Categorizing FTE-like Boundary Layer Signatures Produced by the Kelvin-Helmholtz Instability Using Hall-MHD Simulations and Virtual Spacecraft

Magnetic reconnection and Kelvin-Helmholtz instability (KHI) are two fundamental processes at the planetary magnetospheres that can lead to plasma, momentum and energy transport over magnetospheric boundary. Flux Transfer Events (FTEs) are generally accepted to be produced by the magnetic reconnection at the dayside magnetopause. However, there are still other possible mechanisms which create FTE-like features in the boundary layer. Kelvin-Helmholtz instability can be one of the candidates. The deformed boundary driven by the KHI at the interface of two fluids usually leads to the bipolar signatures of the normal component of the magnetic field. By using two-dimensional Hall-MHD simulations, we study signatures observed by virtual satellites as they pass through KHI along different trajectories. For the same plasma parameters across the magnetosphere and magnetosheath, slightly adjusting the projection angle of the magnetic field will give us 12 combinations of in-plain components at both sides of the boundary. In addition, we assume 3 sets of spacecraft trajectories in each simulation, which totally bring 36 different KHI signatures. While the satellites encountered well-developed KH vortex and spine region, the signatures, when detected by a spacecraft in the magnetosphere, would be easily misidentified as FTEs. The presented analysis examines and categorizes these observed signatures that are clearly generated by the KHI. These results can be used as diagnostic when analyzing spacecraft data to help distinguish KHI created signatures from FTEs

Statistical aspects of omics data analysis using the random compound covariate

BACKGROUND: Dealing with high dimensional markers, such as gene expression data obtained using microarray chip technology or genomics studies, is a key challenge because the numbers of features greatly exceeds the number of biological samples. After selecting biologically relevant genes, how to summarize the expression of selected genes and then further build predicted model is an important issue in medical applications. One intuitive method of addressing this challenge assigns different weights to different features, subsequently combining this information into a single score, named the compound covariate. Investigators commonly employ this score to assess whether an association exists between the compound covariate and clinical outcomes adjusted for baseline covariates. However, we found that some clinical papers concerned with such analysis report bias p-values based on flawed compound covariate in their training data set. RESULTS: We correct this flaw in the analysis and we also propose treating the compound score as a random covariate, to achieve more appropriate results and significantly improve study power for survival outcomes. With this proposed method, we thoroughly assess the performance of two commonly used estimated gene weights through simulation studies. When the sample size is 100, and censoring rates are 50%, 30%, and 10%, power is increased by 10.6%, 3.5%, and 0.4%, respectively, by treating the compound score as a random covariate rather than a fixed covariate. Finally, we assess our proposed method using two publicly available microarray data sets. CONCLUSION: In this article, we correct this flaw in the analysis and the propose method, treating the compound score as a random covariate, can achieve more appropriate results and improve study power for survival outcomes

Reproducibility, stability, and accuracy of microbial profiles by fecal sample collection method in three distinct populations.

The gut microbiome likely plays a role in the etiology of multiple health conditions, especially those affecting the gastrointestinal tract. Little consensus exists as to the best, standard methods to collect fecal samples for future microbiome analysis. We evaluated three distinct populations (N = 132 participants) using 16S rRNA gene amplicon sequencing data to investigate the reproducibility, stability, and accuracy of microbial profiles in fecal samples collected and stored via fecal occult blood test (FOBT) or Flinders Technology Associates (FTA) cards, fecal immunochemical tests (FIT) tubes, 70% and 95% ethanol, RNAlater, or with no solution. For each collection method, based on relative abundance of select phyla and genera, two alpha diversity metrics, and four beta diversity metrics, we calculated intraclass correlation coefficients (ICCs) to estimate reproducibility and stability, and Spearman correlation coefficients (SCCs) to estimate accuracy of the fecal microbial profile. Comparing duplicate samples, reproducibility ICCs for all collection methods were excellent (ICCs ≥75%). After 4-7 days at ambient temperature, ICCs for microbial profile stability were excellent (≥75%) for most collection methods, except those collected via no-solution and 70% ethanol. SCCs comparing each collection method to immediately-frozen no-solution samples ranged from fair to excellent for most methods; however, accuracy of genus-level relative abundances differed by collection method. Our findings, taken together with previous studies and feasibility considerations, indicated that FOBT/FTA cards, FIT tubes, 95% ethanol, and RNAlater are excellent choices for fecal sample collection methods in future microbiome studies. Furthermore, establishing standard collection methods across studies is highly desirable

A Cross-Cultural Study on Teachers’ Use of Print and Digital Resources in Sweden, Finland, the USA, and Flanders : Some Methodological Challenges

