Huisache is a major brush problem on native rangelands and pastures in South Texas. Although herbicide applications to foliage provide very high plant-kill levels, the same herbicides have not proven reliable when applied as broadcast ground or aerial foliar treatments. Aerial and ground broadcast herbicide foliar treatments were applied to 31 huisache sites. Soil temperature and soil moisture were measured at a depth of 30 cm at the time of herbicide application. Cumulative rainfall before herbicide application was recorded. Across all aerial treatments, plant mortality was 69% for plants shorter than 2 m versus 40% for plants taller than 2 m. Across all aerial- and ground-treated sites, plants shorter than 2 m had an average 89% mortality when cumulative 2-wk rainfall was at least 50 mm, versus 72% mortality with cumulative rainfall less than 50 mm. Average plant mortality was 84% when 4-wk cumulative rainfall was at least 76 mm, versus 71% with rainfall less than 76 mm; and 85% when, on a dry-to-wet scale of 0 to 10, soil moisture measured at least 8, versus 71% when soil moisture measured less than 8. In a separate aerial trial, plant-mortality effects of spray droplet size (417, 630, and 800 µm) and spray volume (37.4 L ha−1 and 93.5 L ha−1) were replicated and tested at a single study site in 2014. Plant mortality was lowest for the 93.5 L ha−1 and 800 µm treatment. Plant mortality rates for other treatments were similar, demonstrating a greater importance of droplet size than spray volume. Targeting huisache trees shorter than 2 m, when cumulative rainfall has reached at least 50 mm or at least 76 mm 2 or 4 wk before application, respectively, as well as maintaining spray droplet sizes no larger than 630 µm can increase herbicide efficacy with foliar broadcast applications.

This article presents a normative framework for the assessment of education policies and applies it to the issue of schools’ selecting their students on the basis of religious criteria. Such policies can be justified, and challenged, on many different grounds; public debate is not conducted in terms adequate to the task. The authors’ main objectives are to supplement with non-consequentialist considerations a recent, consequentialist, approach to the normative assessment of education policy proposed by Brighouse et al. (2016, 2018), and to apply the proposed framework to issues of school composition and selection. They argue, further, that policies allowing schools to select all their students on the basis of their parents’ religious affiliation cannot be justified.

In recent years, concerns about misinformation in the media have skyrocketed. President Donald Trump has repeatedly claimed that various news outlets are disseminating ‘fake news’ for political purposes. But when the information contained in mainstream media news reports provides no clear clues about its truth value or any indication of a partisan slant, do people rely on the congeniality of the news outlet to judge whether the information is true or false? In a survey experiment, we presented partisans (Democrats and Republicans) and ideologues (liberals and conservatives) with a news article excerpt that varied by source shown (CNN, Fox News, or no source) and content (true or false information), and measured their perceived accuracy of the information contained in the article. Our results suggest that the participants do not blindly judge the content of articles based on the news source, regardless of their own partisanship and ideology. Contrary to prevailing views on the polarization and politicization of news outlets, as well as on voters' growing propensity to engage in ‘partisan motivated reasoning,’ source cues are not as important as the information itself for partisans on both sides of the aisle.

Species distribution models (SDMs) are statistical tools used to develop continuous predictions of species occurrence. ‘Integrated SDMs’ (ISDMs) are an elaboration of this approach with potential advantages that allow for the dual use of opportunistically collected presence-only data and site-occupancy data from planned surveys. These models also account for survey bias and imperfect detection through the use of a hierarchical modelling framework that separately estimates the species–environment response and detection process. This is particularly helpful for conservation applications and predictions for rare species, where data are often limited and prediction errors may have significant management consequences. Despite this potential importance, ISDMs remain largely untested under a variety of scenarios. We performed an exploration of key modelling decisions and assumptions on an ISDM using the endangered Baird’s tapir (Tapirus bairdii) as a test species. We found that site area had the strongest effect on the magnitude of population estimates and underlying intensity surface and was driven by estimates of model intercepts. Selecting a site area that accounted for the individual movements of the species within an average home range led to population estimates that coincided with expert estimates. ISDMs that do not account for the individual movements of species will likely lead to less accurate estimates of species intensity (number of individuals per unit area) and thus overall population estimates. This bias could be severe and highly detrimental to conservation actions if uninformed ISDMs are used to estimate global populations of threatened and data-deficient species, particularly those that lack natural history and movement information. However, the ISDM was consistently the most accurate model compared to other approaches, which demonstrates the importance of this new modelling framework and the ability to combine opportunistic data with systematic survey data. Thus, we recommend researchers use ISDMs with conservative movement information when estimating population sizes of rare and data-deficient species. ISDMs could be improved by using a similar parameterization to spatial capture–recapture models that explicitly incorporate animal movement as a model parameter, which would further remove the need for spatial subsampling prior to implementation.

