Your search

From La Folie Elisa By Gwenaëlle Aubry Translated by Wendeline A. Hardenberg

He was the Master of Scents. He ruled over them, classified them, harnessed them, recombined them, invented them, and above all took care of their dis...

A.D. 1034 The king and queen took hawks out that day, and their retinue trailed along hills and swales, watching as Duncan and then Suthen lifted gauntleted arms and opened their fists. The hunting…

Human activities have caused massive losses of natural populations across the globe. Like many groups, amphibians have experienced substantial declines worldwide, driven by environmental changes such as habitat conversion, pollution, and disease emergence. Each of these drivers is often found in close association with the presence of roads. Here we report a novel consequence of roads affecting an amphibian native to much of North America, the wood frog (Rana sylvatica). Across 38 populations distributed from southern to central New England, we found that adult wood frogs living adjacent to roads had higher incidence and severity of oedema (indicated by obvious bloating caused by subcutaneous fluid accumulation) during the breeding season than frogs living away from the influence of roads. This effect was best explained by increased conductivity of breeding ponds, probably caused by runoff pollution from road salt used for de-icing. Oedema severity was negatively correlated with locomotor performance in more northerly populations. Interestingly, northern populations experience more intense winters, which tends to result in more de-icing salt runoff and increased energetic demands associated with overwintering cryoprotection needs. Thus, this emerging consequence of roads appears to impose potential fitness costs associated with locomotion, and these effects might be most impactful on populations living in regions where de-icing is most intense. Together, our findings reveal a novel set of impacts of roads and runoff pollution on wood frog physiology and performance, which seem likely to contribute to population decline. Given the global prevalence of roads and increasing salinisation of freshwater habitats, oedema and related impacts could be widespread consequences faced by amphibian populations across much of the planet's temperate zones. © 2022 John Wiley & Sons Ltd.

Variance and invariance are two powerful mathematical ideas to support geometrical and spatial thinking, yet there is limited research about teachers’ knowledge of variance and invariance. In this paper, we examined how high school teachers deal with the task of looking for invariant properties in a dynamic geometry environment (DGE) setting. Specifically, we investigated if they even attend to invariant properties; what invariant properties they discern and discuss; and how DGE can support such discernment. Our analysis found that teachers tend to discern and discuss invariant properties mainly when they were probed to consider invariance. We also found four categories of invariant properties that seem to be important for a robust and rich understanding of geometric objects in the context of invariance and DGE. The use of DGE allowed teachers to see and interact with invariant properties, thus suggesting that accessing geometry dynamically may have structural affordances especially when exploring invariance. Teachers were able to enact different DGE movements to discern and discuss invariant properties, as well as to reason with and about them. We also saw that teachers’ backgrounds and past experiences can play an important role in their descriptions of invariant properties. Possible future research directions and implications to teacher education are discussed. © 2022, The Author(s), under exclusive licence to Springer Nature B.V.

Understanding gluon density distributions and how they are modified in nuclei are among the most important goals in nuclear physics. In recent years, diffractive vector meson production measured in ultraperipheral collisions (UPCs) at heavy-ion colliders has provided a new tool for probing the gluon density. In this Letter, we report the first measurement of J/ψ photoproduction off the deuteron in UPCs at the center-of-mass energy sNN=200 GeV in d+Au collisions. The differential cross section as a function of momentum transfer -t is measured. In addition, data with a neutron tagged in the deuteron-going zero-degree calorimeter is investigated for the first time, which is found to be consistent with the expectation of incoherent diffractive scattering at low momentum transfer. Theoretical predictions based on the color glass condensate saturation model and the leading twist approximation nuclear shadowing model are compared with the data quantitatively. A better agreement with the saturation model has been observed. With the current measurement, the results are found to be directly sensitive to the gluon density distribution of the deuteron and the deuteron breakup process, which provides insights into the nuclear gluonic structure. © 2022 American Physical Society.

