Enhancing visitor use management in parks and protected areas through qualitative research

Applied research aims to generate knowledge that can be used to improve policy and practice. In the field of visitor use management (VUM), researchers and park managers seek to generate knowledge regarding specific dimensions of visitor experiences within and across parks and other kinds of protected areas. A wide variety of management-centric questions are addressed through VUM research. In this article, we argue that to answer such questions, VUM researchers and managers can use qualitative methods (independent of or coupled with quantitative methods) to deepen our knowledge about visitor experiences while improving visitor use management policies and practices. We present current qualitative research designed to aid in the management of parks, and future directions for qualitative inquiry. Existing qualitative research and future possibilities call to expand our collective understanding of what kind of knowledge “counts” in VUM research

Development and validation of a NanoString BASE47 bladder cancer gene classifier

Background Recent molecular characterization of urothelial cancer (UC) has suggested potential pathways in which to direct treatment, leading to a host of targeted therapies in development for UC. In parallel, gene expression profiling has demonstrated that high-grade UC is a heterogeneous disease. Prognostic basal-like and luminal-like subtypes have been identified and an accurate transcriptome BASE47 classifier has been developed. However, these phenotypes cannot be broadly investigated due to the lack of a clinically viable diagnostic assay. We sought to develop and evaluate a diagnostic classifier of UC subtype with the goal of accurate classification from clinically available specimens. Methods Tumor samples from 52 patients with high-grade UC were profiled for BASE47 genes concurrently by RNAseq as well as NanoString. After design and technical validation of a BASE47 NanoString probeset, results from the RNAseq and NanoString were used to translate diagnostic criteria to the Nanostring platform. Evaluation of repeatability and accuracy was performed to derive a final Nanostring based classifier. Diagnostic classification resulting from the NanoString BASE47 classifier was validated on an independent dataset (n = 30). The training and validation datasets accurately classified 87% and 93% of samples, respectively. Results Here we have derived a NanoString-platform BASE47 classifier that accurately predicts basal-like and luminal-like subtypes in high grade urothelial cancer. We have further validated our new NanoString BASE47 classifier on an independent dataset and confirmed high accuracy when compared with our original Transcriptome BASE47 classifier. Conclusions The NanoString BASE47 classifier provides a faster turnaround time, a lower cost per sample to process, and maintains the accuracy of the original subtype classifier for better clinical implementation

Comment on: “Peatland carbon stocks and burn history: Blanket bog peat core evidence highlights charcoal impacts on peat physical properties and long-term carbon storage”, by A. Heinemeyer, Q. Asena, W.L. Burn and A.L. Jones (Geo: Geography and Environment. 2018; e00063)

A recent paper by Heinemeyer et al. (2018) in this journal has suggested that the use of prescribed fire may enhance carbon accumulation in UK upland blanket bogs. We challenge this finding based on a number of concerns with the original manuscript including the lack of an unburned control, insufficient replication, unrecognised potential confounding factors, and potentially large inaccuracies in the core dating approach used to calculate carbon accumulation rates. We argue that burn‐management of peatlands is more likely to lead to carbon loss than carbon gain

Impact of herbicides on soil biology and function

There is a growing awareness among farmers about the importance of soil for sustaining crop production and providing beneficial ecosystem services. Over the last 2 decades, global herbicide use has increased as farmers have shifted to more sustainable conservation tillage practices and have adopted herbicide-tolerant crop cultivars. The implications of increased herbicide use for soil biology are being questioned, but a comprehensive review on this topic is lacking. In this chapter we outline the chemistry and use of the major herbicide classes, and review the soil functions relevant to crop production. We then collate and critically evaluate the evidence for herbicide effects on soil biota and activity. In general, most studies suggest that the impacts of herbicide application on soil function are only minor and/or temporary. However, there are some instances where findings consistently suggest effects that could significantly alter soil function. These include disruptions to earthworm ecology in soils exposed to glyphosate and atrazine; inhibition of soil N-cycling (including biological N2-fixation, mineralization and nitrification) by sulfonylurea herbicides in alkaline or low organic matter soils; and site-specific increases in disease resulting from the application of a variety of herbicides. Issues with extrapolating these findings to broadacre farming include the lack of a consistent framework for assessing herbicide risk to soil biology, the relevance of the magnitude of herbicide impacts compared with the impacts of other soil management practices such as tillage or crop rotation, the complexity of herbicide formulations and mixtures, and the limited number of long-term field studies.Michael T. Rose, Timothy R. Cavagnaro, Craig A. Scanlan, Terry J. Rose, Tony Vancov, Stephen Kimber, Ivan R. Kennedy, Rai S. Kookana, Lukas Van Zwiete