Cross-cultural studies have inherent challenges as researchers from different cultural backgrounds attempt to make sense of similar-seeming material in unfamiliar contexts and communicate seemingly-obvious aspects of their own culture to outsiders (Clarke, 2013; Osborn, 2004). This contribution explores some of the methodological challenges in a cross-cultural study on teachers’ use of print and digital resources in four regions: Sweden, Finland, the USA, and Flanders (Belgium). All but one of the seven team members are insiders to one of the four contexts and to different extents outsiders to the other contexts. In order to benefit from insider-outsider perspectives, we designed five tools to develop alignment of insider and outsider lenses. We describe these tools in this contribution.Peer reviewe

Mathematics curriculum reform in the U.S., Finland, Sweden and Flanders : region-wide coherence versus teacher involvement?

Peer reviewe

The K giant stars from the LAMOST survey data I: identification, metallicity, and distance

We present a support vector machine classifier to identify the K giant stars from the LAMOST survey directly using their spectral line features. The completeness of the identification is about 75% for tests based on LAMOST stellar parameters. The contamination in the identified K giant sample is lower than 2.5%. Applying the classification method to about 2 million LAMOST spectra observed during the pilot survey and the first year survey, we select 298,036 K giant candidates. The metallicities of the sample are also estimated with uncertainty of $0.13\sim0.29$\,dex based on the equivalent widths of Mg$_{\rm b}$ and iron lines. A Bayesian method is then developed to estimate the posterior probability of the distance for the K giant stars, based on the estimated metallicity and 2MASS photometry. The synthetic isochrone-based distance estimates have been calibrated using 7 globular clusters with a wide range of metallicities. The uncertainty of the estimated distance modulus at $K=11$\,mag, which is the median brightness of the K giant sample, is about 0.6\,mag, corresponding to $\sim30$% in distance. As a scientific verification case, the trailing arm of the Sagittarius stream is clearly identified with the selected K giant sample. Moreover, at about 80\,kpc from the Sun, we use our K giant stars to confirm a detection of stream members near the apo-center of the trailing tail. These rediscoveries of the features of the Sagittarius stream illustrate the potential of the LAMOST survey for detecting substructures in the halo of the Milky Way.Comment: 24 pages, 20 figures, submitted to Ap

Zebrafish GDNF and its co-receptor GFR alpha 1 activate the human RET receptor and promote the survival of dopaminergic neurons in vitro

Glial cell line-derived neurotrophic factor ( GDNF) is a ligand that activates, through coreceptor GDNF family receptor alpha-1 (GFR alpha 1) and receptor tyrosine kinase "RET ", several signaling pathways crucial in the development and sustainment of multiple neuronal populations. We decided to study whether non-mammalian orthologs of these three proteins have conserved their function: can they activate the human counterparts? Using the baculovirus expression system, we expressed and purified Danio rerio RET, and its binding partners GFRa1 and GDNF, and Drosophila melanogaster RET and two isoforms of coreceptor GDNF receptor-like. Our results report high-level insect cell expression of posttranslationally modified and dimerized zebrafish RET and its binding partners. We also found that zebrafish GFRa1 and GDNF are comparably active as mammalian cell- produced ones. We also report the first measurements of the affinity of the complex to RET in solution: at least for zebrafish, the Kd for GFR alpha 1-GDNF binding RET is 5.9 mu M. Surprisingly, we also found that zebrafish GDNF as well as zebrafish GFRa1 robustly activated human RET signaling and promoted the survival of cultured mouse dopaminergic neurons with comparable efficiency to mammalian GDNF, unlike E. coli-produced human proteins. These results contradict previous studies suggesting that mammalian GFRa1 and GDNF cannot bind and activate non-mammalian RET and vice versa.Peer reviewe

Current-voltage correlations in interferometers

We investigate correlations of current at contacts and voltage fluctuations at voltage probes coupled to interferometers. The results are compared with correlations of current and occupation number fluctuations at dephasing probes. We use a quantum Langevin approach for the average quantities and their fluctuations. For higher order correlations we develop a stochastic path integral approach and find the generating functions of voltage or occupation number fluctuations. We also derive a generating function for the joint distribution of voltage or occupation number at the probe and current fluctuations at a terminal of a conductor. For energy independent scattering we found earlier that the generating function of current cumulants in interferometers with a one-channel dephasing or voltage probe are identical. Nevertheless, the distribution function for voltage and the distribution function for occupation number fluctuations differ, the latter being broader than that of former in all examples considered here.Comment: 23 pages, 10 figures, minor changes, additional appendix, added reference