[Review of] D.C. Poole. Among the Sioux of Dakota: Eighteen Months Experience as an Indian Agent, 1869-70

From 1869 to 1870 many Oglala and Brule Sioux lived together on their first reservation, the Whetstone Agency, on the Missouri river near Fort Randall, South Dakota. Poole was the reservation agent from 1869-70, and his memoir of that period (published in 1881) introduces the drama of cultural conflict that persists to the present day. The agent had been ordered to use persuasion of every possible kind to induce the Lakota to abandon their way of life and to turn to farming. He had been instructed to regard his wards as children, but he often expresses admiration in many of his descriptions, though rarely in overt statement. Like a novel narrated by a persona whose views differ from that of the author, Poole seems to be expressing conscious limitations that his narrative somehow transcends

Deep Learning for Detecting Trees in the Urban Environment from LIDAR

Cataloguing and classifying trees in the urban environment is a crucial step in urban and environmental planning. However, manual collection and maintenance of this data is expensive and time-consuming. Algorithmic approaches that rely on remote sensing data have been developed for tree detection in forests, though they generally struggle in the more varied urban environment. This work proposes a novel method for the detection of trees in the urban environment that applies deep learning to remote sensing data. Specifically, we train a PointNet-based neural network to predict tree locations directly from LIDAR data augmented with multi-spectral imaging. We compare this model to numerous high-performant baselines on a large and varied dataset in the Southern California region. We find that our best model outperforms all baselines with a 75.5\% F-score and 2.28 meter RMSE, while being highly efficient. We then analyze and compare the sources of errors, and how these reveal the strengths and weaknesses of each approach

A re-evaluation of fixed effect(s) meta-analysis

Summary Meta-analysis is a common tool for synthesizing results of multiple studies. Among methods for performing meta-analysis, the approach known as ‘fixed effects’ or ‘inverse variance weighting’ is popular and widely used. A common interpretation of this method is that it assumes that the underlying effects in contributing studies are identical, and for this reason it is sometimes dismissed by practitioners. However, other interpretations of fixed effects analyses do not make this assumption, yet appear to be little known in the literature. We review these alternative interpretations, describing both their strengths and their limitations. We also describe how heterogeneity of the underlying effects can be addressed, with the same minimal assumptions, through either testing or meta-regression. Recommendations for the practice of meta-analysis are given; it is hoped that these will foster more direct connection of the questions that meta-analysts wish to answer with the statistical methods they choose.</jats:p

Bistable Operation of a Two-Section 1.3-mm InAs Quantum Dot Laser—Absorption Saturation and the Quantum Confined Stark Effect

Room temperature, continuous-wave bistability was observed in oxide-confined, two-section, 1.3- m quantum-dot (QD) lasers with an integrated intracavity quantum-dot saturable absorber. The origin of the hysteresis and bistability were shown to be due to the nonlinear saturation of the QD absorption and the electroabsorption induced by the quantum confined Stark effect

Individual Tree Detection in Large-Scale Urban Environments using High-Resolution Multispectral Imagery

We introduce a novel deep learning method for detection of individual trees in urban environments using high-resolution multispectral aerial imagery. We use a convolutional neural network to regress a confidence map indicating the locations of individual trees, which are localized using a peak finding algorithm. Our method provides complete spatial coverage by detecting trees in both public and private spaces, and can scale to very large areas. We performed a thorough evaluation of our method, supported by a new dataset of over 1,500 images and almost 100,000 tree annotations, covering eight cities, six climate zones, and three image capture years. We trained our model on data from Southern California, and achieved a precision of 73.6% and recall of 73.3% using test data from this region. We generally observed similar precision and slightly lower recall when extrapolating to other California climate zones and image capture dates. We used our method to produce a map of trees in the entire urban forest of California, and estimated the total number of urban trees in California to be about 43.5 million. Our study indicates the potential for deep learning methods to support future urban forestry studies at unprecedented scales

The Microevolution and Epidemiology of Staphylococcus aureus Colonization during Atopic Eczema Disease Flare.

Staphylococcus aureus is an opportunistic pathogen and variable component of the human microbiota. A characteristic of atopic eczema (AE) is colonization by S. aureus, with exacerbations associated with an increased bacterial burden of the organism. Despite this, the origins and genetic diversity of S. aureus colonizing individual patients during AE disease flares is poorly understood. To examine the microevolution of S. aureus colonization, we deep sequenced S. aureus populations from nine children with moderate to severe AE and 18 non-atopic children asymptomatically carrying S. aureus nasally. Colonization by clonal S. aureus populations was observed in both AE patients and control participants, with all but one of the individuals carrying colonies belonging to a single sequence type. Phylogenetic analysis showed that disease flares were associated with the clonal expansion of the S. aureus population, occurring over a period of weeks to months. There was a significant difference in the genetic backgrounds of S. aureus colonizing AE cases versus controls (Fisher exact test, P = 0.03). Examination of intra-host genetic heterogeneity of the colonizing S. aureus populations identified evidence of within-host selection in the AE patients, with AE variants being potentially selectively advantageous for intracellular persistence and treatment resistance.CPH was supported by Wellcome Trust (grant number 104241/z/14/z). MTGH, KAP, and KO were supported by the Scottish Infection Research Network and Chief Scientist Office through the Scottish Healthcare Associated Infection Prevention Institute consortium funding (CSO reference: SIRN10). Bioinformatics and computational biology analyses were supported by the University of St Andrews Bioinformatics Unit that is funded by a Wellcome Trust ISSF award (grant 097831/Z/11/Z). JP and MTGH were supported by Wellcome Trust grant 098051. AEM is supported by Biotechnology and Biological Sciences Research Council grant BB/M014088/1. SJB is supported by a Wellcome Trust Senior Research Fellowship in Clinical Science (106865/Z/15/Z)

Metamagnetic Quantum Criticality in Sr3Ru2O7

We consider the metamagnetic transition in the bilayer ruthenate, ${\rm Sr_3Ru_2O_7}$, and use this to motivate a renormalization group treatment of a zero-temperature quantum-critical end-point. We summarize the results of mean field theory and give a pedagogical derivation of the renormalization-group equations. These are then solved to yield numerical results for the susceptibility, the specific heat and the resistivity exponent which can be compared with measured data on ${\rm Sr_3Ru_2O_7}$ to provide a powerful test for the standard framework of metallic quantum criticality. The observed approach to the critical point is well-described by our theory explaining a number of unusual features of experimental data. The puzzling behaviour very near to the critical point itself, though, is not accounted for by this, or any other theory with a Fermi surface