Project (MsTMIP; https://nacp.ornl.gov/MsTMIP.shtml) activity was provided through NASA ROSES Grant #NNX10AG01A. Data management support for preparing, documenting, and distributing model driver and output data was performed by the Modeling and Synthesis Thematic Data Center at Oak Ridge National Laboratory (MAST-DC; https://nacp.ornl.gov), with funding through NASA ROSES Grant #NNH10AN681. Finalized MsTMIP data products are archived at the ORNL DAAC (https://daac.ornl.gov). We also acknowledge the modeling groups that provided results to MsTMIP. The synthesis of site-level soil respiration, temperature, and moisture data reported in Carey et al 2016a, 2016b) was funded by the US Geological Survey (USGS) John Wesley Powell Center for Analysis and Synthesis Award G13AC00193. Additional support for that work was also provided by the USGS Land Carbon Program. JBF carried out the research at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. California Institute of Technology. Government sponsorship acknowledged

kNN Classification of Epilepsy Brainwaves

Epilepsy is a disorder of the normal brain function by the existence of abnormal synchronous discharges in large groups of neurons in brain structures and it is estimated about 1% of the world’s population suffers from this disease [Tzallas et al., 2009]. It has been reported that the brainwave of Epilepsy patient mostly in sharp, spike and complex wave pattern [Tzallas et al., 2009]. In addition, Epilepsy brainwaves pattern lies in wide variety of Electroencephalogram (EEG) signals in formed of low-amplitude and polyspikes activity [Vargas et al., 2011]. Generally, this disease was examined through the brainwaves or EEG signals by clinical neurulogists. An EEG is a device to record the brainwaves in term of electrical activity from the brain. Brain patterns from wave shapes that are commonly sinusoidal and measured from peak to peak that range from 0.5 μV to 100 μV in amplitude. Moreover, the brainwaves have been categorized into four frequency bands, Beta (>13 Hz), Alpha (8-13 Hz), Theta (4-8 Hz) and Delta (0.5-4 Hz). All the frequency bands will be used to characterize the Epilepsy brainwave in terms of amplitude (voltage) and frequency [Mustafa et al., 2013]. The Epilepsy brainwaves were downloaded from http://www.vis.caltech.edu/~rodri/data.htm of Fp1 and Fp2 channels which is from rats. The brainwaves consists Epilepsy and non-Epilepsy samples. Then, the brainwaves were pre-processed to remove artefact (noise). Various methods had been introduced to detect spike-wave discharge in Epilepsy patient brainwave. Brainwave is nonstationary signal, therefore, time-frequency analysis is appropriate methods to analyse the signals[Tzallas et al., 2009, Vargas et al., 2011]. One of the most popular time-frequency analyses is ShortTime Fourier Transform (STFT). After the brainwaves were pre-processed, STFT was employed to the clean brainwaves. The STFT spectrogram was generated for four frequency bands of the samples

Modelling the effects of p-modulation doping in InAs/InGaAs quantum dot devices

A modelling routine has been developed to quantify effects present in p-modulation doped 1.3 μm InAs/InGaAs quantum dot laser and modulator devices. Utilising experimentally verified parameters, calculated modal absorption is compared to measurements, prior to simulation of structures under reverse and forward bias. Observed broadening and a reduction of absorption in p-doped structures is attributed primarily to increased carrier scattering rates and can bring benefit when structures are configured as optical modulators with enhancements in the figure of merit. However, increased carrier scattering limits the maximum modal gain that can be achieved for lasers. The state filling caused by p-doping only marginally reduces absorption but assists laser operation with increased differential gain and gain magnitude at lower current densities

Co-Variation between Seed Dormancy, Growth Rate and Flowering Time Changes with Latitude in Arabidopsis thaliana

Life-history traits controlling the duration and timing of developmental phases in the life cycle jointly determine fitness. Therefore, life-history traits studied in isolation provide an incomplete view on the relevance of life-cycle variation for adaptation. In this study, we examine genetic variation in traits covering the major life history events of the annual species Arabidopsis thaliana: seed dormancy, vegetative growth rate and flowering time. In a sample of 112 genotypes collected throughout the European range of the species, both seed dormancy and flowering time follow a latitudinal gradient independent of the major population structure gradient. This finding confirms previous studies reporting the adaptive evolution of these two traits. Here, however, we further analyze patterns of co-variation among traits. We observe that co-variation between primary dormancy, vegetative growth rate and flowering time also follows a latitudinal cline. At higher latitudes, vegetative growth rate is positively correlated with primary dormancy and negatively with flowering time. In the South, this trend disappears. Patterns of trait co-variation change, presumably because major environmental gradients shift with latitude. This pattern appears unrelated to population structure, suggesting that changes in the coordinated evolution of major life history traits is adaptive. Our data suggest that A. thaliana provides a good model for the evolution of trade-offs and their genetic basis.<br

Mindfulness-based cognitive therapy v. group psychoeducation for people with generalised anxiety disorder: randomised controlled trial

Background: Research suggests that an 8-week mindfulness-based cognitive therapy (MBCT) course may be effective for generalised anxiety disorder (GAD). Aims: To compare changes in anxiety levels among participants with GAD randomly assigned to MBCT, cognitive–behavioural therapy-based psychoeducation and usual care. Method: In total, 182 participants with GAD were recruited (trial registration number: CUHK_CCT00267) and assigned to the three groups and followed for 5 months after baseline assessment with the two intervention groups followed for an additional 6 months. Primary outcomes were anxiety and worry levels. Results: Linear mixed models demonstrated significant group × time interaction (F(4,148) = 5.10, P = 0.001) effects for decreased anxiety for both the intervention groups relative to usual care. Significant group × time interaction effects were observed for worry and depressive symptoms and mental health-related quality of life for the psychoeducation group only. Conclusions: These results suggest that both of the interventions appear to be superior to usual care for the reduction of anxiety symptoms