We present the first results of a multiyear program to map the orbits of M-dwarf multiples within 25 pc. The observations were conducted primarily during 2019-2020 using speckle interferometry at the Southern Astrophysical Research Telescope in Chile, using the High-Resolution Camera mounted on the adaptive optics module (HRCam+SAM). The sample of nearby M dwarfs is drawn from three sources: multiples from the RECONS long-term astrometric monitoring program at the SMARTS 0.9 m; known multiples, for which these new observations will enable or improve orbit fits; and candidate multiples flagged by their astrometric fits in Gaia Data Release 2 (DR2). We surveyed 333 of our 338 M dwarfs via 830 speckle observations, detecting companions for 63% of the stars. Most notably, this includes new companions for 76% of the subset selected from Gaia DR2. In all, we report the first direct detections of 97 new stellar companions to the observed M dwarfs. Here we present the properties of those detections, the limits of each nondetection, and five orbits with periods 0.67-29 yr already observed as part of this program. Companions detected have projected separations of 0.″024-2.″0 (0.25-66 au) from their primaries and have ΔI ≲ 5.0 mag. This multiyear campaign will ultimately map complete orbits for nearby M dwarfs with periods up to 3 yr, and provide key epochs to stretch orbital determinations for binaries to 30 yr. © 2022. The Author(s). Published by the American Astronomical Society.

This article analyses the economic size and resilience of five established definitions of the Blue Economy across two geographical locations: Scotland (UK) and Michigan (USA). The article analyses sector-level employment, labor productivity and Gross Value Added (GVA) data, and uses graphical representations to highlight the differences in conceptualizing the Blue Economy in ways that affect its weight and contribution to regional economies. Further, it analyses how each definition has fared in the post-2007/2011 crisis, assessing their resilience. This novel work tackles the emerging discourse around the Blue Economy by highlighting its regional character, and by problematizing the divergent definitions of the concept. © 2022 Elsevier B.V.

The Internet contains large amounts of adult content. With only a few taps, or mis-taps, an under-aged user can be exposed to age-inappropriate content. Currently, this can be avoided by creating age-restricted profiles or restricting users to child-friendly applications (apps). However, these existing measures are time-consuming, laborious, and require a higher level of technical literacy than many parents can afford. We believe a better solution is to use a browser or an app that automatically detects the user's age then applies any appropriate content filters. For such a browser/app to be developed, we must learn that age estimation can indeed be performed with an acceptable rate of error. To that end, we created an Android app that collects biometric touchscreen data from elementary school, middle school, high school, and university students. Touch samples were collected from participants aged 5 to 61 on both smartphones and tablets. We focused exclusively on zoom-in and zoom-out touchscreen data samples. We made this decision because we found the zoom gesture to be rich with data and highly used among the most popular applications. Furthermore, we identify a niche within the current research landscape: no other machine learning experiments have leveraged the benefits of the zoom gesture for age estimation. We collected a total of 41,911 zoom data samples. From each zoom sample, 90 features were extracted. Those features were then used to train and test on six regressors and six classifiers to build a method that can accurately estimate the user's age from their touchscreen behavior. The regressors performed with the best mean absolute errors (MAEs) of 2.27 and 2.54 years for smartphones and tablets, respectively. The classifiers performed with the best accuracies of 90% and 91% for smartphones and tablets, respectively. Given these results, it is our belief that not only is touch-based age estimation viable, but developing a child-safe browser or a parental control app with this underlying technology is a worthwhile endeavor. © 2022 Elsevier Ltd

The internet has changed the way that many people access written works. Books and articles, of various lengths, in several formats can be bought and accessed online, both legally and illegally. Texts in even shorter form are originating through forums, SMS, blogs, emails, and social media. Automating the process of determining the authorship of posted texts would help combat online piracy of copyrighted text and plagiarism. In addition, authorship identification could help detect fraudulent email messages from dangerous sources and combat cyberattacks by identifying authentic sources. We experiment with several machine learning algorithms on a limited set of public domain literature to identify the most efficient method of authorship identification using the least amount of samples. Different sized data sets are created by 5 predefined rounds of random sampling of 1500 word blocks on a total of 28 text books from a corpus of 7 authors. Traditional methods of authorship identification, such as Naive Bayes, Artificial Neural Network, and Support Vector Machine are implemented in addition to using a modern Deep Learning Neural Network for classification. Thirteen stylometric features are extracted ranging from character based, word based, and syntactic features. Our model consistently showed that Support Vector Machine out performs other classification methods. © 2020