An in situ toxicity identification and evaluation water analysis system: Laboratory validation

It is difficult to assess the toxicity of a single stressor and establish a strong stressor–causality link when multiple stressors coexist. Toxicity identification evaluation (TIE) methodology uses a series of chemical and physical manipulations to fractionate compounds within a matrix and systematically identify potential toxicants. The current US Environmental Protection Agency application of TIE can provide valuable information but often lacks ecological realism and is subject to laboratory‐related artifacts. An in situ TIE device (iTIED) was designed to assess the sources of toxicity in aquatic ecosystems. For this laboratory validation, each unit was equipped with a sorbent resin chamber, an organism exposure chamber, a water collection container, and a peristaltic pump. Chemical analyses of water processed by each iTIED unit were compared with both lethal and sublethal molecular responses of the organisms. The compound removal effectiveness of different sorbent resins was also compared. In addition to successfully fractionating diverse chemical mixtures, the iTIED demonstrated a potential for early detection of molecular biomarkers, which could identify chronic toxicity that may go unnoticed in traditional TIE assays. Utilizing this novel in situ system will reduce the uncertainty associated with laboratory‐based simulations and aid management efforts in targeting compounds that pose the greatest threat. Environ Toxicol Chem 2017;36:1636–1643. © 2016 SETACPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137342/1/etc3696.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137342/2/etc3696_am.pd

Internet gaming disorder: feeling the flow of social games

Introduction: Gaming Disorder (GD) was added to the recent publication of the International Classification of Diseases (ICD-11) by the World Health Organization. This aligns with recommendations of the fifth edition of the Diagnostic Statistical Manual for Mental Disorders (DSM-5), issued by the American Psychiatric Association. Accordingly, further relevant research has been invited. The interplay between preference for online social game genres, the degree of online Flow (or immersive pleasure) experienced, and the gamer's biological gender were examined here as contributing factors of IGD. Method: A normative sample of adult internet gamers was collected online (N=237, Age=18–59, Males=157; 66%; Females=80; 34%). Participants completed the nine-item Internet Gaming Disorder Scale-Short Form (IGDS-SF9), the Online Flow Questionnaire (OFQ), and also self-reported demographics and internet/gaming behaviours. Results: Mediation and moderated mediation analyses indicated that the level of online Flow experienced considerably mediated the association between the preference for social games genres and the intensity of IGD behaviours across both biological genders. Conclusions: Results suggest that the level of online Flow experienced constitutes a risk factor in relation to the development of IGD. Furthermore, games which mandate social interaction with others present to be conducive to online Flow, and thus enhancing IGD risk irrespective of the biological gender of the gamer. Implications and limitations of the study are discussed. Keywords: Internet gaming disorder, Flow, Online flow, Social games, Massively multiplayer online role playing games, Multiplayer online battle arena, Gaming addictio

Information-based data selection for ensemble data assimilation

Ensemble-based data assimilation is rapidly proving itself as a computationally-efficient and skilful assimilation method for numerical weather prediction, which can provide a viable alternative to more established variational assimilation techniques. However, a fundamental shortcoming of ensemble techniques is that the resulting analysis increments can only span a limited subspace of the state space, whose dimension is less than the ensemble size. This limits the amount of observational information that can effectively constrain the analysis. In this paper, a data selection strategy that aims to assimilate only the observational components that matter most and that can be used with both stochastic and deterministic ensemble filters is presented. This avoids unnecessary computations, reduces round-off errors and minimizes the risk of importing observation bias in the analysis. When an ensemble-based assimilation technique is used to assimilate high-density observations, the data-selection procedure allows the use of larger localization domains that may lead to a more balanced analysis. Results from the use of this data selection technique with a two-dimensional linear and a nonlinear advection model using both in situ and remote sounding observations are discussed

The acheulean handaxe : More like a bird's song than a beatles' tune?

© 2016 Wiley Periodicals, Inc. KV is supported by the Netherlands Organization for Scientific Research. MC is supported by the Canada Research Chairs Program, the Social Sciences and Humanities Research of Canada, the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund, and Simon Fraser UniversityPeer reviewedPublisher PD

Body Segment Differences in Surface Area, Skin Temperature and 3D Displacement and the Estimation of Heat Balance during Locomotion in Hominins