Weeds remain the most commonly cited concern of organic farmers. Without the benefit of synthetic herbicides, organic farmers must rely on a host of ecological weed management (EWM) practices to control weeds. Despite EWM’s ability to improve soil quality, the perceived rate of integrated EWM strategy adoption remains low. This low adoption is likely a result of the complexity in designing and evaluating EWM strategies, the tendency for outreach to focus on the risks of EWM strategies rather than their benefits, and a lack of quantitative measures linking the performance of EWM strategies to farmers’ on-farm objectives and practices. Here we report on the development and deployment of an easy-to-use online decision support tool (DST) that aids organic farmers in identifying their on-farm objectives, characterizing the performance of their practices, and evaluating EWM strategies recommended by an expert advisory panel. Informed by the principles of structured decision making, the DST uses multiple choice tasks to help farmers evaluate the short- and long-term trade-offs of EWM strategies, while also focusing their attention on their most important objectives. We then invited organic farmers across the United States, in particular those whose email addresses were registered on the USDA’s Organic Research Integrity Database, to engage the DST online. Results show considerable movement in participants’ (n = 45) preferences from practices focused on reducing weeding costs and labor in the short term to EWM strategies focused on improving soil quality in the long term. Indeed, nearly half of those farmers (48%) who initially ranked a strategy composed of their current practices highest ultimately preferred a better-performing EWM strategy focused on eliminating the weed seedbank over 5 yr.

Introduction: The Canadian population is aging and an increasing proportion of emergency department (ED) patients are seniors. ED visits among seniors are frequently instigated by a fall at home. Some of these patients develop intracranial hemorrhage (ICH) because of falling. There has been little research on the frequency of ICH in elderly patients who fall, and on which clinical factors are associated with ICH in these patients. The aim of this study was to identify the incidence of ICH, and the clinical features which are associated with ICH, in seniors who present to the ED having fallen. Methods: This was a prospective cohort study conducted in three EDs. Patients were included if they were age >65 years, and presented to the ED within 48 hours of a fall on level ground, off a bed/chair/toilet or down one step. Patients were excluded if they fell from a height, were knocked over by a vehicle or were assaulted. ED physicians recorded predefined clinical findings (yes/no) before any head imaging was done. Head imaging was done at the ED physician's discretion. All patients were followed for 6 weeks (both by telephone call and chart review at 6 weeks) for evidence of ICH. Associations between baseline clinical findings and the presence of ICH were assessed with multivariable logistic regression. Results: In total, 1753 patients were enrolled. The prevalence of ICH was 5.0% (88 patients), of whom 74 patients had ICH on the ED CT scan and 14 had ICH diagnosed during follow-up. 61% were female and the median age was 82 (interquartile range 75-88). History included hypertension in 76%, diabetes in 29%, dementia in 27%, stroke/TIA in 19%, major bleeding in 11% and chronic kidney disease in 11%. 35% were on antiplatelet therapy and 25% were on an anticoagulant. Only 4 clinical variables were independently associated with ICH: bruise/laceration on the head (odds ratio (OR): 4.3; 95% CI 2.7-7.0), new abnormalities on neurological examination (OR: 4.4; 2.4-8.1), chronic kidney disease (OR: 2.4; 1.3-4.6) and reduced GCS from baseline (OR: 1.9; 1.0-3.4). Neither anticoagulation (OR: 0.9; 0.5-1.6) nor antiplatelet use (OR: 1.1; 0.6-1.8) appeared to be associated with ICH. Conclusion: This prospective study found a prevalence of ICH of 5.0% in seniors after a fall, and that bruising on the head, abnormal neurological examination, abnormal GCS and chronic kidney disease were predictive of ICH.