Semiparametric theory and empirical processes in causal inference

In this paper we review important aspects of semiparametric theory and empirical processes that arise in causal inference problems. We begin with a brief introduction to the general problem of causal inference, and go on to discuss estimation and inference for causal effects under semiparametric models, which allow parts of the data-generating process to be unrestricted if they are not of particular interest (i.e., nuisance functions). These models are very useful in causal problems because the outcome process is often complex and difficult to model, and there may only be information available about the treatment process (at best). Semiparametric theory gives a framework for benchmarking efficiency and constructing estimators in such settings. In the second part of the paper we discuss empirical process theory, which provides powerful tools for understanding the asymptotic behavior of semiparametric estimators that depend on flexible nonparametric estimators of nuisance functions. These tools are crucial for incorporating machine learning and other modern methods into causal inference analyses. We conclude by examining related extensions and future directions for work in semiparametric causal inference

Photoaffinity labeling of the lysosomal neuraminidase from bovine testis

Abstract ASA-NeuAc2en, a photoreactive arylazide derivative of sialic acid, is shown to be a powerful competitive inhibitor of lysosomal neuraminidase from bovine testis (Ki ≈ 21 μM). Photoaffinity labeling and partial purification of preparations containing this lysosomal neuraminidase activity result in specifically and non-specifically labeled polypeptides. Only labeling in a 55 kDa polypeptide is found to be specific, since it could be prevented by the competitive neuraminidase inhibitor NeuAc2en. We conclude that the 55 kDa polypeptide in the bovine testis β-galactosidase/neuraminidase/protective protein complex contains the catalytic site of neuraminidase

Demonstration of the temporal matter-wave Talbot effect for trapped matter waves

We demonstrate the temporal Talbot effect for trapped matter waves using ultracold atoms in an optical lattice. We investigate the phase evolution of an array of essentially non-interacting matter waves and observe matter-wave collapse and revival in the form of a Talbot interference pattern. By using long expansion times, we image momentum space with sub-recoil resolution, allowing us to observe fractional Talbot fringes up to 10th order.Comment: 17 pages, 7 figure

Kaon Production and Kaon to Pion Ratio in Au+Au Collisions at \snn=130 GeV

Mid-rapidity transverse mass spectra and multiplicity densities of charged and neutral kaons are reported for Au+Au collisions at \snn=130 GeV at RHIC. The spectra are exponential in transverse mass, with an inverse slope of about 280 MeV in central collisions. The multiplicity densities for these particles scale with the negative hadron pseudo-rapidity density. The charged kaon to pion ratios are $K^+/\pi^- = 0.161 \pm 0.002 {\rm (stat)} \pm 0.024 {\rm (syst)}$ and $K^-/\pi^- = 0.146 \pm 0.002 {\rm (stat)} \pm 0.022 {\rm (syst)}$ for the most central collisions. The $K^+/\pi^-$ ratio is lower than the same ratio observed at the SPS while the $K^-/\pi^-$ is higher than the SPS result. Both ratios are enhanced by about 50% relative to p+p and $\bar{\rm p}$+p collision data at similar energies.Comment: 6 pages, 3 figures, 1 tabl

Longitudinal double-spin asymmetry and cross section for inclusive neutral pion production at midrapidity in polarized proton collisions at sqrt(s) = 200 GeV

We report a measurement of the longitudinal double-spin asymmetry A_LL and the differential cross section for inclusive Pi0 production at midrapidity in polarized proton collisions at sqrt(s) = 200 GeV. The cross section was measured over a transverse momentum range of 1 < p_T < 17 GeV/c and found to be in good agreement with a next-to-leading order perturbative QCD calculation. The longitudinal double-spin asymmetry was measured in the range of 3.7 < p_T < 11 GeV/c and excludes a maximal positive gluon polarization in the proton. The mean transverse momentum fraction of Pi0's in their parent jets was found to be around 0.7 for electromagnetically triggered events.Comment: 6 pages, 3 figures, submitted to Phys. Rev. D (RC