The conventional method of estimating heat balance during locomotion in humans and other hominins treats the body as an undifferentiated mass. This is problematic because the segments of the body differ with respect to several variables that can affect thermoregulation. Here, we report a study that investigated the impact on heat balance during locomotion of inter-segment differences in three of these variables: surface area, skin temperature and rate of movement. The approach adopted in the study was to generate heat balance estimates with the conventional method and then compare them with heat balance estimates generated with a method that takes into account inter-segment differences in surface area, skin temperature and rate of movement. We reasoned that, if the hypothesis that inter-segment differences in surface area, skin temperature and rate of movement affect heat balance during locomotion is correct, the estimates yielded by the two methods should be statistically significantly different. Anthropometric data were collected on seven adult male volunteers. The volunteers then walked on a treadmill at 1.2 m/s while 3D motion capture cameras recorded their movements. Next, the conventional and segmented methods were used to estimate the volunteers' heat balance while walking in four ambient temperatures. Lastly, the estimates produced with the two methods were compared with the paired t-test. The estimates of heat balance during locomotion yielded by the two methods are significantly different. Those yielded by the segmented method are significantly lower than those produced by the conventional method. Accordingly, the study supports the hypothesis that inter-segment differences in surface area, skin temperature and rate of movement impact heat balance during locomotion. This has important implications not only for current understanding of heat balance during locomotion in hominins but also for how future research on this topic should be approached

Georectifying drone image data over water surfaces without fixed ground control: Methodology, uncertainty assessment and application over an estuarine environment

Light-weight consumer-grade drones have the potential to provide geospatial image data to study a broad range of oceanic processes. However, rigorously tested methodologies to effectively and accurately geolocate and rectify these image data over mobile and dynamic water surfaces, where temporally fixed points of reference are unlikely to exist, are limited. We present a simple to use automated workflow for georectifying individual aerial images using position and orientation data from the drone’s on-board sensor (i.e. direct-georectification). The presented methodology includes correcting for camera lens distortion and viewing angle and exploits standard mathematics and camera data processing techniques. The method is used to georectify image datasets from test flights with different combinations of altitude and camera angle. Using a test site over land, directly-georectified images, as well as the same images georectified using standard photogrammetry software, are evaluated using a network of known ground control points. The novel methodology performs well with the camera at nadir (both 10 m and 25 m above ground level) and exhibits a mean spatial accuracy of ±1 m. The same accuracy is achieved when the camera angle is 30◦ at 10 m above ground level but decreases to ±2.9 m at 30◦ and 25 m. The accuracy changes because the uncertainties are a function of the altitude and angle of the camera versus the ground. Drone in-flight positioning errors can reduce the accuracy further to ±5 m with the camera at 30◦ and 25 m. An ensemble approach is used to map the uncertainties within the camera field-of-view to show how they change with viewing distance and drone position and orientation. The complete approach is demonstrated over an estuarine environment that includes the shoreline and open water, producing results consistent with the land-based field-tests of accuracy. Overall, the workflow presented here provides a low cost and agile solution for direct-georectification of drone-captured image data over water surfaces. This approach could be used for collecting and processing image data from drones or ship-mounted cameras to provide observations of ocean colour, sea-ice, ocean glitter, sea surface roughness, white-cap coverage, coastal water quality, and river plumes. The Python scripts for the complete image georectification workflow, including uncertainty map generation, are available from https://github.com/JamieLab/SArONG

Morphological variation of genetically confirmed Alouatta Pigra × A. palliata hybrids from a natural hybrid zone in Tabasco, Mexico

While hybridization has been reported for a large number of primate taxa, there is a general lack of data on hybrid morphology for wild individuals with known genetic ancestry. A confirmed hybrid zone for the closely related Neotropical primates Alouatta palliata and A. pigra has provided a unique opportunity to study primate hybrid morphological variation. Here we used molecular evidence based on mitochondrial, Y‐chromosome, and autosomal data to assess hybrid ancestry. We conducted univariate and multivariate statistical comparisons of morphometric data collected from individuals both outside and within the hybrid zone in Tabasco, Mexico. Our results show that of all the hybrids detected ( N = 128), only 12% of them were approximately genetically intermediate, and none of them were first generation hybrids. Univariate pairwise comparisons among parental individuals, multigenerational backcrossed hybrids, and intermediate hybrids showed that overall, multigenerational backcrossed hybrids resemble the parental species with which they share most of their alleles. Conversely, intermediates were highly variable. Similarly, principal component analysis depicts an overlap between the parental species and their backcrosses when considering overall morphological differences. Finally, discriminant function analysis of the morphological variables was overall unreliable for classifying individuals into their assigned genotypic classes. Taken together, our results suggest that primate natural hybridization studies should incorporate molecular methods for determining ancestry, because morphology may not always be a reliable indicator of hybrid status. Hybrid zones could comprise a large number of multigenerational backcrossed hybrids that are indistinguishable from the parental species. The implications for studying hybridization in the primate fossil record are discussed. Am J Phys Anthropol, 2013. © 2012 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/96397/1/22196_ftp.pd