This article compares the collective commemoration of martyrs to ascertain changes in cultural understandings of the relationship between the ultimate sacrifice offered by an individual and monarchal violence. This historical comparison is used to argue that changes in the nature of Christianity transformed the popular interpretation of sovereign violence from a desecrative to a redemptive force. While cultural individualism and political statism appear in secularized modernity as contradictory impulses, their birth in early modernity was induced by coherent and entirely consistent religious worldview.

Pesaran, Shin, and Smith (2001) (PSS) proposed a bounds procedure for testing for the existence of long run cointegrating relationships between a unit root dependent variable ( $y_{t}$ ) and a set of weakly exogenous regressors $\boldsymbol{x}_{t}$ when the analyst does not know whether the independent variables are stationary, unit root, or mutually cointegrated processes. This procedure recognizes the analyst’s uncertainty over the nature of the regressors but not the dependent variable. When the analyst is uncertain whether $y_{t}$ is a stationary or unit root process, the test statistics proposed by PSS are uninformative for inference on the existence of a long run relationship (LRR) between $y_{t}$ and $\boldsymbol{x}_{t}$ . We propose the long run multiplier (LRM) test statistic as a means of testing for LRRs without knowing whether the series are stationary or unit roots. Using stochastic simulations, we demonstrate the behavior of the test statistic given uncertainty about the univariate dynamics of both $y_{t}$ and $\boldsymbol{x}_{t}$ , illustrate the bounds of the test statistic, and generate small sample and approximate asymptotic critical values for the upper and lower bounds for a range of sample sizes and model specifications. We demonstrate the utility of the bounds framework for testing for LRRs in models of public policy mood and presidential success.

A subset ${\mathcal{X}}$ of a C*-algebra ${\mathcal{A}}$ is called irredundant if no $A\in {\mathcal{X}}$ belongs to the C*-subalgebra of ${\mathcal{A}}$ generated by ${\mathcal{X}}\setminus \{A\}$ . Separable C*-algebras cannot have uncountable irredundant sets and all members of many classes of nonseparable C*-algebras, e.g., infinite dimensional von Neumann algebras have irredundant sets of cardinality continuum.

There exists a considerable literature showing that the question whether every AF commutative nonseparable C*-algebra has an uncountable irredundant set is sensitive to additional set-theoretic axioms, and we investigate here the noncommutative case.

Assuming $\diamondsuit$ (an additional axiom stronger than the continuum hypothesis), we prove that there is an AF C*-subalgebra of ${\mathcal{B}}(\ell _{2})$ of density $2^{\unicode[STIX]{x1D714}}=\unicode[STIX]{x1D714}_{1}$ with no nonseparable commutative C*-subalgebra and with no uncountable irredundant set. On the other hand we also prove that it is consistent that every discrete collection of operators in ${\mathcal{B}}(\ell _{2})$ of cardinality continuum contains an irredundant subcollection of cardinality continuum.

Other partial results and more open problems are presented.

Energy dispersive X-ray fluorescence (EDXRF) analysis is finding increasing application in field assay of soils and stream sediments for geochemical prospecting; in borehole logging and core analysis for formation evaluation in mine control, and in on stream analysis for process control.

The analytical capability of the method is determined by the choice of source, the energy of the exciting radiation and the energy resolution of the detector. The nature of the samples, their atomic number and concentration are also important. However, the most dominant constraints on limits of detection are often imposed by the environment at the region of measurement: by the borehole condition, the nature of the rock face or the form of the particulates and stability of the fluid in a process stream.

A series of computer programs have been written (collectively called XRDQUAL) for automated identification of XRD patterns. The algorithms used in XRDQUAI, have been selected for maximum compatibility with computerbased calculations and decisions, XRDQUAI relies heavily on probabilistic logic and calculations. The overall sequence used can be divided into three general steps.