Characterizing the variation of propagation constants in multicore fibre

We demonstrate a numerical technique that can evaluate the core-to-core variations in propagation constant in multicore fibre. Using a Markov Chain Monte Carlo process, we replicate the interference patterns of light that has coupled between the cores during propagation. We describe the algorithm and verify its operation by successfully reconstructing target propagation constants in a fictional fibre. Then we carry out a reconstruction of the propagation constants in a real fibre containing 37 single-mode cores. We find that the range of fractional propagation constant variation across the cores is approximately $\pm2 \times 10^{-5}$.Comment: 17 pages; preprint format; 5 figures. Submitted to Optics Expres

Microwave-assisted synthesis and electrochemical evaluation of VO2 (B) nanostructures

Understanding how intercalation materials change during electrochemical operation is paramount to optimizing their behaviour and function and in situ characterization methods allow us to observe these changes without sample destruction. Here we first report the improved intercalation properties of bronze phase vanadium dioxide VO2 (B) prepared by a microwave-assisted route which exhibits a larger electrochemical capacity (232 mAh g-1) compared with VO2 (B) prepared by a solvothermal route (197 mAh g-1). These electrochemical differences have also been followed using in situ X-ray absorption spectroscopy allowing us to follow oxidation state changes as they occur during battery operation

Fast microwave-assisted synthesis of Li-stuffed garnets and insights into Li diffusion from muon spin spectroscopy

Lithium-stuffed garnets attract huge attention due to their outstanding potential as solid-state electrolytes for lithium batteries. However, there exists a persistent challenge in the reliable synthesis of these complex functional oxides together with a lack of complete understanding of the lithium-ion diffusion mechanisms in these important materials. Addressing these issues is critical to realizing the application of garnet materials as electrolytes in all solid-state lithium-ion batteries. In this work, a cubic phase garnet of nominal composition Li6.5Al0.25La2.92Zr2O12 is synthesized through a microwave-assisted solid-state route for the first time, reducing considerably the reaction times and heating temperatures. Lithium-ion diffusion behavior is investigated by electrochemical impedance spectroscopy (EIS) and state-of-art muon spin relaxation (mSR) spectroscopy, displaying activation energies of 0.55 0.03 eV and 0.19 0.01 eV respectively.  This difference arises from the high inter-grain resistance, which contributes to the total resistance in EIS measurements. In contrast, mSR acts as a local probe providing insights on the order of the lattice, giving an estimated value of 4.6210􀀀11 cm2s􀀀1 for the lithium diffusion coefficient. These results demonstrate the potential of this lithium-stuffed garnet as a solid-state electrolyte for all-solid state lithium-ion batteries, an area of growing interest in the energy storage community

Soil-related habitat specialization in dipterocarp rain forest tree species in Borneo

Summary 1 We conducted a field experiment to test whether aggregated spatial distributions were related to soil variation in locally sympatric tree species in the rain forests of Sarawak, Malaysia. Dryobalanops aromatica , Shorea laxa , and Swintonia schwenkii are naturally aggregated on low-fertility humult ultisols, Dryobalanops lanceolata and Hopea dryobalanoides on moderate-fertility udult ultisols and Shorea balanocarpoides is found on both soil types. 2 Seedlings of all six species were grown in a nested-factorial experiment for 20 months in humult and udult soils in gaps and in the understorey to test for soil-specific differences in performance. Phosphorus addition was used to test for effects due to P-limitation. 3 Four species showed significantly higher growth on their natural soils, but one humultsoil species ( D. aromatica ) and the broadly distributed species were not significantly affected by soil type. 4 One udult-soil species, D. lanceolata , had both lower relative growth rate and lower mycorrhizal colonization on humult soil. However, humult soils also had lower levels of Ca, Mg, K, N and probably water availability. 5 The overall ranking of growth rates among species was similar on the two soils. Growth rates were strongly positively correlated with leaf area ratio and specific leaf area among species in both soils. With the exception of D. aromatica , species of the higher-nutrient soils had higher growth rates on both soils. 6 Although P addition led to elevated soil-P concentrations, elevated root-and leaf-tissue P concentrations on both soils, there was no significant growth enhancement and therefore no evidence that P availability limits the growth or constrains the distribution of any of the six species in the field. Differences in soil water availability between soils may be more important. 7 Our results suggest that habitat-mediated differences in seedling performance strongly influence the spatial distributions of tropical trees and are therefore likely to play a key role in structuring tropical rain forest communities

Phase Evolution and Li Diffusion in LATP Solid-State Electrolyte Synthesized via a Direct Heat-Cycling Method

Herein, the direct synthesis of phase-pure lithium aluminum titanium phosphate (Li_{1.3}Al_{0.3}Ti_{1.7}(PO_{4})_{3}, LATP) solid-electrolyte powder in 220 min and relatively low temperatures (850 °C) is achieved via a new (cyclic) fast heat treatment (c-FHT) route. The complex structural evolution highlights rate-limited lithium incorporation of intermediate metal phosphates formed prior to the final phase-pure LATP. The prepared LATP product powder displays similar bulk (2 × 10^{−10} cm^{2} s^{−1}) and local (3 × 10^{−10} cm^{2} s^{−1}) values for lithium diffusion coefficients (D_{Li}) characterized by electrochemical impedance spectroscopy and muon spin relaxation (μSR), respectively. The similarity between both D_{Li} values suggests excellent retention of inter- and intraparticle lithium diffusion, which is attributed to the absence of deleterious surface impurities such as AlPO4. A low-energy barrier (E_{a} = 73 meV) of lithium diffusion is also estimated from the μSR data

Evaluating techniques for metagenome annotation using simulated sequence data

The advent of next-generation sequencing has allowed huge amounts of DNA sequence data to be produced, advancing the capabilities of microbial ecosystem studies. The current challenge is identifying from which microorganisms and genes the DNA originated. Several tools and databases are available for annotating DNA sequences. The tools, databases and parameters used can have a significant impact on the results: naïve choice of these factors can result in a false representation of community composition and function. We use a simulated metagenome to show how different parameters affect annotation accuracy by evaluating the sequence annotation performances of MEGAN, MG-RAST, One Codex and Megablast. This simulated metagenome allowed the recovery of known organism and function abundances to be quantitatively evaluated, which is not possible for environmental metagenomes. The performance of each program and database varied, e.g. One Codex correctly annotated many sequences at the genus level, whereas MG-RAST RefSeq produced many false positive annotations. This effect decreased as the taxonomic level investigated increased. Selecting more stringent parameters decreases the annotation sensitivity, but increases precision. Ultimately, there is a trade-off between taxonomic resolution and annotation accuracy. These results should be considered when annotating metagenomes and interpreting results from previous studies

Permeable, Non-irritating Prodrugs of Nonsteroidal and Steroidal Agents

Prodrugs containing an active drug molecule linked to a polyethylene glycol group, and a method of use thereof are described. Exemplary soluble ester prodrugs contain naproxen, triamcinolone acetonide, gancyclovir, taxol, cyclosporin, dideoxyinosine, trihydroxy steroids, and flurbiprofen molecules linked to polyethylene glycol (PEG) groups. Pharmaceutical compositions containing these prodrugs, and a method of using these esters for treating disease states or symptoms are also described

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network

Network Structure and Biased Variance Estimation in Respondent Driven Sampling

This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network